DevSecOps Engineer

General Dynamics

Remote Hybrid

Quick summary

Work type
Remote
Location
Remote
Salary
$142,696–$158,303 / yr
Posted
3 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $163k
This role $150k
$118k most similar roles pay here $208k

This role pays less than 59% of similar roles. Most pay $126,800–$199,225 — the shaded band above. At the midpoint, this role pays about $150k versus about $163k for comparable roles.

Based on 240 similar postings.

Employer

About General Dynamics

General Dynamics is a global aerospace and defense company offering a broad portfolio of products and services in business aviation, ship construction, land combat vehicles, and information technology. It serves customers in the U.S. government, allied governments, and a diverse array of commercial markets.

General Dynamics currently has 439 open roles on FindRole.

Listed pay typically runs $112,924–$149,500 across 366 roles with salary data.

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At a glance

TL;DR · DevSecOps Engineer

As a DevSecOps Engineer on the AIOps team, you will be part of a high-performing, cross-functional group tasked with modernizing critical enterprise systems through secure-by-design automation and AI-powered infrastructure. Your daily responsibilities include designing and implementing end-to-end automation solutions using GitLab CI, AKS, Terraform, and Ansible, ensuring security controls are integrated from the start. You will also deploy and manage containerized workloads on AKS, automate Azure infrastructure provisioning with Terraform and Ansible, and build secure CI/CD pipelines integrating SAST, DAST, dependency scanning, and AI-powered tooling. Additionally, you will design and secure MCP servers on Azure, handle OAuth 2.0 authentication flows, and enable agentic workflows for AI agents to interact autonomously within defined security guardrails. This role requires hands-on experience with AI/ML models, LLM-based assistants, and agentic frameworks in production environments, as well as a deep understanding of prompt engineering and real-time enterprise context integration.

What you'll do

  • Design and implement secure-by-design automation solutions using GitLab CI, AKS, Terraform, and Ansible.
  • Deploy and manage containerized workloads on Azure Kubernetes Service (AKS) with hardened configurations.
  • Build and maintain CI/CD pipelines integrating SAST, DAST, dependency scanning, and AI-powered tooling for secure testing and deployment.
  • Design and deploy Model Context Protocol (MCP) servers on Azure to expose tools, data sources, and APIs securely for AI agents.
  • Implement OAuth 2.0 / OpenID Connect authentication flows within MCP servers using Microsoft Entra ID for secure access management.
  • Develop agentic workflows enabling autonomous interaction of AI agents with Azure infrastructure and operational systems under security guardrails.

What we're looking for

  • Proven experience in building end-to-end automation solutions using GitLab CI, AKS, Terraform, and Ansible.
  • Hands-on expertise in deploying containerized workloads on AKS and automating Azure infrastructure provisioning with Terraform and Ansible.
  • Experience in designing and securing Model Context Protocol (MCP) servers on Azure for AI agents and LLM-powered workflows.
  • Familiarity with OAuth 2.0/OpenID Connect authentication flows within MCP servers using Microsoft Entra ID, including token lifecycle management.
  • Expertise in building CI/CD pipelines integrating SAST, DAST, dependency scanning, and AI-powered tooling for secure testing and deployment.
  • Experience deploying or integrating AI/ML models, LLM-based assistants, and agentic frameworks in production environments on Azure.

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