Hire Adobe Experience Managers Backed by a U.S. Delivery Team

Looking to hire an Adobe Experience Manager? Our Adobe Experience Managers bring senior-level expertise, backed by a U.S. delivery team.

HIRE NOW
  • 100+

    Fully Vetted Developers

  • 24h

    Average Matching Time

  • 300

    Project Delivered

net-developers-iowa certificate
angular-developers-oklahoma-city certificate
app-development-kansas certificate
ai-company-kansas certificate
ai-company-south-dakota certificate
computer-vision-denver certificate
drupal-developers-wyoming certificate
flutter-developers-maryland certificate
generative-ai-boston certificate
generative-ai-seattle certificate
java-developers-alabama certificate
java-developers-idaho certificate
laravel-developers-denver certificate
machine-learning-kansas-city certificate
nextjs-developer-portland certificate
nodejs-developers-albuquerque certificate
php-developers-little-rock certificate
python-django-developers-denver certificate
react-native-developer-indiana certificate
react-native-developer-nashville certificate
software-developers-albuquerque certificate
software-developers-west-virginia certificate
swift-company-alabama certificate
web-developers-little-rock certificate

Hire remote Adobe Experience Manager

Discover developers that match your project requirements.

No exact match for this specialty yet — here are related experts from our network.

Aditya P.
Available Now
Verified in SoftDoesAditya P.
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Aditya P.
Available Now
Aditya P.Verified in SoftDoes
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Aditya P.
Available Now
Aditya P.Verified in SoftDoes
DevOps Engineer/ Site Reliability Engineer
US 🇺🇸English (B2)Senior
GoPythonUNIX Shell ScriptingPHP

Principal DevOps / Site Reliability Engineer with 14+ years of software engineering experience (including freelance development) and 9+ years of professional DevOps/SRE experience. Expert in designing and automating scalable cloud infrastructure across AWS, GCP, Azure, a company Cloud, with deep expertise in Kubernetes, Docker, OpenShift, Terraform, Ansible, GitOps (ArgoCD/FluxCD), CI/CD, Go, and Python. Experienced in building multi-cloud, high-availability platforms, infrastructure automation, cloud migrations, and developer platforms. Currently working as Principal Engineer at FOX, previously held senior engineering roles at Hippo Insurance, a company, and Morgan Stanley.

Andrea M.
Available Now
Verified in SoftDoesAndrea M.
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrea M.
Available Now
Andrea M.Verified in SoftDoes
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrea M.
Available Now
Andrea M.Verified in SoftDoes
AI Solutions Architect/Engineer
IT 🇮🇹English (C1)Senior
PythonLangChainLangGraphGoogle Cloud

I am a solutions architect and engineer with 5+ years of experience in designing and implementing cloud-based AI solutions. Solid skills across applied AI, software engineering, cloud architecture and DevOps practices, built on years of field experience, allow me to drive AI initiatives from concept to production, leveraging AI tools to boost delivery speed without compromising on deliverable quality.

Andrii V.
Available Now
Verified in SoftDoesAndrii V.
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Andrii V.
Available Now
Andrii V.Verified in SoftDoes
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Andrii V.
Available Now
Andrii V.Verified in SoftDoes
Senior Python Engineer
CA 🇨🇦English (C1)Senior
PythonDjangoFastAPIFlask

Senior Python Developer with 11+ years of experience designing scalable backend systems and microservice architectures across data analytics, logistics, and fintech platforms. Proven track record leading engineering teams and delivering cloud-native solutions on AWS and Kubernetes. Recently led development of AI-powered and real-time observability platforms using modern Python frameworks and large-scale data technologies. Strong background in system architecture, distributed systems, and mentoring teams in Agile environments.

Boris S.
Available Now
Verified in SoftDoesBoris S.
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Boris S.
Available Now
Boris S.Verified in SoftDoes
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Boris S.
Available Now
Boris S.Verified in SoftDoes
Senior AI/ML Engineer
BG 🇧🇬English (B2)Senior
PythonSQLBashFastAPI

Senior AI/ML Engineer with 10+ years of experience designing and deploying large-scale machine learning and generative AI systems in production environments. Specialized in LLM architectures, agentic AI systems, distributed ML infrastructure, and end-to-end MLOps platforms. Proven track record of delivering high-impact AI products including diagnostic AI systems improving accuracy by 38% and enterprise ML platforms accelerating data pipelines by 40%. Experienced in leading cross-functional teams, architecting scalable AI platforms, and driving AI innovation across healthcare, enterprise analytics, and automation domains.

