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AI & Machine Learning 1h ago

Software/AI Developer & DevSecOps Engineer, R&D

Rackner
United StatesUnited States
Full-time
Not Disclosed
Mid-Level

Job Description

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CI/CDAI EngineerDevSecOps

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Build Secure, AI-Enabled Mission Software

Rackner is seeking a Software/AI Developer & DevSecOps Engineer, R&D to build mission-focused applications, AI-enabled development tools, and secure software-delivery pipelines for government and defense customers.

This is a hands-on role spanning software engineering, generative AI, application modernization, and DevSecOps. You will develop working software while creating the controls needed to use AI coding agents safely in secure government environments.

What You’ll Do

  • Build backend services, APIs, data workflows, and AI-enabled applications.
  • Develop model-agnostic coding agents and LLM workflows with human approval, prompt history, auditability, and controlled tool access.
  • Enforce architecture, UX, cybersecurity, testing, and deployment standards through automated policies and CI/CD controls.
  • Generate and maintain technical documentation, architecture diagrams, API documentation, and software bills of materials.
  • Use AI-assisted analysis to assess and modernize application portfolios through replatforming, refactoring, retirement, preservation, or API wrapping.
  • Integrate human- and AI-generated code into automated quality, functional, security, accessibility, and compliance testing.
  • Build hardened AI development environments using approved tools, isolated execution, restricted permissions, and secure containers or virtual machines.
  • Develop Platform One-compatible workflows that enforce Iron Bank images, approved cloud services, and Party Bus deployment requirements.
  • Connect user feedback, behavior telemetry, logs, metrics, and platform context to agents that identify issues and prepare reviewed pull requests.
  • Build platform-security automation that finds vulnerabilities and configuration risks, recommends fixes, and produces compliance evidence.
  • Collaborate with software, platform, cybersecurity, and mission teams to move R&D prototypes toward operational use.

What You’ll Bring

  • Strong software development experience, particularly with Python.
  • Experience building backend services, APIs, integrations, or data-driven applications.
  • Experience with generative AI, LLM applications, coding agents, or AI-assisted software development.
  • Experience with DevSecOps, CI/CD, cloud-native development, or platform engineering.
  • Familiarity with Docker, Kubernetes, Git, automated testing, security scanning, and infrastructure-as-code.
  • Understanding of application architecture, secure coding, code review, debugging, and software supply-chain security.
  • Ability to independently take an evolving technical problem from concept through implementation and demonstration.
  • U.S. citizenship and the ability to obtain and maintain a government security clearance.

Helpful Experience

  • Active Secret clearance or higher.
  • Experience with Platform One, Party Bus, Big Bang, Iron Bank, or DoD software factories.
  • Experience with OpenCode, Codex, Claude Code, LangGraph, LangChain, LlamaIndex, or similar agentic-development tools.
  • Experience with FastAPI, Prefect, Temporal, PostgreSQL, vector databases, or event-driven systems.
  • Experience with AWS, Azure, Helm, Terraform, GitLab CI, GitHub Actions, or Argo CD.
  • Familiarity with NIST SP 800-53, RMF, DISA STIGs, CMMC, cATO, or other DoD cybersecurity requirements.
  • Experience with SAST, DAST, SBOM generation, dependency scanning, observability, or automated remediation.
  • Experience modernizing legacy systems or developing software for classified, disconnected, or constrained environments.
  • Experience supporting defense, C2, ISR, mission planning, autonomy, or other national security missions.

What Success Looks Like

Success means delivering software and AI-assisted engineering workflows that are functional, secure, explainable, maintainable, and deployable. You will help shorten the path from mission need to operational capability while ensuring AI-generated changes remain controlled, tested, traceable, and subject to human review.

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