As DevSecOps Engineer, you’ll support secure, mission-critical platforms in a federal environment. This role works as part of a small, agile design and development team, collaborating closely with developers, data scientists, and government stakeholders to deliver reliable, scalable, and secure application and platform capabilities.

We know that you can’t have great technology services without amazing people. At MetroStar, we are obsessed with our people and have led a two-decade legacy of building the best and brightest teams. Because we know our future relies on our deep understanding and relentless focus on our people, we live by our mission: A passion for our people. Value for our customers.

If you think you can see yourself delivering our mission and pursuing our goals with us, then check out the job description below!

What you’ll do:

• Work in an agile environment as part of a small, integrated design and development team, participating in agile ceremonies and directly supporting government customers.
• Continuously improve client infrastructure and platform capabilities to support developers, data scientists, and AI-enabled workflows.
• Support development teams in deploying, maintaining, and troubleshooting web applications and AI-enabled services in a secure environment progressing from IL2 to IL4+.
• Design, deploy, and maintain CI/CD pipelines that support application delivery, experimentation, and secure software supply chains.
• Serve as a subject matter expert in containerization and DevSecOps, providing guidance on secure deployment patterns, platform services, and automation best practices.
• Automate provisioning of virtual machines and container platforms, enabling consistent, repeatable environments for development, testing, and deployment.
• Enable secure access to cloud services and internal capabilities via custom APIs, including token-based access controls and service-to-service authentication.
• Support secure experimentation environments, including notebooks and web-based IDEs (e.g., VS Code), while enforcing security and access controls.
• Implement and maintain secure package management, artifact repositories, and controlled dependency update processes.
• Support secure data transfer and access to segmented, secured environments, integrating SSO and role-based access controls across platform services.
• Monitor application and infrastructure health, performance, and availability using enterprise observability tools.

What you’ll need to succeed:

• Bachelor’s degree in a technical discipline (required).
• Active Secret security clearance (required).
• 4+ years of experience in DevSecOps or DevOps roles supporting production systems.
• Strong experience developing and supporting server-side web applications and backend services.
• Experience integrating applications with custom APIs to dynamically consume data, services, and AI-enabled capabilities.
• Hands-on experience deploying and operating containerized applications in secure or regulated environments.
• Experience with Kubernetes-based deployment patterns, including scaling, resilience, and secure configuration.
• Proficiency with CI/CD and automation tools such as GitLab CI, including pipeline optimization and security scanning.
• Experience managing, storing, and updating artifacts using secure artifact repositories.
• Experience deploying and operating services in AWS, including secure networking, IAM, and access controls.
• Familiarity with monitoring and observability platforms such as Datadog or Elastic Cloud.

SALARY RANGE: $110,000 - $124,000

The salary range for this position is determined based on qualifications, skills, and relevant experience. The final salary offered will be determined based on several factors including: 

• The candidate's professional background and relevant work experience
• The specific responsibilities of the role and organizational needs
• Internal equity and alignment with current team compensation
• This role is also eligible for additional compensation, subject to the terms and policies of MetroStar, which may include:
• Performance-based bonuses
• Company-paid training and/or certifications
• Referral bonuses

As a Sr. AI/ML Engineer I, you’ll design, develop, and deploy machine learning solutions supporting secure, web-based applications in a dynamic, mission-focused environment. This role emphasizes applied AI, experimentation, and collaboration with cross-functional teams to deliver production-ready capabilities that evolve as mission needs change.

We know that you can’t have great technology services without amazing people. At MetroStar, we are obsessed with our people and have led a two-decade legacy of building the best and brightest teams. Because we know our future relies on our deep understanding and relentless focus on our people, we live by our mission: A passion for our people. Value for our customers.

If you think you can see yourself delivering our mission and pursuing our goals with us, then check out the job description below!

What you’ll do:

• Design, develop, implement, and fine-tune AI and machine learning models to support web-based applications in secure environments with evolving use cases..
• Build and maintain data pipelines, training workflows, and experimentation environments to enable rapid model iteration and evaluation.
• Evaluate model performance using quantitative and qualitative metrics (e.g., accuracy, robustness, stability, efficiency, generalization) and translate results into actionable improvements.
• Analyze data, model outputs, and experimental results to recommend changes to algorithms, features, data sources, or system architecture.
• Proactively identify and assess tools, frameworks, and technologies that best support platform goals, balancing performance, scalability, and maintainability.
• Collaborate closely with software developers, data engineers, DevSecOps teams, and stakeholders to integrate AI capabilities into production systems.
• Ensure AI and data science solutions are transparent, testable, and maintainable to support long-term operational use.
• Communicate technical approaches, assumptions, tradeoffs, and results clearly to both technical and non-technical audiences, including during design reviews and demonstrations.