Eugene M.
Available Now
Verified in SoftDoesEugene M.
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Eugene M.
Available Now
Eugene M.Verified in SoftDoes
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Eugene M.
Available Now
Eugene M.Verified in SoftDoes
DevOps Engineer
ES 🇪🇸English (C2)Senior
AWSGoogle CloudKubernetesTerraform

10+ years in IT, 7+ years focused on DevOps/SysOps/SRE. Currently - Tech Lead at a U.S. company.

Hripsime S.
Available Now
Verified in SoftDoesHripsime S.
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Hripsime S.
Available Now
Hripsime S.Verified in SoftDoes
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Hripsime S.
Available Now
Hripsime S.Verified in SoftDoes
AI Engineer | Data Scientist
FR 🇫🇷English (C1)Senior
Deep LearningMachine LearningInterpretabilityConvolutional Neural Networks

AI engineer with 6+ years of professional experience, available to start a new challenging role in stimulating and innovative company.

Mario J.
Available Now
Verified in SoftDoesMario J.
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Mario J.
Available Now
Mario J.Verified in SoftDoes
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Mario J.
Available Now
Mario J.Verified in SoftDoes
Senior Data Engineer
GT 🇬🇹English (C1)Senior
PythonSQLPandasPySpark

Over the past 8 years, I have gained ample experience in ETL/ELT, Snowflake, Airflow, and Data Warehouse. I have been responsible for Data Lake Support and creating new ETL/ELT processes within AWS using either Snowflake, Glue, Airflow, dbt, Xplenty, Docker, or Custom Python Scripts with APIs. I have also worked as an Application Architect, which includes over 50 different services across AWS. I needed to create pipelines, organizations, and permissions within AWS Infrastructure to meet business requirements while optimizing costs. My previous work includes over four years as a Data Analyst, creating and supporting BI Tools like Sisense, Quicksight, and Power BI/Tableau. I managed and created dashboards, widgets, and Data Architecture with Sisense and Redshift. I was also the Support Engineer for Sisense Installation and Maintenance. I would describe myself as reliable and able to undertake complex situations with unique solutions. I have over 7 years of experience in the Data sector, over 17+ years of SQL experience, and 20+ years as a Developer. I’m also a mid-QA Automation Engineer, which gives me a better idea of the attention to detail a developer needs to attain to complete development within the time limit and without affecting PROD releases. My other skills include being a Sysadmin in both Windows and Linux environments, a company Web Services AWS, a company 365 Portal, JumpCloud, 1Password, and Slack. I also have DBA knowledge, including creating servers and Data Warehouses. I'm an expert in MS Office and can automate with macros. I’m also a Cybersecurity advocate since I’m always looking for ways to protect data and user permissions. I have been in Agile Development with Jira in Kanban and Scrum for the past 4 years. And I have also created bots to automatize process alerts and configurations with Slack APIs and AWS to help my teammates get prompt feedback from the ETL pipelines.

Raphael O.
Available Now
Verified in SoftDoesRaphael O.
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Raphael O.
Available Now
Raphael O.Verified in SoftDoes
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Raphael O.
Available Now
Raphael O.Verified in SoftDoes
Snr. Staff Software Engineer
US 🇺🇸English (Native)Senior
LeadershipAgileBig dataAPI design

I am a technical leader and problem solver who designs and delivers scalable, distributed software and AI systems that create measurable business value. I have led cross-functional teams and platform initiatives, translating complex requirements into reliable, production-ready solutions built on open standards. My experience spans architecting, mentoring, and driving execution across diverse technology stacks, with a strong focus on operational excellence, product impact, and long-term system sustainability.

Santiago G.
Available Now
Verified in SoftDoesSantiago G.
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Santiago G.
Available Now
Santiago G.Verified in SoftDoes
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Santiago G.
Available Now
Santiago G.Verified in SoftDoes
DevOps Engineer
US 🇺🇸English (C1)Senior
LinuxBashDockerAnsible

Energetic, adaptable, mission-focused and multilingual MBA professional with more than 20 years of experience in IT, Business Intelligence, Marketing and Finance in 4 multinationals. Proven track record of finding creative solutions to solving challenges. Effective presenter who collaborates well in teams and across divisions. Passion for learning and acquiring new skills every day.

