DevSecOps Engineer - General Dynamics Mission Systems

OpenTalent; United States; On-site; USD 140,000 - 200,000; Full time

Job summary

OpenTalent is seeking a DevSecOps Engineer on the AIOps team to modernize critical enterprise systems with secure-by-design automation, AI-powered infrastructure, and hardened deployment pipelines on Azure.

You will own end-to-end CI/CD, integrate SAST/DAST, and embed security controls across MCP servers and AI agent workflows, leveraging AKS, Terraform, Ansible, and GitLab CI.

Qualifications

• Bachelor's degree with 8+ years of experience, or Master's with 6+ years.
• U.S. citizenship required due to work in facilities.
• Hands-on with GitLab CI, AKS, Terraform (AzureRM), Ansible.
• Experience enforcing Azure Policy, RBAC, hardened clusters.
• End-to-end CI/CD with SAST/DAST and AI tooling on Azure.
• Design and secure MCP servers on Azure (App Service/Container Apps/AKS).
• OAuth 2.0/OpenID Connect with Azure AD for access control.
• Experience with AI agent skills and agentic frameworks on Azure.

Responsibilities

• Engineer secure automation solutions across the stack from ground up.
• Develop end-to-end automation with GitLab CI and Azure deployments.
• Embed security controls and RBAC in pipelines and infrastructure.
• Design MCP servers exposing tools and data for AI agents.
• Implement agentic workflows and AI/LLM integrations in production.
• Ensure secure integration of AI agents with Azure infrastructure.

Skills

DevSecOps

Security automation

AI workflows

RBAC

OAuth 2.0

Education

Bachelor's degree in Software Engineering or related STEM

Master's degree

Tools

GitLab CI

AKS

Terraform (AzureRM)

Ansible

Azure Policy

Azure AD / Entra ID

Job description

ROLE AND POSITION OBJECTIVES:

DevSecOps Engineer — AIOps Team

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.

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.

• 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.