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Hire remote Security 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 Security 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 Security 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 Security Engineer through SoftDoes?

Traditional security engineering searches often stretch across months due to the talent shortage (over 3.5 million cybersecurity roles were unfilled recently). SoftDoes compresses this timeline by maintaining a prescreened [talent network of DevSecOps and security engineers](/talent/hire-devsecops-engineers) with validated technical signal. Once requirements are clearly defined, including stack, seniority, compliance needs, and deployment model, expect warm candidate slates within days. The speed depends on role clarity and stack alignment, but the bottleneck shifts from sourcing to your internal decision making process rather than the pipeline itself.

What does it cost to hire a Security Engineer?

The average salary of a security engineer in the US is $167,000 as of recent data, with variation from roughly $100,000 to $230,000 depending on seniority, region, and specialty. Total cost of employment includes benefits, onboarding, salary during ramp, and opportunity cost of delays. A bad hire can cost 1.5x to 3x salary when you include project delays, rework, and replacement. Hiring a cybersecurity developer through SoftDoes starts at $2,500 per month, with pricing that reflects the engagement model, seniority, and scope of the role.

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

SoftDoes offers fully embedded dedicated hires integrated with your internal team, fractional or contract security engineers for specific initiatives or validation periods, security pods or shared centers of excellence for broader coverage, and project based engagements with fixed scope deliverables. Each model trades off speed, ownership, control, and cost differently. Fractional or contract engagements work well early to validate the need; embedded permanent hires make sense when ownership, continuity, and deep understanding of your systems matter most.

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

SoftDoes focuses on North American talent, which simplifies overlap for US and Canadian clients. For remote hires, we enforce overlapping core working hours, geographical clustering that matches the majority of your engineering operations, and synchronous standups. For organizations in regulated industries or those requiring on call coverage, we establish response SLAs and monitoring protocols that cover after hours windows. The goal is that your security engineer operates as a natural extension of your team, not as an offshore resource with a 12 hour communication lag.

How does SoftDoes technically vet a Security Engineer?

Our vetting process prioritizes hands on experience over memorization. Candidates go through scenario based architecture reviews, secure code review exercises, and threat modeling debriefs that simulate real operational challenges. We assess communication under pressure, cross functional collaboration ability, and proactive risk awareness through behavioral interviews. Reference checks focus specifically on past incidents the candidate led and how they handled failures. Candidates should demonstrate practical security engineering experience across application security, cloud security, and network security before entering our talent pool. A trial or probation period allows you to observe working style and cultural fit before full commitment.

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

SoftDoes guarantees replacements within an agreed period at no additional cost, eliminating the financial risk of a bad hire. If your threat landscape or business goals shift, you can scale up by adding team members or moving to a pod model, or scale down through flexible contract terms. All engagements include documentation standards and knowledge transfer protocols to limit disruption during transitions and avoid vendor lock in. The model is designed so that your security posture never depends on a single point of failure, whether that is a person or a contract structure.

The Executive Guide to Hiring a Security Engineer

A bad security engineering hire costs between $150,000 and $520,000 when you factor in project delays, rework, and replacement. A slow hiring pipeline leaves your infrastructure exposed while over 3.5 million cybersecurity roles sit unfilled. This playbook gives you a field tested strategy to define, vet, and onboard top tier security engineer talent, built from real lessons running engineering delivery across regulated industries.

What Actually Separates a Senior Security Engineer from a Checkbox Operator

The Operational Realities That Define the Role

Hiring a system security developer requires looking beyond traditional software engineering skills. The difference between a senior security engineer who protects your company and one who just runs scans comes down to ownership, system design authority, and the ability to manage tradeoffs under pressure. NIST recommends defining cybersecurity roles around specific tasks, knowledge, and skills rather than generic titles. Here is what that looks like in practice:

  • Security control maturity ownership. A senior cyber security engineer identifies top risks through threat modeling, incident trend data, and asset criticality, then delivers quarterly risk reduction priorities. This is proactive architecture, not reactive patching.
  • Cross stack technical depth. Cloud security, endpoint security, infrastructure hardening, identity and access management, container and Kubernetes security, network segmentation. The right hire operates across all of these, not just one.
  • Active incident response and detection. Weekly threat hunting, alert triage, root cause analysis. Effective incident response capabilities are essential for security developers; proficiency in incident response separates operators from order takers.
  • Security automation craftsmanship. Building SOAR playbooks, infrastructure as code for security enforcement, and tool integrations that eliminate manual toil. Proficiency with automated security tooling is non negotiable for anyone protecting production systems at scale.
  • Cross functional influence. Working directly with product, compliance, legal, and platform teams. Security developers need strong communication skills to explain vulnerabilities to non technical stakeholders, guide software architecture decisions, and drive audit readiness.
  • Designing systems with security baked in. Experience implementing security measures throughout the software development lifecycle, not bolting them on post deployment.

