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Hire remote Enterprise Architect

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.

Andrew V.
Available Now
Verified in SoftDoesAndrew 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.

Andrew V.
Available Now
Andrew 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.

Andrew V.
Available Now
Andrew 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.

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What our Enterprise Architects 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.

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RIGHT expert, FASTER

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How to hire a Enterprise Architect

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 Enterprise Architect through SoftDoes?

It typically takes about 45 days from kickoff to offer stage for remote enterprise architect positions, assuming mandate and decision rights are clearly defined upfront. The process starts with defining deliverables and frameworks clearly, followed by technical screening and stakeholder alignment. Average time to match an enterprise architect candidate is under 24 hours thanks to our prescreened talent network, but the full hiring cycle depends on your internal decision speed and role clarity. If there is ambiguity in executive sponsorship, scope, or target architecture documents, expect delays. SoftDoes accelerates this through access to ready vetted candidates and hands on technical screening assistance that eliminates the guesswork typical of traditional recruitment.

What does it cost to hire an Enterprise Architect?

Base salary for a senior enterprise architect in the US and Canada commonly falls in the range of $185,000 to $235,000, excluding bonus and equity. Principal enterprise architect and lead level roles can reach $230,000 to $290,000 or more in total base compensation depending on scope and industry. Total compensation including bonus, stock, and benefits can push significantly higher, especially in high demand sectors like finance, healthcare, and AI platforms. Contract or pod engagement models may carry a higher hourly rate but substantially lower long term risk, since you avoid the full burden of a misaligned permanent hire and retain flexibility to adjust as your technology strategy evolves.

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

SoftDoes supports full time dedicated enterprise architect placement, fractional or contract engagement, and enterprise architects embedded within pods or cross functional teams. The right model depends on how much control and influence you give the architect, how broad the domain ownership is, and what speed of impact you require. For companies pursuing large scale cloud transformation or digital transformation, a dedicated hire often makes sense. For organizations that need strategic guidance on data architecture, reference architectures, or computer science driven modernization without a permanent headcount commitment, a fractional or pod model delivers the expertise without the overhead.

How do you ensure time zone alignment with an Enterprise Architect?

For US and Canada enterprises, we preferentially match enterprise architects in overlapping time zones across Eastern, Central, Mountain, and Pacific regions. For remote jobs, we ensure that the candidate commits to onsite or in person stakeholder meetings during the critical early engagement period. We establish core collaboration hours that align with your engineering teams and business analysts. SoftDoes leverages remote talent with proven track records of leading cross regional teams and serving clients across multiple time zones without sacrificing responsiveness or delivery quality.

How does SoftDoes technically vet an Enterprise Architect?

Our process is multi layered. It begins with resume and reference validation, confirming candidates have eight to ten years of senior technology experience across relevant domains. Next, candidates complete a live technical assignment based on a real world architecture problem, where they must demonstrate trade off analysis, target state architecture thinking, and problem solving under constraints. We then conduct a communication assessment evaluating storytelling ability, willingness to discuss past failures, and capacity to translate technical decisions into business alignment language. We also validate domain experience in areas like cloud data platforms (Microsoft Azure, AWS, GCP), data warehouse design, vector databases, operating systems, supply chain systems, and compliance frameworks relevant to your industry. Finally, we assess cultural fit with cross functional teams to ensure the architect can collaborate effectively with product, engineering, security, and business stakeholders.

What happens if the Enterprise Architect isn't the right fit, or I need to scale up or down?

SoftDoes offers a zero risk replacement guarantee. If within the initial engagement period you determine the enterprise architect is not delivering to expectations, we replace them at no additional cost. Beyond replacement, we can adjust the engagement model entirely: shift from full time to fractional, add staff to a pod, or scale down scope based on evolving business needs. We track performance metrics throughout the engagement so you can identify misalignment early, before it becomes costly. This flexibility is what separates a strategic talent partnership from a traditional recruitment transaction.

The Executive Guide to Hiring an Enterprise Architect

A failed enterprise architect hire is not just a wasted salary. It is platform decisions made without rigor, technical debt baked into your core services, and compounding risk across every product line. A slow hiring pipeline bleeds opportunity cost while your engineering teams drift without strategic direction. This playbook delivers a field tested strategy to define, vet, and onboard a senior enterprise architect who creates measurable business impact from day one.

What Actually Separates a Strategic Enterprise Architect from an Expensive Order Taker

The Capabilities That Move the Needle

When you hire enterprise architects, you are not buying someone who draws diagrams and presents frameworks. You are buying a leader who owns architecture as a strategic asset and drives outcomes across your entire organization. Here is what a seasoned enterprise architect actually does every day:

  • Owns target state architecture end to end: defines where systems, data, and infrastructure need to go, aligns across business units, and enforces compliance against that vision. They create current state and target state architecture diagrams and document transition plans between them.
  • Manages trade offs under real uncertainty: cost vs. latency vs. scale vs. reliability vs. regulatory requirements. Enterprise architects must balance long term architecture with near term business needs. They do not default to perfect; they articulate risk and reward in language business leaders understand.
  • Drives technical systems thinking at scale: cloud microservices vs. modular monoliths, data architecture (data warehouse, governance, observability), infrastructure (multi region, cloud cost optimization, disaster recovery), and security embedded design. Experience with cloud platforms like AWS, Azure, or GCP is essential.
  • Orchestrates stakeholders, not just follows them: shapes product, operations, legal, compliance, and budget conversations. Stakeholder translation is a critical role of an enterprise architect, turning technical issues into business outcomes that resonate with executives.
  • Owns change management and modernization: guiding cloud transformation, technical debt reduction, retiring legacy systems, and ensuring migration plans have rollback paths. Change management experience is essential for enterprise architects.
  • Establishes architecture governance and standards: setting architecture review boards, enforcing reference architectures, monitoring system health, and tracking metrics on reliability, performance, and security. Enterprise architects establish technology standards and governance policies across the organization.

Candidates should have at least eight to ten years of experience spanning software development, infrastructure, data, and technology strategy. Top skills for enterprise architects include TOGAF and AWS proficiency, with the AWS Certified Solutions Architect Professional being a widely recognized credential. But credentials alone do not separate the right enterprise architect from a resume collector. Strong problem solving skills and the ability to demonstrate influence and executive communication skills matter far more than badges.

The Business Case You Should Be Making Internally

Here are the concrete ROI vectors a strong enterprise architect delivers:

  • Technical debt reduction: organizations without enterprise architecture accumulate technical debt that inflates maintenance costs, bug counts, and support tickets. A capable architect drives measurable reduction in those deficits as a percentage of annual maintenance budget.
  • Faster deployment cycles: clear architecture shortens delivery timelines for new products. With proper platform design, modular architecture, CI/CD, and infrastructure as code, the enterprise architect works to compress cycle time and reduce rollback frequency across engineering teams.
  • Infrastructure optimization and cost avoidance: enterprise architecture reduces duplicate spending on overlapping systems. This includes choosing cost effective cloud solutions, avoiding overprovisioning, consolidating silos, and improving vendor management on contracts.
  • Risk mitigation and compliance: enterprise architecture de risks migrations like cloud adoption. In regulated industries, this means ensuring alignment with HIPAA, PCI, GDPR, and FEAF standards while reducing vulnerabilities, enforcing encryption, and maintaining data integrity.

Effective enterprise architecture aligns IT investments with business outcomes. Enterprise architects define technology roadmaps for business objectives, ensuring that every platform build supports a revenue enablement outcome rather than wasted engineering effort. Bad hire cost for a principal enterprise architect can reach one to two times salary when you account for recruiting costs, onboarding, waiting for deliverables, and cleanup across your application portfolio.

How to Prepare Before You Start Sourcing Candidates

Audit Your Technical Constraints First

Rushing into a search without clarity on the problem you are solving causes scope creep, mismatched expectations, and long cycles without impact. Before you post a single enterprise architect job, complete these three audits.

Architecture and Debt Audit

Conduct a current vs. target state analysis: which systems are legacy, which technology solutions are brittle, which external dependencies create bottlenecks. Review all major integration points, data flows, existing APIs, and outage history. Understand historical architectural missteps. Assess nonfunctional requirements: latency SLAs, uptime targets, scalability needs during peak season, regulatory compliance constraints (data residency, for example), and security maturity. Enterprise architects assess application portfolios for rationalization, so give them real data to work with from the start.

Team Dynamics and Autonomy Level

Define the role inside your org before you hire. Will this enterprise architect lead a dedicated architecture function, or embed inside a business unit? Is the role centralized or distributed? What is the reporting line: CTO, CIO, or VP of Product? Most critically: can the architect make real decisions (choose platforms, approve vendor contracts, enforce guidelines), or is the role purely advisory? If advisory, your best candidates will walk. Top talent wants decision making authority, not a seat at the table with no vote.

Deployment Model Dynamics

Determine whether you need a full time employee, a contract engagement, or a fractional architecture consultant. Many scale ups and enterprises prefer hybrid models: a core FTE complemented by vetted remote enterprise architect talent. For remote jobs, the first hiring quarter often requires strong onsite presence to build executive trust and organizational credibility, so plan for that friction.

Engineering the Ideal Profile, Not a Generic Job Spec

Stop writing job descriptions that read like a TOGAF glossary. Design the profile around four essential components:

  • Core mission and outcome: for example, reduce technical debt by 40% within eighteen months, consolidate the application portfolio, ensure system uptime of 99.9%, or enable M&A integration. Tie the mission to business objectives, not abstract architecture goals.
  • Technical stack reality: what cloud platforms, programming languages, data stack, and infrastructure does the architect need strong knowledge of? What domains will they touch: security, AI/ML, data engineering, cloud migrations, legacy monolith decomposition, supply chain systems, or mobile development?
  • Decision making authority: what parts of business architecture and solution architecture can they enforce vs. recommend? What vendor and contract approvals do they own? Who reports to them? How do they interact with business analysts and project management functions?
  • Growth trajectory: will this person scale a team, own strategic transformation programs, or move toward a Chief Architect role? How does this position evolve over the next eighteen months? Senior enterprise talent wants to see a path, not a dead end.
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A Battle Tested Framework for Vetting and Onboarding

How to Actually Evaluate Enterprise Architect Candidates

Sourcing Reality

Traditional recruiters frequently miss the nuances of this role. They misclassify a solutions architect or domain architect as an enterprise architect, sending you candidates who lack the strategic scope, governance experience, or stakeholder orchestration skills the role demands. Generic job boards attract recently laid off candidates, not the employed, high performing talent you want. A prescreened engineering talent network can bring candidates who already have a proven track record of driving enterprise architecture outcomes, not just polished resumes. This dramatically shortens time to quality. Average time to match an enterprise architect through a vetted network is under 24 hours, with roughly 45 days to complete hiring for remote enterprise architect positions once scope and deliverables are clearly defined.

Technical Evaluation Pipeline

Replace trivia based whiteboard theory questions with evaluations that mirror how an enterprise architect works in the real world:

  • Live scenario architecture review: give the candidate your system (or a sanitized version) and ask for a target architecture proposal. Ask them to address trade offs: latency vs. cost vs. compliance vs. developer velocity. Watch how they ask "what are the constraints?" rather than assuming a perfect environment.
  • Communication under pressure: simulate a stakeholder disagreement. Require them to argue trade offs to product leadership. Candidates should demonstrate influence and executive communication skills, not just technical depth.
  • Cross functional culture fit: evaluate the candidate's ability to collaborate with product, compliance, operations, data, and engineering teams. In regulated environments like banking, healthcare, or government, adaptability and compliance awareness are non negotiable.
  • Portfolio and deliverable review: ask candidates to walk through technology roadmaps they built, cloud migration roadmaps they developed for major platforms, and governance policies they established. Enterprise architects must excel at business capability modeling; this is where you see that skill in action.