Thierry M.
Available Now
Verified in SoftDoesThierry M.
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thierry M.
Available Now
Thierry M.Verified in SoftDoes
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thierry M.
Available Now
Thierry M.Verified in SoftDoes
Senior Infrastructure / Production Engineer
US 🇺🇸English (C1)Senior
AWSGoogle CloudAzureKubernetes

15+ years of experience designing and operating large-scale distributed systems and latency-sensitive production platforms. Expertise in multi-region Kubernetes infrastructure, hybrid cloud environments, and production reliability engineering, with a strong focus on scalability, fault tolerance, observability, and operational automation. Deep experience building and operating hybrid bare-metal and cloud platforms (AWS, GCP), including Kubernetes infrastructure, traffic routing, CI/CD systems, and production observability stacks supporting globally distributed workloads. Strong background in incident response, Linux systems, networking, distributed systems troubleshooting, and infrastructure automation using Terraform and Python. Focused on end-to-end ownership of production infrastructure platforms while partnering closely with engineering teams to improve reliability, security, deployment consistency, and operational efficiency.

Thomas S.
Available Now
Verified in SoftDoesThomas S.
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Thomas S.
Available Now
Thomas S.Verified in SoftDoes
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Thomas S.
Available Now
Thomas S.Verified in SoftDoes
Technical leader at a company AI Core
DE 🇩🇪English (C1)Team Lead
LeadershipMentorshipGenerative AIPyTorch

Technical leader at a company AI Core, building and operating cloud-native AI platform services from prototype to production. Hands-on across backend engineering, distributed systems, and Kubernetes, driving technical direction and delivery across teams without direct authority.

Tzechung K.
Available Now
Verified in SoftDoesTzechung K.
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

Tzechung K.
Available Now
Tzechung K.Verified in SoftDoes
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

Tzechung K.
Available Now
Tzechung K.Verified in SoftDoes
Lead AI/ML Developer
US 🇺🇸English (Native)Senior
Claude CodeOpenAI CodexGoogle AntigravityLLM Fine-Tuning

Software Engineer with 10+ years of AI/ML experience and proven expertise in developing LLM-powered applications, generative AI systems, and ad engines. Strong track record of scaling ML platforms from inception to 1,500+ users at a company, building production AI systems, and creating innovative ad solutions. Experienced in full software development lifecycle with deep knowledge of PyTorch, TensorFlow, and modern AI frameworks including LangChain, LangGraph, and various LLM APIs.

Discover More Adobe Experience Managers in the SoftDoes NetworkRegister to view more

What our Adobe Experience Managers can build

Not sure which engagement model fits?

SoftDoes takes full ownership of delivery, combining project management, engineering, design, and QA into one accountable team focused on successful outcomes.

Explore Services

FIND THE
RIGHT expert, FASTER

Choose a role. Filter by technology.
Discover developers that match your project requirements.

How to hire a Adobe Experience Manager

01
BROWSE PROFILESRIGHT NOW

Fill out a short form and see who's on the bench. Real profiles, verified histories.

02
Interview1-3 DAYS

Tell us what you need. We propose two or three candidates from the bench; you interview them directly.

03
OnboardWEEK ONE

Your engineer starts on your project. Contract, payments, and the guarantee run through us.

US VS. THE DATABASE

Time to Start
Talent Quality
Technical Vetting
Flexibility
Operational Overhead
Cost Efficiency
cursor
<SoftDoes>
Time to Start
1-2 weeks
Talent Quality
Senior-only engineers
Technical Vetting
Multi-stage screening
Flexibility
Scale up or down anytime
Operational Overhead
As managed as you want
Cost Efficiency
Competitive, fee-free
Talent Marketplaces
Time to Start
1-3 months
Talent Quality
Mixed experience levels
Technical Vetting
One screen, then gone
Flexibility
Contract restrictions
Operational Overhead
Partially managed
Cost Efficiency
Agency markup
In-House Hiring
Time to Start
2-6 months
Talent Quality
Depends on market
Technical Vetting
Internal responsibility
Flexibility
Long-term commitment
Operational Overhead
Fully internal
Cost Efficiency
Highest total cost

Frequently Asked Questions

Everything you need to know about deploying, scaling, and securing your neural agents with SoftDoes. Can’t find an answer?

How long does it take to hire an Adobe Experience Manager through SoftDoes?

