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Hire remote Growth Marketer

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.
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Andrii V.Verified in SoftDoes
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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.
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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
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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
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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.
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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.
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Eugene M.Verified in SoftDoes
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ES 🇪🇸English (C2)Senior
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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
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AWSGoogle CloudKubernetesTerraform

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

Hripsime S.
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Verified in SoftDoesHripsime S.
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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.
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Hripsime S.Verified in SoftDoes
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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.
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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 Growth Marketers in the SoftDoes NetworkRegister to view more

What our Growth Marketers 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 Growth Marketer

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 a Growth Marketer through SoftDoes?

Most engagements move from profile definition to placement within three to four weeks, assuming technical constraints and growth objectives are clearly defined upfront. One documented case of a strategic Growth Director role was filled in four weeks through a structured vetting process. Traditional hiring for specialist growth roles can stretch to 48 days or longer; SoftDoes compresses that timeline by maintaining a prescreened talent pool and running technical evaluations in parallel with cultural fit assessments.

What does it cost to hire a Growth Marketer?

The cost of a growth marketer depends on seniority, budget responsibility, geography, and engagement model. Senior growth marketers in US tech markets command base salaries in the range of $120K to $150K or higher, with total compensation (including performance incentives) reaching well above that for candidates with global experience and AI/LLM skills. Freelancers and consultants operate under different pricing models, often billing hourly or on project retainers. SoftDoes structures engagements to align cost with business outcomes, so your investment scales with the value delivered rather than a fixed overhead commitment.

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

SoftDoes offers multiple engagement structures: fractional growth roles for companies validating channels before committing full time headcount, embedded specialists who integrate with your existing team, full FTE placements, and hybrid pods that pair a growth marketer with supporting analytics, content, or development resources. Each model carries tradeoffs in speed, cost, and alignment. The right structure depends on your growth stage, internal capabilities, and whether you need hands on execution or strategic leadership.

How do you ensure time zone alignment with a Growth Marketer?

SoftDoes draws from a North American talent pool, which provides natural overlap with US and Canadian business hours. For distributed teams, the expectation is set during the engagement design phase: core overlapping hours are defined, communication cadence is agreed upon, and candidates with prior experience in remote or global teams are prioritized. A growth marketer who has operated across time zones before is a stronger fit than one who has only worked colocated, regardless of technical skills.

How does SoftDoes technically vet a Growth Marketer?

Vetting follows a structured rubric: candidates must present past metrics with specificity (not vague claims), complete live work challenges based on real operational scenarios, demonstrate channel depth and stack familiarity through an architecture review, and show evidence of cross functional collaboration and ownership of business outcomes. Candidates who cannot substantiate claims under direct questioning are filtered out early. The process is designed to surface the growth experts who deliver results, not the ones who interview well and underperform on the job.

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

SoftDoes provides a zero risk replacement guarantee. If the hire does not meet performance expectations, a replacement is deployed without additional cost or extended downtime. Contract provisions allow you to scale your team up or down as business conditions change, with performance metrics tied to outcomes rather than hours logged. The goal is to remove the executive risk from the hiring decision entirely, so you can focus on growth rather than worrying about whether your latest hire will work out.

The Executive Guide to Hiring a Growth Marketer

A single bad growth marketing hire burns through six figures in wasted campaigns, stalled pipelines, and lost engineering cycles before anyone pulls the plug. The right one unlocks compounding revenue, lower acquisition costs, and a growth engine that scales with your product. This playbook gives you a field tested strategy to define, vet, and onboard top tier growth marketer talent, written from the perspective of someone who has made these calls and lived with the consequences.

