Senior AI Infrastructure Engineer, Security & Observability

Bitwise•Laurel, MD

About The Position

We're building the next generation of AI infrastructure that will power innovation across the intelligence community. As a Senior Software Engineer on our Platform team, you'll own the AWS infrastructure, Kubernetes clusters, and security posture that every AI capability in the organization runs on. Your focus will be on deploying and maintaining reliable, secure infrastructure that the rest of our AI services depend on. You'll lead the design, deployment, and maintenance of cloud infrastructure used by the organization's AI capabilities, translate high-level stakeholder goals into engineering outcomes and platform solutions, and work within ambiguous problem spaces to define structured solutions the team can execute against. As a senior engineer, you'll mentor other engineers, grow development best practices, and establish and enforce security best practices for infrastructure systems and data. Requirements shift quickly as mission needs evolve and new technologies emerge, so you'll keep sharpening your skills and learning to turn loosely defined problems into working solutions.

Requirements

An active TS//SCI clearance with polygraph is required for this role.
12 years of experience, with a B.S. in a technical discipline (or 4 additional years of relevant experience in place of a B.S.)
Extensive experience with AWS services such as EKS, Terraform, IAM, and Route 53
Strong experience with Kubernetes and Helm/Kustomize
Hands-on experience with Docker and containerization
Experience with Argo CD and/or other CI/CD frameworks
Demonstrated experience configuring and using observability tooling such as the Elastic Stack (Kibana) and Grafana/Prometheus
Expertise in certificate management and cloud-native security practices
Proven experience supporting cloud-native architecture and maintaining production software and infrastructure
Ability to take high-level mission goals and transform them into engineering outcomes
Excellent communication, stakeholder management, and leadership skills
Ability to balance hands-on engineering with leadership and coordination responsibilities

Nice To Haves

Experience developing technical policies and governance frameworks
Experience with AI inference serving technologies (vLLM, LiteLLM, etc.)
Previous experience with agentic frameworks
Knowledge of vector databases and embedding systems
Familiarity with LLMs and AI hosting concepts

Responsibilities

Own the AWS infrastructure, Kubernetes clusters, and security posture that every AI capability in the organization runs on.
Deploy and maintain reliable, secure infrastructure that the rest of our AI services depend on.
Lead the design, deployment, and maintenance of cloud infrastructure used by the organization's AI capabilities.
Translate high-level stakeholder goals into engineering outcomes and platform solutions.
Work within ambiguous problem spaces to define structured solutions the team can execute against.
Mentor other engineers.
Grow development best practices.
Establish and enforce security best practices for infrastructure systems and data.
Keep sharpening your skills and learning to turn loosely defined problems into working solutions.