SoftDoes typically matches prescreened senior AEM talent to your project within days, not months. Because every professional in our network has already been vetted through live architecture challenges and real world scenario reviews, the process skips the lengthy screening cycles that plague traditional recruitment. Once matched, your AEM expert can begin onboarding immediately, with a structured 30/60/90 day ramp protocol designed to deliver visible impact from the first month. The exact timeline depends on the complexity of your AEM architecture and the specificity of the role, but most engagements move from initial discovery call to active project kickoff in under two weeks.

What does it cost to hire an Adobe Experience Manager?

Cost varies significantly based on engagement model, seniority, and work location. For context, Adobe AEM salaries range from $178,200 to $289,000 annually for full time employees, with geographic variation (for example, New York commands the higher end of that range). Freelance AEM experts charge between $50 to $150 per hour, while senior AEM consultants typically earn $65 to $80 per hour. SoftDoes engagements are structured to deliver better value than a full time hire when you factor in the hidden costs of traditional recruitment: benefits, onboarding ramp time, management overhead, and the risk of a bad hire that can easily exceed $200K in total losses. We scope pricing to your specific project needs and provide transparent cost breakdowns during the discovery session.

What engagement models are available (dedicated hire, pod, contract)?

SoftDoes offers three primary engagement models tailored to your engineering reality. A dedicated hire model embeds a senior AEM professional directly into your team for ongoing platform development and maintenance. A pod model deploys a small cross functional team (typically an architect, one or two developers, and a QA lead) for defined deliverables like cloud migrations, new site launches, or e commerce implementations. A contract model provides senior AEM architects for strategic guidance, architecture reviews, and technical oversight on a flexible schedule. All models include engineering led delivery oversight, and you can transition between models as your project scope evolves.

How do you ensure time zone alignment with an Adobe Experience Manager?

SoftDoes is a North America focused partner, which means our talent network is concentrated in US and Canadian time zones. Every engagement is scoped with time zone overlap requirements defined upfront, ensuring your AEM expert participates in standups, architecture reviews, and cross functional meetings during your core business hours. For teams with distributed operations, we establish communication protocols and async workflows that maintain velocity without requiring 24 hour availability. The goal is seamless integration with your existing development rhythm, not a coordination tax.

How does SoftDoes technically vet an Adobe Experience Manager?

Our technical evaluation pipeline is designed to surface real capability, not memorized trivia. Candidates complete live problem solving exercises, such as mapping a legacy AEM on premise deployment to AEM as a Cloud Service with explicit tradeoff analysis around cost, performance, and risk. They undergo a real world scenario architecture review where they identify bottlenecks, propose improvements, and demonstrate knowledge of caching strategy, DAM performance, and cloud native architecture. We evaluate communication under pressure through simulated incident scenarios, and assess cross functional culture fit through discussions that mirror the non engineering constraints they will face working with content, marketing, and compliance teams. We also verify credentials: relevant certifications such as Adobe Certified Expert and Adobe Certified Master, proficiency in Java, HTML, CSS, JavaScript, Apache Sling, and OSGi, along with confirmed experience with AEM Sites, digital asset management, and multi site management across enterprise environments.

What happens if the Adobe Experience Manager isn't the right fit, or I need to scale up or down?

SoftDoes provides a zero risk replacement guarantee. If your AEM expert does not meet your technical standards or fails to integrate effectively with your team, we replace them at no additional cost. There is no severance negotiation, no HR process, and no project interruption. Scaling is equally straightforward: you can add team members as project demands increase or reduce scope as deliverables complete, without the contractual friction of traditional employment. This flexibility is core to how we support clients who need to manage engineering budgets carefully while maintaining delivery velocity on critical Adobe Experience Manager initiatives.

The Executive Guide to Hiring an Adobe Experience Manager

Do you have an interesting idea?Contact us
Do you have an interesting idea?Contact us

A single bad Adobe Experience Manager hire can quietly drain six figures in wasted salary, stalled migrations, and compounding technical debt before anyone flags the problem. A slow hiring pipeline is no better: every quarter without the right AEM expert is a quarter your digital experience platform underperforms, your content teams bottleneck, and your competitors pull ahead. This playbook distills a field tested strategy to define, vet, and onboard top tier Adobe Experience Manager talent, built from real lessons in the engineering trenches so you can skip the expensive trial and error.

