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Hire remote DevSecOps Engineer

Discover developers that match your project requirements.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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What our DevSecOps Engineers 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 DevSecOps Engineer

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 DevSecOps Engineer through SoftDoes?

Most engagements move from initial technical discovery to candidate presentation within 14 to 21 days. For urgent situations requiring rapid incident response capability or critical compliance deadlines, top talent can be secured within 48 hours. The speed comes from maintaining a prescreened network of senior DevSecOps engineers who have already passed rigorous live problem solving and system design evaluations, eliminating the months long cycles that plague traditional recruitment. Your hiring managers receive a shortlist of vetted candidates, not a flood of unqualified resumes.

What does it cost to hire a DevSecOps Engineer?

DevSecOps engineers in the US earn between $115k and $155k at mid level. Junior DevSecOps engineers in the US earn $80k to $105k, while senior DevSecOps engineers in the US earn $165k to $225k. The target salary range for DevSecOps engineers is typically $120k to $150k. In international markets, mid level DevSecOps salaries in the UK range from £80k to £110k, and senior DevSecOps engineers in Germany earn €130k to €180k. Through SoftDoes, clients can save 40 to 65% compared to traditional hiring by accessing vetted remote talent without the overhead of full time benefits, office space, and extended recruitment cycles, while still getting engineering led oversight and accountability.

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

SoftDoes offers flexible engagement models tailored to your project scope and timeline. Dedicated Teams provide full time, long term partnerships where engineers operate as extensions of your own technical teams. Contract to Hire allows for a flexible trial period so you can evaluate fit before making a permanent commitment. The Time and Material model bills based on actual hours used, ideal for variable scope projects or consulting engagements. Each model includes engineering led oversight, so you never end up with an unmanaged contractor operating without accountability. Whether you need a single DevSecOps expert for a compliance sprint or a full pod for a platform security transformation, the structure adapts to your operations.

How do you ensure time zone alignment with a DevSecOps Engineer?

SoftDoes is a North America focused partner serving clients across the US and Canada, and time zone alignment is built into every engagement. Engineers are matched not only on technical skills and industry expertise but also on working hour overlap with your core team. For DevSecOps roles especially, where rapid incident response and real time collaboration with development and operations teams are critical, meaningful overlap is nonnegotiable. Engineers can work on their own schedule within defined overlap windows, ensuring both asynchronous productivity and synchronous collaboration when it matters. Productivity penalties from misaligned time zones are a well documented risk, and we structure every engagement to eliminate that friction.

How does SoftDoes technically vet a DevSecOps Engineer?

Every candidate goes through a multi stage technical evaluation pipeline designed to predict real world performance, not certify textbook knowledge. This includes live problem solving exercises where candidates review actual CI/CD pipelines and infrastructure as code configurations to identify vulnerabilities and propose remediation. System design interviews test architectural thinking at scale. Communication evaluation assesses how the candidate explains technical risk to cross functional stakeholders under pressure. We also evaluate cross functional culture fit, probing how candidates have navigated trade offs between product velocity and security in previous roles. Only the top 3 to 5% of candidates clear this process. Industry certifications like CISSP or AWS Certified DevOps Engineer are valued but never treated as substitutes for demonstrated problem solving and hands on experience with real world cybersecurity threats.

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

SoftDoes provides a zero risk replacement guarantee. If the engineer does not meet expectations for any reason, we replace them at no additional cost and with no extended exit timeline. Scaling is equally straightforward: whether you need to add engineers for a security transformation initiative or scale down after a compliance milestone, the engagement model flexes without penalty. This eliminates the sunk cost and contractual friction that makes traditional FTE hiring so risky, especially for projects with evolving scope. You maintain full executive control over team composition and engagement duration.

The Executive Guide to Hiring a DevSecOps Engineer

A single bad DevSecOps hire can silently hemorrhage six figures in delayed releases, unpatched vulnerabilities, and failed compliance audits before anyone notices the damage. On the flip side, the right placement transforms your security posture from a bottleneck into a competitive advantage within weeks. This playbook is a field tested strategy to define, vet, and onboard top tier DevSecOps engineer talent, built from real lessons deploying senior engineers into high stakes enterprise environments.

What's Actually at Stake When You Get This Wrong

What Separates a Senior DevSecOps Engineer from an Order Taker

Most hiring managers treat DevSecOps engineer jobs as a checklist of tools. That misses the point entirely. A true senior engineer is a bridge between risk and delivery, someone who owns choices, trade-offs, and outcomes across the full software development lifecycle. DevSecOps integrates security into every software development phase, making security a shared responsibility from inception to operation.