What you’ll need to succeed:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical discipline.
• Active Secret security clearance (required).
• 4+ years of experience in data science, machine learning, or applied artificial intelligence.
• Strong hands-on experience developing, training, and tuning AI/ML models using Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
• Experience selecting and applying appropriate modeling approaches (e.g., supervised, unsupervised, reinforcement learning, or hybrid methods) based on problem context.
• Strong software engineering fundamentals including API design, clean architecture, testing, and Git-based workflows. 
• Ability to work effectively in ambiguous problem spaces, defining requirements, success metrics, and implementation steps as understanding evolves.
• Experience integrating AI models into web-based or service-oriented platforms, working alongside DevSecOps engineering teams.
• Solid understanding of the full AI lifecycle, including data preparation, experimentation, validation, deployment considerations, and ongoing model improvement.

• Strong analytical and problem-solving skills, with sound judgment on when to prototype, iterate, or rethink an approach.

SALARY RANGE: $133,000 - $147,000

The salary range for this position is determined based on qualifications, skills, and relevant experience. The final salary offered will be determined based on several factors including: 

• The candidate's professional background and relevant work experience
• The specific responsibilities of the role and organizational needs
• Internal equity and alignment with current team compensation
• This role is also eligible for additional compensation, subject to the terms and policies of MetroStar, which may include:
• Performance-based bonuses
• Company-paid training and/or certifications
• Referral bonuses

As a Sr. DevSecOps Engineer I, you’ll support secure, mission-critical platforms in a federal environment. This role works as part of a small, agile design and development team, collaborating closely with developers, data scientists, and government stakeholders to deliver reliable, scalable, and secure application and platform capabilities.

We know that you can’t have great technology services without amazing people. At MetroStar, we are obsessed with our people and have led a two-decade legacy of building the best and brightest teams. Because we know our future relies on our deep understanding and relentless focus on our people, we live by our mission: A passion for our people. Value for our customers.

If you think you can see yourself delivering our mission and pursuing our goals with us, then check out the job description below!

What you’ll do:

• Work in an agile environment as part of a small, integrated design and development team, participating in agile ceremonies and directly supporting government customers.
• Continuously improve client infrastructure and platform capabilities to support developers, data scientists, and AI-enabled workflows.
• Support development teams in deploying, maintaining, and troubleshooting web applications and AI-enabled services in a secure environment progressing from IL2 to IL4+.
• Design, deploy, and maintain CI/CD pipelines that support application delivery, experimentation, and secure software supply chains.
• Serve as a subject matter expert in containerization and DevSecOps, providing guidance on secure deployment patterns, platform services, and automation best practices.
• Automate provisioning of virtual machines and container platforms, enabling consistent, repeatable environments for development, testing, and deployment.
• Enable secure access to cloud services and internal capabilities via custom APIs, including token-based access controls and service-to-service authentication.
• Support secure experimentation environments, including notebooks and web-based IDEs (e.g., VS Code), while enforcing security and access controls.
• Implement and maintain secure package management, artifact repositories, and controlled dependency update processes.
• Support secure data transfer and access to segmented, secured environments, integrating SSO and role-based access controls across platform services.
• Monitor application and infrastructure health, performance, and availability using enterprise observability tools.

What you’ll need to succeed:

• Bachelor’s degree in a technical discipline (required).
• Active Secret security clearance (required).
• 4+ years of experience in DevSecOps or DevOps roles supporting production systems.
• Strong experience developing and supporting server-side web applications and backend services.
• Experience integrating applications with custom APIs to dynamically consume data, services, and AI-enabled capabilities.
• Hands-on experience deploying and operating containerized applications in secure or regulated environments.
• Experience with Kubernetes-based deployment patterns, including scaling, resilience, and secure configuration.
• Proficiency with CI/CD and automation tools such as GitLab CI, including pipeline optimization and security scanning.
• Experience managing, storing, and updating artifacts using secure artifact repositories.
• Experience deploying and operating services in AWS, including secure networking, IAM, and access controls.
• Familiarity with monitoring and observability platforms such as Datadog or Elastic Cloud.

SALARY RANGE: $110,000 - $124,000

The salary range for this position is determined based on qualifications, skills, and relevant experience. The final salary offered will be determined based on several factors including: 

• The candidate's professional background and relevant work experience
• The specific responsibilities of the role and organizational needs
• Internal equity and alignment with current team compensation
• This role is also eligible for additional compensation, subject to the terms and policies of MetroStar, which may include:
• Performance-based bonuses
• Company-paid training and/or certifications
• Referral bonuses