What a Growth Marketing Hire Actually Costs You (and What It Should Return)

Separating Senior Growth Talent from Expensive Order Takers

Most candidates who apply for growth roles can run marketing campaigns on a handful of platforms. That is table stakes, not senior capability. The distinction between quality growth marketers and glorified channel operators shows up in daily operational realities:

  • Constraint identification and removal. A senior growth marketer owns the answer to "what is the single biggest bottleneck limiting sustainable growth?" and works across product, sales, pricing, and analytics to eliminate it. Order takers wait for someone else to define the problem.
  • Full funnel ownership. Growth marketers use frameworks like AARRR (acquisition, activation, retention, revenue, referral) to develop strategy across every stage, not just the top of funnel. They improve conversion rates across the entire customer lifecycle instead of optimizing one landing page in isolation.
  • Data driven experimentation as a discipline. Growth marketers should live by the scientific method in their experimentation framework. They conduct A/B tests and cohort analyses to validate assumptions, using tools like Optimizely, SQL, and Google Analytics to tie every experiment to core business metrics. They look past vanity metrics; every test connects to revenue or retention.
  • Technical depth paired with strategic breadth. Strong growth marketers are usually broad operators with depth in one or two areas. They need broad knowledge across the entire marketing spectrum (SEO, email marketing, paid advertising, social media, content) paired with deep expertise in specific channels. Proficiency in tools like HubSpot and Amplitude is expected, not aspirational.
  • Cross functional collaboration under real constraints. Growth marketers must collaborate across teams for effective execution. They adjust experiments when engineering capacity shifts, legal flags a compliance issue, or product changes the roadmap. They do not operate in a silo and complain when reality intervenes.
  • Tradeoff management with business context. Balancing customer acquisition cost against unit economics, choosing speed over technical debt (or vice versa), and deciding whether to scale a channel before retention metrics stabilize are decisions that separate senior growth talent from someone who simply optimizes campaigns.

Growth marketers must deeply understand user psychology and motivations to craft effective messaging. They should be skilled in creative copywriting, not because they write every ad, but because they understand what drives conversion at each stage. Recruitment of top growth marketers requires a specialized approach that blends analysis and creativity; the role itself demands the same blend.

Revenue and Risk: Quantifying the Business Case

Hiring the wrong person is expensive. Hiring the right one generates returns across four concrete vectors:

  • Channel efficiency and lower acquisition costs. A senior growth marketer identifies underperforming marketing channels and reallocates spend. One documented case: a company discovered a second acquisition channel at $2,200 CAC, then scaled it to generate $850K in new ARR within six months after bringing in the right hire. Demand for growth marketers is expanding precisely because customer acquisition costs keep rising.
  • Faster experiment velocity. When a founder or CTO is running growth on the side, experiment cycles stretch from days to months. A dedicated hire compresses learning loops and eliminates the opportunity cost of executive distraction. One company saved over $120K by using fractional growth execution to validate channels before committing to a full time role.
  • Lifetime value gains through retention and activation. Companies prioritizing customer experience achieve double the revenue growth. A growth marketer who optimizes onboarding, activation, and retention directly increases LTV and reduces churn, compounding returns over time.
  • Risk mitigation on budget and compliance. A mis hire who bets on the wrong channels, ignores attribution integrity, or violates regulatory requirements in a regulated industry (healthcare, finance, edtech) costs more than their salary. In one case, a company screening for LLM/SEO expertise found that most candidates who claimed proficiency could not substantiate their claims under technical questioning, which would have led to expensive, misdirected initiatives.

Groundwork Before You Post the Job

Auditing Technical Constraints Before Searching for Candidates

Defining the ideal hire starts with understanding what your organization actually needs, which requires an honest audit of your internal capabilities, not a wish list.

Measurement Infrastructure and Technical Debt

Ask whether your data is clean, instrumented, and integrated across product analytics, CRM, and marketing attribution platforms. If your measurement stack is broken, a senior growth marketer will spend their first months cleaning data instead of running experiments. Audit your product onboarding flows, feature flagging infrastructure, and performance bottlenecks; these often block the retention and activation metrics a growth hire needs to move. Inventory your channel tech stack (ad platforms, CMS, email automation, SEO tools, analytics platforms) so you can write a job description that reflects reality, not fantasy.