Here is what actually defines the scope of a senior DevSecOps developer in daily operations:

  • Security as code ownership: They write guardrails directly into infrastructure as code modules, enforce policy as code (Open Policy Agent, Sentinel), and embed automated security gates (SAST, DAST, SCA) into CI/CD pipelines rather than relying on manual reviews that introduce manual errors and bottleneck releases.
  • Runtime security management: From secrets management and least privilege access control to container baselines, patching cadences, and runtime anomaly detection, they manage the live threat surface of your cloud environments, not just the build phase.
  • Pipeline integrity and supply chain security: They own CI/CD pipeline security integration by embedding automated security gates into orchestration tools like GitHub Actions, GitLab CI, and Argo CD, including pull request scanning, image scanning, artifact signing, and SBOM generation.
  • Incident ownership and root cause analysis: When vulnerabilities or breaches surface, they trace systemic failures, lead rapid incident response, define corrective actions, and build feedback loops that prevent recurrence. Secure software delivery practices include vulnerability management and incident response at this level.
  • Observability and compliance instrumentation: They build dashboards tracking mean time to patch, mean time to detect, and control gate performance, giving executive leadership real time visibility into security posture rather than quarterly slide decks.
  • Developer empathy and enablement: The best DevSecOps engineers build golden paths and enable security champions across technical teams, making security practices usable and friction minimal instead of creating adversarial gatekeeping. Communication skills are essential for DevSecOps professionals to work across teams, and collaboration and empathy are important traits for bridging security and development teams.

DevSecOps requires blending software development, infrastructure automation, and security expertise. If your candidate cannot demonstrate ownership across these dimensions, you are looking at an order taker, not a senior engineer.

The Financial and Operational Impact Your Board Needs to See

The business case for hiring DevSecOps engineers is concrete and quantifiable. Here are the ROI vectors that matter to a C level audience:

  • Vulnerability remediation cost compression: Fixing vulnerabilities after release costs roughly 10x more time than if found during development or testing. With developer fully burdened cost averaging around $500 per day, one vulnerability fixed late in production can consume over $10,000 versus roughly $1,000 when caught early through the shift left security approach. Across 100 vulnerabilities per year, organizations without embedded DevSecOps practices can spend nearly $960,000 more than those with strong practices in place.
  • Deployment velocity and operational stability: DORA metrics (deployment frequency, lead time for changes, change failure rate, MTTR) improve materially with DevSecOps practices. Higher deployment frequency combined with lower MTTR translates directly to reduced cost of outages and faster time to market for your software.
  • Compliance and regulatory cost avoidance: In regulated industries (finance, healthcare, government), delays in audits, noncompliance fines, or lost contracts can dwarf engineering cost. A DevSecOps engineer ensures audit evidence is ready, controls are documented, and compliance posture is continuous rather than scrambled before each review cycle.
  • Infrastructure cost governance and tech debt reduction: Through automation of infrastructure provisioning, standardization of cloud platforms, rightsizing, removal of unused resources, and cost tagging, a strong DevSecOps developer directly reduces cloud spend. Reducing operational toil also frees your senior engineer talent for high value projects rather than maintenance firefighting.

Preparing to Search: Strategy Before Sourcing

Audit Your Technical Constraints Before You Write a Single Job Spec

Before you hire DevSecOps talent, you need internal clarity. Skipping this step is how organizations end up with a brilliant engineer solving the wrong problem.

Architecture and Technical Debt Audit

What problem must this hire solve first? Determine your biggest vulnerabilities right now. Are you missing supply chain security (dependencies, SBOMs)? Are your containers unpatched? Is secrets management nonexistent? Is your infrastructure as code brittle and undocumented? Expertise in securing Docker containers and Kubernetes deployment clusters is essential, and understanding the OWASP Top 10 and common vulnerabilities is necessary for application security. Hire for the pain that is most relevant to your current threat surface, not for a generic DevSecOps job description.

Team Dynamics and Autonomy Level

Are you embedding the DevSecOps engineer into a centralized platform team, or having them work inside product pods? Define the scope of authority clearly: do they own the security standard across all teams, or are they advising without enforcement power? Ambiguity here creates paralysis and frustration for even the best candidate.

