Software Engineer 3 - (Kubernetes, Docker, Prometheus)

Akina • Annapolis Junction, MD

4d • Onsite

About The Position

Act as a Software Engineer focused on DevOps, platform engineering, and infrastructure automation for a mission delivering AI/ML capabilities to end users. The work centers on building reliable, scalable infrastructure and deployment pipelines rather than application development, supporting continuous availability of mission-critical services through infrastructure-as-code, containerization, and orchestration. Implement observability and monitoring solutions that track system health and user usage patterns. Collaborate with data scientists and system administrators and own the platform layer that enables rapid, resilient delivery of AI technologies to the mission.

Deploy and manage containerized AI/ML services using Kubernetes in on-premises environments. Implement monitoring and observability with Prometheus, Grafana, or related tooling; build and maintain CI/CD pipelines and infrastructure-as-code; design resilient infrastructure patterns for high availability and performance; and work with stakeholders to translate operational and reliability requirements into platform engineering solutions. The position requires TS/SCI clearance with polygraph.

Requirements

• TS/SCI clearance with polygraph required.
• At least 12 years of experience as a Software Engineer on programs and contracts of similar scope, type, and complexity.
• Bachelor's degree in Computer Science or a related discipline from an accredited college or university; four additional years of SWE experience on projects with similar software processes may substitute for the degree.
• Experience deploying and managing services in on-premises infrastructure environments.
• Production experience containerizing and orchestrating services with Docker and Kubernetes.
• Experience with observability and monitoring tools such as Prometheus, Grafana, or equivalent platforms.
• Knowledge of CI/CD pipelines and GitOps workflows.
• Experience with version control using Git.
• Experience with Atlassian tools, including Jira and Confluence.

Nice To Haves

• Experience with model-serving technologies such as vLLM, TorchServe, TensorFlow Serving, or Triton Inference Server.
• Knowledge of AI infrastructure tools and frameworks such as LiteLLM, Bifrost, Ray, or Ollama.
• Knowledge of service mesh technologies such as Istio or Linkerd, or advanced Kubernetes patterns.
• Awareness of the current AI/ML landscape, including emerging models, capabilities, and applicability to different use cases.
• Knowledge of end-to-end SIGINT collection and analysis systems.
• Experience with production CNO capabilities and operations.

Responsibilities

• Deploy and manage containerized AI/ML services using Kubernetes in on-premises environments.
• Implement observability and monitoring solutions using Prometheus, Grafana, and related tooling to track system health and usage metrics.
• Build and maintain CI/CD pipelines and infrastructure-as-code for reliable, automated deployment of platform services.
• Design and implement resilient infrastructure patterns to ensure high availability and performance of mission-critical capabilities.
• Collaborate with stakeholders to translate operational and reliability requirements into platform engineering solutions.
• Own the platform layer that enables rapid, resilient delivery of AI technologies to the mission.

Benefits

• 24 days of PTO accrued annually and 11 federal holidays.
• 401(k) is 100% vested on the start date, with a company direct contribution worth 10% of salary.
• Company covers 100% of employee healthcare costs and 50% of dependent healthcare costs.
• Educational assistance for college classes.
• Company covers costs associated with job-related training and certifications.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior