DevSecOps Engineer

Basic Qualifications Bachelor's degree in Software Engineering, or related Science, Technology, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus 6 years relevant experience.

Due to the nature of work performed within our facilities, U.S. citizenship is required. Responsibilities for this Position ROLE AND POSITION OBJECTIVES:

DevSecOps Engineer — AIOps Team

As a DevSecOps Engineer on our AIOps team, you'll be a core member of a high-performing, cross-functional team responsible for modernizing critical enterprise systems through secure-by-design automation, AI-powered infrastructure, agentic AI workflows, and hardened deployment pipelines. You won't just write scripts — you'll engineer complete, security-integrated automation solutions from the ground up, embedding security controls into AI agents, Model Context Protocol (MCP) servers, and intelligent tooling across every layer of the stack.

We encourage you to apply if you have any of these preferred skills or experiences:

Proven experience building end-to-end automation solutions using GitLab CI, AKS (Azure Kubernetes Service), Terraform (with AzureRM provider), and Ansible — full lifecycle design and implementation with security controls built in from the start, not bolted on. Hands-on expertise deploying and managing containerized workloads on AKS and automating Azure infrastructure provisioning with Terraform and Ansible in an AIOps environment, with a focus on Azure Policy enforcement, RBAC, and hardened cluster configurations. Experience building and owning CI/CD pipelines end-to-end — integrating SAST, DAST, dependency scanning, and AI-powered tooling to automate secure testing,deployment, and operational workflows via GitLab CI targeting Azure environments. Experience designing, deploying, and securing MCP (Model Context Protocol) servers on Azure — leveraging Azure App Service, Container Apps, or AKS — that expose tools, data sources, and APIs as context for AI agents and LLM-powered workflows, with attention to access boundaries and least-privilege exposure. Hands-on familiarity with OAuth 2.0 / OpenID Connect authentication flows within MCP servers using Microsoft Entra ID (Azure AD), including token lifecycle management, scoped permissions, and secure delegation of access to downstream Azure services. Experience building or integrating AI agent skills — defining tool-use capabilities, orchestrating multi-step agentic workflows, and enabling agents to autonomously interact with Azure infrastructure, GitLab CI pipelines, and operational systems within defined security guardrails. Experience working with or deploying AI/ML models, LLM-based assistants, and agentic frameworks (e.g., Claude Agent SDK, A2A, ACP, or similar) in production or operational environments on Azure, with awareness of model trust boundaries and output validation. Understanding of prompt engineering, retrieval-augmented generation (RAG), and how to ground AI agents with real-time enterprise context via MCP or similar protocols — including risks like prompt injection and data leakage, and mitigation patterns applicable to Azure-hosted deployments.

Creative thinker with demonstrated success leading the software development life cycle Expertise in applying technical standards and methodologies to solve challenges Exceptional communication skills with the capacity to secure buy-in on concepts and ideas Collaborative team player eager to provide technical leadership and position others for success Commitment to ongoing professional development for yourself and others Identifies opportunities to apply AI for continuous improvement and innovation

An exciting career path with opportunities for continuous learning and development. Research oriented work, alongside award winning teams developing practical solutions for our nation’s security