Deployment Model Dynamics

On premises versus cloud versus hybrid; greenfield versus legacy migration. Talent skilled in cloud security, IaC, and containerization differs significantly from someone securing legacy monoliths. Also consider remote versus local versus mixed teams, time zone overlap requirements, and compliance constraints around data residency. The flexibility of vetted dedicated remote talent often outperforms the friction of in house FTE hiring cycles, especially when you need to contribute impact quickly.

Engineering the Ideal Candidate Profile, Not a Generic Job Spec

Stop writing job descriptions that read like a keyword dump of technologies. Instead, define four essential profile components:

  1. Core outcome and mission: What measurable result must this hire deliver? For example: "Reduce mean time to patch high severity vulnerabilities to under 48 hours" or "Secure the software supply chain to pass SOC2 and HIPAA audits" or "Achieve zero critical infrastructure misconfigurations in production." DevSecOps engineers conduct vulnerability scanning and automated security testing as core responsibilities, and they are responsible for monitoring and programming to secure digital data.
  2. Technical stack reality: Specify cloud platforms (AWS, Azure, Google Cloud), containerization (Kubernetes, Docker), IaC tools (Terraform, Pulumi, CloudFormation), pipeline tooling (GitHub Actions, Jenkins, GitLab, Argo CD), security scanning toolchain expertise (SAST, DAST, SCA, SBOM tools), observability (OpenTelemetry, Prometheus), IAM, and secrets management. DevSecOps roles require proficiency in programming languages like Python and Java, and proficiency in scripting languages like Python and Go aids in automating security tasks. Infrastructure as Code requires a strong grasp of cloud and hardening through tools like Terraform. Organizations should focus on candidate competencies rather than just tool familiarity.
  3. Decision making authority: Can this hire enforce policies, gate pipelines, reject code or infrastructure changes, lead security incident response, and choose tools? Clear ownership prevents paralysis. DevSecOps engineers collaborate with DevOps teams to address security vulnerabilities, and that collaboration requires defined authority.
  4. Growth trajectory: Map the path to senior leadership (Platform, Security, Compliance), stretch work (tool migration, enabling others, risk modeling, architecture reviews), and ability to scale the team through security champions programs. A background in software development or system administration is beneficial for DevSecOps roles and supports this kind of growth.
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Vetting and Onboarding: Where Most Hiring Processes Fall Apart

A Vetting Framework That Actually Predicts Performance

Sourcing Reality

A rigorous vetting process that presents only the top 3 to 5% of candidates makes all the difference. Pure freelancer marketplaces consistently underdeliver for senior, high ownership DevSecOps roles. A balanced sourcing strategy combines expert recruiters, prescreened engineering talent networks, and referrals from engineers who have worked in mission critical systems and high compliance environments. SoftDoes maintains a curated talent network of battle tested engineers specifically for this reason.

Haystack provides a five step hiring playbook for DevSecOps engineers, and the principle is sound: structured, multi stage evaluation beats gut feel every time.

Technical Evaluation Pipeline

Forget trivia questions about port numbers or certification acronyms. Industry certifications like CISSP or AWS Certified DevOps Engineer are valued in DevSecOps, but they tell you about knowledge, not capability. Here is what actually predicts on the job performance:

  • Live problem solving over trivia: Present a real CI/CD pipeline (with Terraform, Dockerfiles, GitHub Actions configurations) and ask the candidate to identify vulnerabilities and propose remediation. Practical problem solving and scenario based assessments are effective for evaluating DevSecOps candidates.
  • System design interviews: For instance, "Design a supply chain security strategy for a containerized monorepo" or "Architect a SAST/DAST/SCA program for a 300 engineer SaaS company." This reveals whether the candidate can operate at the scope you need. CI/CD pipeline security integration involves embedding automated security gates into orchestration tools, and you want to see this thinking in real time. Candidates should demonstrate a proactive security mindset embedded in development processes.
  • Communication under pressure: Evaluate how the candidate describes on call incidents, explains trade offs, and decides when to say "no" to product speed for safety. Clear communication is key to explaining technical risk metrics to cross functional stakeholders. DevSecOps reduces the gap between development and security teams, and the right candidate demonstrates this ability naturally.
  • Cross functional culture fit: Has this candidate pushed back on product leadership for security? Have they failed and learned? Do they mentor other software developers? DevSecOps employs automated security testing in CI/CD pipelines, but the culture around how those gates are communicated and enforced matters just as much.

The First 90 Days: A Ramp Up Protocol That Delivers Immediate ROI

A fast, frictionless ramp separates high impact hires from expensive warmup periods.