The Real Stakes

What Actually Separates a Senior AEM Expert from an Order Taker

Most job descriptions for Adobe Experience Manager developers read like a copy paste of Adobe's documentation. That tells you nothing about whether a candidate can own outcomes. A senior AEM expert operates as a technical leader, not a ticket closer. Here is what that looks like in practice:

  • Ownership of experience architecture. They design reusable AEM components, template libraries, content fragment structures, and experience fragments that scale across brands and markets. Adobe Experience Manager emphasizes reusable component libraries and structured content models, and a senior hire builds them to last.
  • Tradeoff decision making under real constraints. Speed versus maintainability versus performance. Cloud versus on premise versus hybrid. Custom code versus out of the box capability. They make these calls daily and can explain the reasoning behind each one.
  • Technical leadership for deployment and scaling. This means hands on work with AEM as a Cloud Service, CI/CD pipelines, dispatcher caching, CDN strategy, performance tuning, and zero downtime upgrades. Knowledge of CI/CD pipelines is critical for deploying AEM solutions in cloud environments, and AEM as a Cloud Service requires a cloud native architecture approach.
  • Cross functional guidance. A senior Adobe Experience Manager professional collaborates with UX, content authors, digital marketing, analytics, and legal. They establish governance, authoring workflows, and DAM taxonomy strategy rather than waiting for someone else to define it.
  • Technical debt and legacy migration management. Refactoring monolithic custom code, mapping upgrade paths from AEM 6.x to AEM as a Cloud Service, migrating between on premise and cloud. This is where deep expertise separates veterans from juniors learning on your budget.
  • Risk and compliance ownership. Accessibility, privacy, regulatory compliance, disaster recovery, uptime SLAs, and security testing. A senior hire surfaces risk before it reaches production, not after.

On the technical side, expect mastery in Java, Apache Sling, OSGi, JCR (Jackrabbit Oak), and modern front end technologies like HTML, CSS, and JavaScript. They should demonstrate familiarity with AEM integration to third party APIs, headless delivery (GraphQL, SPA frameworks like React Native), and the full Adobe ecosystem including Adobe Analytics, Adobe Campaign, and Adobe Workfront. Hands on experience with AEM Sites and component development is essential, alongside proficiency in digital asset management workflows.

AEM experts typically have 5+ years of extensive experience, and the strongest candidates hold credentials such as Adobe Certified Expert or Adobe Certified Master.

The Business Case: Financial and Operational Impact

Hiring the right Adobe Experience Manager talent is not a staffing decision. It is an investment with measurable ROI vectors:

  • Technical debt reduction. Every duplicated component, outdated module, or patched workaround increases future upgrade and maintenance cost. A senior hire pays down that debt systematically, saving multiples of their cost over time. IDC research shows AEM Assets implementations reduced duplicate asset spend by roughly 62% and cut unused assets by approximately 40%.
  • Faster deployment cycles. Organizations using AEM Assets report 55% faster campaign launches, 66% faster creation of new digital assets, and 73% shorter time to spin up new digital experiences from existing content. That speed comes from proper architecture, not heroics.
  • Infrastructure and hosting cost optimization. AEM as a Cloud Service delivers around 38% lower total cost of ownership compared to legacy on premise deployments, driven by fewer FTE hours spent on upgrades, infrastructure management, and security overhead.
  • Risk mitigation. Reducing compliance failures (accessibility, regulatory, privacy), eliminating unapproved content distribution, preventing site downtime, and avoiding overrun upgrades. IDC studies show AEM implementations reduced risk of distributing out of date or unapproved assets by roughly 52%.

The aggregate numbers are striking: IDC reports a three year ROI of approximately 366% for AEM Sites and roughly 348% for Assets, tied directly to engagement improvements and content delivery effectiveness.

Preparing to Search

Audit Your Technical Constraints Before Writing a Single Job Spec

Before you source a single candidate, you need clarity on three dimensions. Skip this step and you will end up hiring for a role that does not match your actual needs.

Architecture and Debt Audit

Map your current AEM architecture: classic versus cloud, current version, custom versus out of the box AEM components, front end integration approach. Identify the biggest pain points: tight coupling, monolithic components, slow builds, poor DAM performance, inefficient metadata and tagging.

Then answer the critical question: what problem must this hire solve first? Is it a cloud migration? Stabilizing performance? Introducing CI/CD? Modernizing content delivery? Reducing build downtime? The answer shapes everything from the candidate profile to the project scope.

Team Dynamics and Autonomy Level

Decide whether you need a dedicated AEM pod (a small cross functional team under this hire's leadership) or whether you are embedding a specialist into existing engineering and DevOps teams. Senior roles vary dramatically: full architectural authority versus advisory influence, mixed spans of control versus individual contributor.