These capabilities define a cyber security developer who designs safe systems, versus someone who follows a checklist.

The Financial and Operational Case for Getting This Hire Right

Cyberattacks are among the costliest threats to businesses today. Security software development is crucial for protecting sensitive data, and the ROI of placing the right engineer is measurable across four vectors:

  • Avoided breach costs. Organizations suffering from severe security staffing shortages pay on average $1.76 million more per breach than those with adequate staff, according to IBM's Cost of a Data Breach Report. Implementing security measures reduces exposure to breaches during development, not just in production.
  • Faster detection and containment. Teams that adopt AI driven automation and continuous monitoring tools lower breach costs by roughly $167,000 and cut detection to containment timelines by nearly 100 days.
  • Compliance and audit readiness. A senior hire who understands compliance frameworks such as GDPR, HIPAA, and PCI DSS avoids regulatory penalties, delayed deal closings, and rescoped contracts. Security developers should be familiar with these frameworks as a baseline, not a stretch goal.
  • Reduced technical debt and rework. A senior security engineer catches design flaws early, preventing patch slips, misconfigurations, and accumulated vulnerability backlogs. This protects deployment velocity and business growth simultaneously.

How to Prepare Before You Start Sourcing Candidates

Audit Your Technical Constraints First

Before writing a job description, map your weakest security gaps. This audit drives whether you need a mission focused hire or a tactical specialist, and what skill sets are non negotiable.

Mapping Your Architecture and Debt Exposure

Start with one question: what problem must this hire solve first?

Analyze your cloud environments. Is your cloud posture fragmented across teams? Are container platforms or serverless functions under monitored? Check IAM sprawl: are service accounts, API keys, and tokens audited and rotated? Many breaches trace back to over permissioned or poorly managed access. Assess your CI/CD pipelines for security gates (SAST, DAST, IaC scanning) and determine whether those gates are automated or manual. Finally, review the backlog of high severity CVEs and patch lag times. A pattern of risk accumulation tells you the hire needs to be senior enough to own remediation strategy, not just execute tickets.

Embedded Specialist or Dedicated Security Pod

The deployment model shapes compensation, reporting, and performance benchmarks. An embedded specialist supports product teams directly: faster feedback loops, less bureaucracy, but risk of silos and overdependence on one person. A dedicated security team or security operations center enables consistency, shared ownership, and standardization, but decision making slows unless reporting and culture are well designed. Your choice here affects whether you are hiring a senior engineer or a staff/principal level leader.

In House FTE Friction Versus Vetted Remote Talent

In house full time hires give you control, alignment, and IP protection, but carry higher fixed costs, benefits overhead, and onboarding timelines measured in months. The demand for security engineers is at an all time high, and remote or distributed models broaden your talent network while reducing cost. Contract or fractional hires through a partner like SoftDoes reduce risk and allow fast starts, though deep system knowledge retention requires deliberate onboarding. Each model trades off speed, ownership, control, and cost differently.

Writing a Profile That Attracts Top System Security Developers

Generic job specs attract generic candidates. To hire cybersecurity developers who actually move the needle, your profile needs four components:

  1. Core outcome and mission. "Reduce severity and frequency of incidents by 40% within 12 months" beats "improve security posture." Hiring managers who define success in measurable terms attract candidates who think the same way.
  2. Technical stack reality. List your cloud providers (AWS, Azure, GCP), infrastructure stack (Kubernetes, Docker, serverless), programming languages in use, threat modeling tools, and detection platforms (SIEM, EDR, SOAR). Security engineers need proficiency in programming languages like Python; be specific about what your stack requires. Knowledge of SIEM platforms is crucial for security engineers operating in fast paced environments.
  3. Decision making authority. Clarify what choices this hire will make about tools, vendor approvals, policy exceptions, and tradeoffs between speed and risk. Candidates with extensive experience in various domains want to know who has final say on security architecture decisions.
  4. Growth trajectory. Show the path to staff, principal, or leadership roles. Senior security talent cares about technical influence and mentorship opportunities. A clear trajectory makes your company a valuable asset to their career, not just another job.
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The Vetting Pipeline and First 90 Day Onboarding Plan

A Vetting Framework Built for Scarce Talent

Where Top Cybersecurity Developers Actually Come From

Over 3.5 million cybersecurity roles were unfilled recently, and the gap keeps widening. Traditional recruiters casting wide nets waste your time. Security specialists with a proven track record are passive candidates; they are not browsing job boards. Effective sourcing means tapping prescreened engineering talent networks where candidates already carry validated technical signal through video interviews, skill assessments, and detailed evaluation summaries. Freelance cybersecurity developers and unmanaged marketplace hires carry higher risk; a curated talent network with engineering led oversight produces faster, more reliable results.