  • Days 1 through 30 (Ramp and Quick Wins): Audit existing pipelines, IT infrastructure, and threat surface. Deliver quick wins such as automating image scanning or secrets rotation in a single step for one critical service. Align with security and product leaders to define SLA goals for mean time to detect and mean time to patch. Vulnerability scanning is a key component of DevSecOps practices, and early wins here build credibility fast. Threat modeling and risk assessment skills help anticipate design flaws early in reviews.
  • Days 31 through 60 (Broader Impact): Roll out standardized IaC modules, integrate pipeline security gates across multiple teams, and remedy known vulnerabilities in high risk areas. Build security posture dashboards for executive visibility. This is where continuous integration practices and automation start compounding.
  • Days 61 through 90 (Full Ownership): Lead the first post incident root cause analysis. Present security metrics to leadership. Begin enabling a security champions program across development teams. Document policies, prepare the roadmap for continuous improvement, and ensure some decisions are irreversibly positive for your compliance and risk profile. Top talent can be secured within 48 hours, and a structured ramp protocol means that speed translates to early value rather than confusion.

Making the Call: Signals That Predict Success or Disaster

How to Read Interview Signals: Red Flags vs. Green Flags

After vetting hundreds of DevSecOps experts for enterprise clients, these patterns are reliable:

Red Flags:

  • Seniority defined by years, not scope: The candidate cites average experience in years but cannot describe decisions they made, risk trade offs they managed, or legacy systems they untangled.
  • Tool obsession without problem solving depth: They name every tool in the ecosystem but cannot explain trade offs, failure modes, or assumptions behind their choices. This signals a resume optimized for devsecops engineer jobs rather than real hands on experience.
  • All greenfield, zero legacy: Has never dealt with technical debt, confusing infrastructure, or partial ownership. Real world DevSecOps work involves inheriting messy systems and making them secure.
  • Inability to discuss past failures or trade offs under pressure: "I haven't encountered issues" or "I always succeeded" signals lack of depth. Every experienced engineer has scar tissue.

Green Flags:

  • Pragmatic trade off analysis: Can articulate speed versus security versus cost, compliance versus innovation, and choose accordingly with data. This is what separates DevSecOps engineers who contribute at the strategic level.
  • Focus on data, system integrity, and measurable outcomes: Can show metrics such as lead time, MTTR, recurrence rate, and cost avoidance from previous projects.
  • Proactive risk identification: Does not wait for tools to report issues. They think about threat models, attack surfaces, and guardrails before code ships. The shift left security approach ensures vulnerabilities are addressed early in the development lifecycle.
  • Excellent communication skills: Can translate cybersecurity threats and security risk into business cost. Can work with product and engineering leadership, not just security teams. This is the trait most often underweighted by hiring managers.

Why SoftDoes Is the Strategic Advantage for DevSecOps Hiring

When you hire DevSecOps developers through SoftDoes, you are not posting a job and hoping. You get a partner that has operated inside the engineering trenches.

  • Battle tested senior talent: Every DevSecOps developer in our network has been vetted through live problem solving, system design review, and communication evaluation, not keyword matching.
  • Engineering led delivery oversight: Unlike unmanaged freelancers or generic staffing firms, SoftDoes provides DevOps and cloud infrastructure oversight with architectural guidance and accountability built in. This is the difference between a contractor and a strategic deployment.
  • Rapid deployment capability: A typical hiring process takes 14 to 21 days. Clients can save 40 to 65% compared to traditional hiring while getting engineers who understand devops culture, cloud security, and compliance from day one.
  • Zero risk replacement guarantee: If the engineer does not meet expectations, we replace them at no additional cost. No long exit negotiations, no sunk cost. Dedicated Teams provide full time, long term partnerships, while Contract to Hire allows for a flexible trial period.
  • Flexible engagement models: Scale up or down based on project scope. Whether you need a single senior engineer or a dedicated pod, the model flexes with your operations.

Your Next Move

Every week without embedded DevSecOps capability is a week your pipelines ship code with unscanned vulnerabilities, your compliance posture drifts, and your infrastructure accumulates risk. The cost of inaction compounds.

Book a technical discovery session with SoftDoes architects. We will evaluate your current security posture, map the ideal DevSecOps profile for your stack and threat surface, and present vetted candidates who can deliver measurable impact within 30 days. No generic resumes. No unmanaged contractors. Just senior security engineering talent deployed with strategic oversight.

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