The First 90 Days: From New Hire to Measurable Impact

Use a 30/60/90 day ramp up protocol that eliminates the typical architectural stall and ensures the enterprise architect delivers value fast:

  • Days 1 through 30: Deep Discovery. The architect reviews current architecture artifacts, the full application portfolio, infrastructure, data flows, and the technology stack. They meet every stakeholder: engineering, product, security, operations, and business units. They audit metrics, quantify existing technical debt, and review current roadmaps. The goal is credibility through demonstrated understanding of business processes and systems.
  • Days 31 through 60: Align the Target State. The architect drafts an architecture vision, defines architecture governance standards, selects decision rights, defines trade off frameworks, and identifies quick wins. They begin establishing an architecture review board if one does not exist. They present target architectures and the transition plan to leadership for approval, ensuring alignment between technology investments and business needs.
  • Days 61 through 90: Deliver Initial Outcomes. The architect pilots modernization of one specific system, decommissions a legacy application, proves cost savings or performance improvements, and formalizes standards. They embed observability, compliance checks, and documentation workflows into engineering operations. This is where application portfolio rationalization moves from theory to measurable result.

Separating the Right Hire from the Expensive Mistake

Interview Signals: Red Flags vs. Green Flags

After conducting hundreds of enterprise architect evaluations, these are the signals that predict success or failure.

Red Flags:

  • Tool obsession over problem solving: the candidate talks certifications, tools, and frameworks endlessly but cannot walk you through actual choices, trade offs, or cost/risk decisions they made. TOGAF certification is highly valued for enterprise architects, but it is a baseline, not a differentiator.
  • Cannot discuss past failures: every seasoned enterprise architect has at least one major outcome that did not go as planned. If a candidate cannot describe what went wrong and what they learned, they either lack real experience or lack self awareness.
  • Excessive engineering detail when the mission is strategic: layering in CPU scheduler optimizations or micro level code decisions when what you need is roadmaps, standards, and ensuring alignment across business units signals a mismatch in scope.
  • Poor stakeholder awareness: the candidate does not ask about or understand business priorities. They cannot translate technology strategy into business outcomes, P&L impact, or risk reduction for business leaders.

Green Flags:

  • Balanced trade off thinking: cost vs. performance vs. security vs. time. The candidate can articulate when "good enough" is the optimal decision and explain why, using data and operational logic rather than dogma.
  • Proactive risk identification: "I recognized this pattern early and paused future work until we addressed the root cause." This signals an architect who protects the organization, not one who documents problems after the damage is done.
  • Clarity in communication: can explain to a non technical executive why an architecture choice matters in terms of revenue, compliance, or operational cost, without hiding behind jargon. Communication skills at the executive level are what separate a principal enterprise architect from a senior individual contributor.
  • Ownership and execution in past roles: not just architecting on paper, but shepherding change, embedding governance, enforcing standards, and driving costly migrations to completion. Look for a track record of digital transformation delivered, not just planned.

The SoftDoes Strategic Advantage

SoftDoes is a North America focused custom software engineering and data and AI partner serving clients across the US and Canada. When you need to hire a software architect or a dedicated enterprise architect, the difference comes down to three things: talent quality, delivery rigor, and risk mitigation.

  • Battle tested senior talent: not freelance enterprise architect contractors from open marketplaces, but seasoned professionals vetted for strategic thinking, domain breadth (cloud, data architecture, AI, legacy modernization, analytics), and compliance experience across industries. Banking and finance sectors, healthcare organizations requiring HIPAA compliance, telecommunications companies undergoing OSS/BSS transformations, government agencies following FEAF standards, retail and e commerce companies pursuing omnichannel integration, and manufacturing industries consolidating ERP systems all represent markets we serve.
  • Engineering led delivery oversight: you get someone who ensures execution follows the architecture, who escalates issues early, and who partners with your engineering teams on implementation, not an unmanaged freelancer drawing diagrams in isolation.
  • Rapid deployment and flexible scaling: engage a dedicated enterprise architect, embed an architecture pod, or start with a contract model. Scale up or down as your needs evolve. Our zero risk replacement guarantee means that if the enterprise architect is not the right fit, we replace them at no additional cost, eliminating the catastrophic bad hire scenario.

Take the Next Step

Decide whether your company's scale, culture, and technical leadership model truly need an enterprise architect now or in the near term. Use the preparation, vetting, and ramp up methods in this playbook to ensure your hire delivers value fast and compounds returns across your business.

When you are ready, book a technical discovery session with SoftDoes architects. We will map exactly what one hire can save or generate in your specific regulatory, technical, and business context. No obligation, no fluff, just a candid assessment from people who have built and scaled enterprise systems across dozens of organizations.

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