Evaluating Technical Competence and Operational Judgment

Move away from trivia and certification checklists. Security engineers often hold certifications like CISSP or CEH, but employers should place substantial weight on hands on experience over certifications when hiring security developers. Use performance based questions during interviews to assess candidates' problem solving skills. Here is what an effective pipeline looks like:

  • Hands on assessment. Evaluate technical competence through assessments like secure code reviews and threat modeling exercises. Have candidates review a real or sanitized codebase, discover vulnerabilities in a running application, or walk through a security architecture diagram. These simulate daily work and test whether candidates demonstrate practical, hands on security engineering experience.
  • Live scenario problem solving. Present a situation: "You detect abnormal outbound traffic from a production service," or "A misconfigured IAM policy gives over privilege to a third party service account." Assess immediate prioritization, escalation logic, and communication under pressure. Developers should have hands on threat modeling experience to anticipate attack vectors and respond under ambiguity.
  • Behavioral and "will do" evaluation. Probe situational leadership, failure stories, tradeoff thinking, and ethical reasoning. Security developers should possess core programming fluency and knowledge of operating systems and networks, but the will do layer reveals whether they apply that knowledge proactively. Use NIST's Secure Software Development Framework to evaluate understanding of secure software development throughout the lifecycle.
  • Reference checks focused on real incidents. Ask references about incidents the candidate led, unanticipated risks they missed, and how they responded. Resumes cannot fake this.

The First 90 Days: From New Hire to Operational Owner

A senior security engineer should deliver measurable value within 90 days. Without structured milestones, even top cybersecurity developers get bogged in low impact tasks.

Days 1 through 30: Full onboarding to the tech stack. Security audit of the highest critical area (cloud IAC, IAM, network security). Meaningful input on one ongoing project. Shadow the existing incident response and continuous monitoring processes. The goal is orientation plus one early win.

Days 31 through 60: Lead a threat model for a key system. Own remediation of the top three to five CVEs or security gaps. Begin implementing improved security baselines: logging, telemetry, least privilege access management.

Days 61 through 90: Present a six month roadmap for security investment and risk reduction. Begin mentoring peers or defining standards. Deliver a vulnerability assessment of the next highest priority system. By day 90, the hire should own their domain with minimal oversight.

Evaluating Candidates and Choosing the Right Engagement Model

What to Watch for in Final Round Interviews

Red flags that predict failure:

  • Tool obsession without reasoning. The candidate lists ten security solutions but cannot articulate why they chose one over another, or explain tradeoffs in context.
  • No failure stories. Every seasoned security consultant has incidents they learned from. A candidate who claims a clean record either lacks experience or lacks self awareness.
  • Binary thinking about risk. Claims that "perfect security" is achievable rather than discussing managing risk through probabilities, tradeoffs, and prioritization.
  • Inability to work across cross functional teams. Information security does not operate in isolation. If a candidate cannot describe collaborating with product, compliance, or legal, they will create friction, not security solutions.

Green flags that predict impact:

  • Pragmatic tradeoff analysis. Clear discussion of speed versus risk, engineering constraints, and when to defer or escalate.
  • Data driven operational thinking. Referencing metrics like mean time to detect, patch lag, risk scoring, or incident cost during the conversation.
  • Proactive risk identification. Someone who has raised issues before they became incidents and built mechanisms (alerts, auditing, penetration testing, red teaming) to surface risks early.
  • Clear communication under ambiguity. Cyber threats involve uncertainty. The ability to express assumptions, flag unknowns, and escalate cleanly is a crucial role competency.

Why Engineering Teams Choose SoftDoes

SoftDoes operates as a North America focused custom software engineering, data, and AI partner serving clients across the US and Canada. For organizations that need to hire cybersecurity developers without absorbing the full risk of traditional recruitment, the model is built around five operational guarantees:

  • Battle tested senior talent. Every security engineer in our network carries a proven track record in enterprise regulated industries (finance, healthcare, compliance). 92% of placed engineers remain with clients after 12 months.
  • Engineering led delivery oversight. Technical leadership reviews architecture, security posture, and ongoing performance. This is managed DevOps and cloud infrastructure delivery, not unmanaged freelancer coordination.
  • Rapid deployment capability. Qualified system security developer profiles delivered within days once requirements are clear, not the months typical of traditional hiring pipelines.
  • Flexible scaling model. Scale your security team up or down based on threat landscape and business operations needs without sunk cost.
  • Zero risk replacement guarantee. If the hire is not performing or the fit is off, a replacement is provided within the agreed period.

Your Next Step

Security software developers are among the most sought after professionals in information technology. Every week without the right hire is a week your sensitive data, infrastructure, and compliance posture remain exposed. Book a technical discovery session with SoftDoes architects to map your current security gaps, evaluate whether a dedicated hire, a pod, or a partner model delivers the fastest ROI, and get clarity on alignment before pushing "post job description."

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