Clear decision rights improve speed and accountability. A senior title without real decision making authority leads to frustration and turnover.

Deployment Model Dynamics

In house FTE offers greater control but comes with longer hiring lead times, overhead of retention, benefits, and management cost. Adobe AEM salaries range from $178,200 to $289,000 annually. In New York, AEM salaries range from $199,600 to $289,000. In Illinois, AEM salaries range from $187,400 to $271,400.

Vetted dedicated remote talent through a partner like SoftDoes offers faster scaling, access to a wider pool of battle tested professionals, and flexible schedule arrangements, with the ability to scale up or down without HR complications. The tradeoff is that you need strong governance and delivery oversight, which is exactly what an engineering led partner provides versus unmanaged freelancers. Freelance AEM experts charge between $50 to $150 per hour, while senior AEM consultants earn $65 to $80 per hour. AEM projects can take between 10 to 60 days to complete depending on complexity.

Engineering the Ideal Profile, Not a Generic Job Description

A useful candidate profile has four components. Generic job specs attract generic candidates.

  • Core outcome and mission. Define exactly what business result you expect: reducing time to publish content by a specific percentage, migrating to cloud with zero downtime, improving user engagement, enabling personalized digital experiences. The senior AEM hire should own that outcome, not just execute tasks.
  • Technical stack reality. Know your AEM landscape: version, modules used (Sites, Assets, Forms), degree of headless or SPA usage, integration with other Adobe solutions and third party systems. Set expectations around front end (HTL, React, Vue), back end (Sling, OSGi), deployment (cloud versus on premise), and infrastructure (CDN, edge, security). Focus on technical mastery in Java and modern front end technologies.
  • Decision making authority. Determine if the candidate will have authority over architecture decisions, module and vendor selection, team hiring, performance SLAs, and budget for tools or cloud services. Spell this out before interviews begin.
  • Growth trajectory. What is the evolution? The role may scale into Head of Digital Experience, Technical Director, or span multiple brands and geographies. Strong candidates evaluate the future path as carefully as the immediate job.

Also include required soft traits: high accountability, strong written and oral communication (this person works with marketing, content, and legal teams daily), the ability to surface risk early, and transparency in tradeoffs.

To Contact Page

Let’s Turn Your Idea into Scalable Software

Book a call with the representative to get answers to all the questions you may have.

Contact us

Vetting and Onboarding

A Vetting Framework Built from Real Hiring Failures

Sourcing Reality

Traditional recruiters consistently struggle to find truly senior AEM cloud experienced professionals. The Adobe Experience Manager platform sits at the intersection of enterprise content management, web development, software development, and cloud infrastructure, which means generalist recruiters lack the technical knowledge to evaluate candidates properly.

Use specialist engineering talent networks and prescreened AEM communities. The strongest senior talent typically comes from enterprises or large consultancies that have completed recent cloud migrations. A freelance Adobe Experience Manager developer can fill short term gaps, but rarely brings the full spectrum of architecture, cloud operations, performance optimization, and cross functional delivery skills that enterprise projects demand. AEM experts are skilled in site development and content management, but you need to verify that expertise spans the complete lifecycle.

Technical Evaluation Pipeline

Ditch the trivia quizzes. Here is what actually works:

  • Live problem solving. Give candidates a real architecture challenge: take a legacy AEM on premise deployment and map the migration to AEM as a Cloud Service, with explicit tradeoffs around cost, timeline, and risk. This reveals how they think, not what they memorized.
  • Real world scenario architecture review. If possible, ask the candidate to review your current setup and propose improvements. Where are the bottlenecks in scaling? What is the caching strategy missing? How would they restructure the DAM taxonomy for performance?
  • Communication under pressure. Simulate a situation where an urgent bug or compliance issue arises during a deployment. Evaluate how they articulate tradeoffs, accept or decline risks, and mobilize teams. Project management skills matter here: overseeing content workflows in AEM requires calm, structured leadership.
  • Cross functional culture fit. Senior AEM professionals must work with content authors, product teams, project managers, marketing, and legal. Evaluate their comfort navigating non engineering discussions, constraints, and competing priorities.

AEM developers should be familiar with content workflow management, and you should probe for experience with multi site management, which is key for AEM architects operating across brands or geographies.