Reporting Lines and Decision Making Authority

Decide where this role sits. Reporting to a CMO produces a different outcome than reporting to a CTO or CRO. Determine autonomy: can they pull budget, influence the product roadmap, choose vendors? Or must they defer to three layers of approval for every experiment? That answer determines whether you need a senior operator or a specialist executor. Evaluate existing supporting roles in analytics, creative, content, and development. A growth marketer who arrives to find zero supporting resources and zero authority is a six figure frustration for everyone.

Deployment Model: FTE, Fractional, or Embedded

Internal full time hires offer deeper alignment and institutional knowledge. External or fractional growth experts offer faster access to specialized skills and flexibility to scale up or down. For companies in the early stages or still establishing product market fit, a fractional engagement often makes more sense than a full time commitment. Startups often hire a single growth marketer due to budget constraints; knowing whether that person needs to be hands on solo or building a team changes the profile entirely. Time zone overlap, communication cadence, and cultural fit matter for remote talent; prior experience in distributed teams is a concrete green flag.

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Building the Right Profile Instead of a Generic Spec

Defining the exact growth profile is crucial because the term "growth marketing" varies by company. A strong job description clarifies growth stage and expected outcomes. Four components to get right:

  1. Core outcome and mission. What business metric does this person own? ARR growth? CAC reduction? Retention rate? Tie it directly to business growth strategy. Growth marketers are essential for companies achieving product market fit; the mission must reflect where you are on that curve.
  2. Technical stack reality. Document the tools and platforms your system already uses, or comparable ones. If you need someone who can work with AI/ML channels, LLM optimization, or advanced lead generation infrastructure, say so. Do not list every tool on the market; list the ones that matter for your specific requirements.
  3. Decision making authority. Spell out what this person can do without asking permission: allocate budget, choose channels, make vendor decisions, affect product changes. Without real authority, a senior hire is a senior title with junior impact.
  4. Growth trajectory and experience level. What team size, budget size, and complexity have they managed? Top growth marketers typically have six or more years of experience. One documented case sought a Growth Director managing a team of 12, a budget near $2M, and a global pipeline; that level of specificity in a job description attracts the right candidates and repels the wrong ones.

Evaluating Candidates and Getting Them Productive

A Vetting Framework That Filters for Real Capability

Where Traditional Sourcing Falls Short

Traditional recruiters and job boards produce high volume and low precision for growth roles. Resumes for growth marketing experts are plagued by exaggeration; candidates claim data driven strategies and impressive results without evidence. Growth marketers should approach hiring through networks rather than just job boards. One company hired a Growth Manager without reading a single resume; they used situational judgment questions and real work challenges, completing the process in six days from LinkedIn post to offer. Prescreened talent networks that require proof of impact outperform generic sourcing for this role category.

Evaluating Technical and Strategic Depth

A simple recruiting process should include defining measurable outcomes and competencies, then building the interview process around them. Assessing hard analytical skills is vital when screening growth marketer candidates.

Live problem solving over trivia. Give candidates a real scenario: sample product data from your onboarding funnel, and ask them to identify friction, propose experiments, and outline tradeoffs. This reveals whether they think in growth loops and systems or just recite playbook tactics.

Architecture and strategy review. Have them critique your growth stack and propose improvements. Do they understand scalability, data pipelines, attribution bias? Do they ask about your data quality before proposing solutions? Great growth marketers diagnose before they prescribe.

Communication under pressure. How do they explain failures? How do they present tradeoffs to a non technical executive? One company rejected candidates who could not substantiate claims about LLM channel expertise under direct questioning. The ability to explain what went wrong, what they learned, and what changed is a stronger signal than a polished success narrative.

Cross functional fit. Ask for specific examples where they adjusted growth initiatives due to regulatory, legal, or engineering constraints. Growth marketers who have only worked in a vacuum struggle in environments where product, engineering, compliance, and sales all have a stake.