The First 90 Days: From New Hire to Measurable Impact

A structured ramp up protocol separates fast ROI from slow burn. Here is the milestone roadmap:

Days 0 to 30: Audit and Visibility The new hire audits existing architecture, content models, templates, and technical debt. They shadow content operations, align on top priorities with stakeholders, and tackle low hanging technical issues. This is where they build credibility and situational awareness.

Days 30 to 60: Initiative Execution Begin standardizing AEM components, improving or establishing CI/CD pipelines, automating metadata workflows, and fixing performance bottlenecks. If a cloud migration is underway, this is where modules begin moving. Establish reporting and metrics frameworks so progress is visible to leadership.

Days 60 to 90: Delivering Measurable Results The hire delivers first impact metrics: speed improvements, reduced failures or downtime, stabilized content authoring workflows. They hand off authorable templates and components, and you measure the ROI of early wins against the cost of the engagement. This is the checkpoint where you confirm the hire is delivering or trigger a course correction.

Making the Call

Interview Signals That Predict Success or Expensive Failure

Red Flags:

  • Tool obsession. The candidate fixates on having a specific library or module (Adobe Photoshop, Adobe Illustrator, Adobe XD, or a niche framework) rather than solving the core business problem. Tools serve solutions, not the other way around.
  • Cannot discuss past failures. Any senior AEM professional who has led migrations or managed production incidents has stories about what went wrong. If they cannot be candid about failures and lessons learned, they lack the self awareness you need.
  • Lack of ownership. They want to hand off responsibility, stay in a reactive posture, or defer every decision upward. This is a signal they will create more management overhead, not less.
  • No clear view on tradeoffs. If they cannot articulate when to use custom versus out of the box components, when to decouple the front end, or how to balance performance against flexibility, they are not operating at the level you need.

Green Flags:

  • Pragmatic tradeoff analysis. They explain choices made in prior work with nuance: why they chose a headless approach for mobile apps, why they kept a monolithic authoring layer for a specific client, how they managed the transition.
  • Data and system integrity focus. They demonstrate strong process around metadata management, asset governance, content consistency, and compliance. They maintain and improve the content management system rather than patching around it.
  • Proactive risk identification. They spot compliance, performance, or security issues before those issues reach users. They explain how they surface risk early and create visibility for leadership.
  • Strong cross domain communication. They translate technical issues into business language for stakeholders across marketing, compliance, product, and the C suite. This ability is what separates a strategic hire from a capable but siloed web developer.

The SoftDoes Strategic Advantage

SoftDoes exists to eliminate the hiring gamble for enterprise systems like Adobe Experience Manager AEM. As a North America focused custom software engineering, data, and AI partner serving clients across the US and Canada, SoftDoes delivers what traditional recruitment cannot:

  • Battle tested senior talent. Not junior developers learning on your budget. Every AEM expert in our network has delivered cloud migrations, performance optimization, and cross functional solutions at enterprise scale. AEM experts help implement and optimize Adobe Experience Manager across the complete stack.
  • Engineering led delivery oversight. Your AEM hire operates under structured technical supervision, not as an unmanaged freelancer. Code quality, architectural integrity, and documentation standards are maintained from day one.
  • Rapid deployment capability. Skip the months long recruitment cycle. SoftDoes matches prescreened AEM professionals to your specific architecture, project scope, and team dynamics within days.
  • Flexible scaling. Scale your team up or down based on project phases without the friction of severance, benefits renegotiation, or HR overhead. Whether you need a dedicated hire, a cross functional pod, or a contract engagement, the model adapts.
  • Zero risk replacement guarantee. If an AEM expert does not meet your technical standards, SoftDoes replaces them at no additional cost. This eliminates the most expensive risk in technical hiring.

Your Next Move

Every week without the right Adobe Experience Manager talent is a week your digital experience platform accumulates debt, your content teams work around broken workflows, and your competitors ship faster. The cost of inaction compounds.

Book a technical discovery session with SoftDoes architects. In one call, we will assess your current AEM landscape, define the exact profile you need, and match you with senior talent who can deliver measurable impact within 30 days. No obligation, no HR overhead, no gamble.

Flag icon

U.S.-Based

Discuss Your Project

This is a no-pressure, 30-minute conversation. We will talk through what you are building, identify risks or unknowns, and outline what it would take to do it right.

Certificates

Let's build together.

Talk with a senior engineer about your product idea, architecture, and what it would take to build it.

Upload File