Getting a New Growth Marketer to Full Velocity in 90 Days

A structured ramp up protocol converts your investment into positive results faster than "figure it out" onboarding:

  • Days 1 through 30: Map and measure. Full immersion in the current growth funnel: acquisition sources, activation rates, retention curves, revenue per customer, referral mechanics. Identify measurement gaps. Secure access to all analytics, marketing, product, and sales tools. Execute quick wins on underperforming channels to build credibility and momentum.
  • Days 31 through 60: Prioritize and build. Select two to three high leverage experiments based on where they can have the most impact. Define hypotheses with KPI guardrails. Build dashboards with full data transparency. Define resource needs (team, budget, tools). Begin collaborating with product on UX and onboarding improvements. Effective growth marketers run A/B tests to optimize customer acquisition during this phase; the goal is learning velocity, not perfection.
  • Days 61 through 90: Execute and scale. Run experiments at scale and collect results. Review failures and successes with equal rigor. Secure authority over budget or resource allocation. Start building subordinate roles or agency relationships if the data supports scaling. Establish a reporting cadence with leadership (weekly or biweekly) tied to revenue impact, not activity volume.

Dropbox grew from 100,000 to 4 million users in 15 months; that growth was powered by referral programs and systematic experimentation, not a single genius insight. The first 90 days should establish the same kind of experimental infrastructure, adapted to your scale.

Interview Signals and Strategic Partnership

What to Watch for When You Make the Final Call

Red flags that predict failure:

  • Tool obsession without problem solving. Candidates who talk only in platform names (GA4, HubSpot, Meta Ads) without explaining the decisions behind their choices or the tradeoffs they managed. Tools are inputs; outcomes are what matter.
  • No failures on record. If a candidate offers only success stories and cannot describe missteps, what they learned, or what they changed, they are either inexperienced or dishonest. Both are disqualifying.
  • Vague metrics. Cannot define LTV, CAC, churn, retention, or ARPU for prior roles with actual numbers. "We improved retention" is not a data point; it is a hope.
  • Technical depth without business ownership. Strong analytical skills but no evidence of aligning growth with sales, customer success, or company strategy. This person drives growth in a spreadsheet, not in revenue.

Green flags that predict results:

  • Pragmatic tradeoff analysis. "I chose the higher CAC channel because it unlocked higher LTV segment customers" or "I delayed the feature launch to avoid breaking retention for existing cohorts." This is the growth mindset applied to real decisions.
  • Focus on data integrity and system design. Speaks fluently about instrumentation, attribution, measurement bias, and data hygiene. Growth marketers use data driven tactics to optimize customer engagement; the ones who care about data quality are the ones whose results hold up.
  • Proactive risk identification. Flags privacy, regulatory, compliance, or ethical concerns with AI/ML channels before you ask. This person protects your company while scaling it.
  • Ownership of outcomes, not inputs. Delivered revenue growth, reduced churn by a measurable amount, scaled marketing channels, managed budget, hired and led teams. The best fit for a senior role has a proven track record measured in business outcomes, not campaign launches.

Why Executives Partner with SoftDoes for Growth Marketing Hires

Traditional recruitment agencies offer generic matches and slow timelines. Unmanaged freelancers and consultants operate under different pricing models with variable reliability and minimal oversight. Large consulting firms layer cost and process onto an already complex hire.

SoftDoes operates differently. As a North America focused custom software engineering and data/AI partner serving clients across the US and Canada, SoftDoes delivers battle tested senior talent with engineering led delivery oversight. Every growth marketing expert deployed through SoftDoes is technically vetted against real operational challenges, not resume keywords. Rapid deployment capability means you are not waiting months to fill a critical role. The flexibility to scale up or down lets you match investment to results. And a zero risk replacement guarantee removes the executive liability that makes every hire feel like a gamble.

If your company needs to hire integrated marketing strategists or growth marketing experts who can operate at the intersection of product, engineering, and revenue, the starting point is a technical discovery session with SoftDoes architects. Referral programs, organic growth, SEO, paid acquisition, email marketing, social media, landing pages; whatever channels and initiatives your business requires, the conversation starts with your constraints, not a generic pitch.

Book a technical discovery session and stop paying for hiring mistakes.

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