Note: The job is a remote job and is open to candidates in USA. Ultimate Knowledge Institute is a leader in cybersecurity training and readiness for the Department of Defense and other organizations. They are seeking an AI Workflow Engineer to architect and implement agentic software development lifecycle workflows, integrating AI systems to enhance development processes and ensure governance and security in AI adoption.
Responsibilities
- Build our agentic SDLC pipeline. Design, implement, and operate agentic workflows across the development lifecycle - planning, code generation, review, testing, documentation, and release that is all integrated with our GitOps and CI/CD infrastructure
- Level up developer experience. Bring modern AI integrations into the daily workflow of our engineering team: coding agents, automated review, intelligent test generation, and self-service tooling that removes friction and multiplies output
- Engineer grounded, trustworthy systems. Build retrieval-grounded and context-aware AI systems that produce reliable, verifiable results and design the evaluation harnesses that prove it
- Establish governance and guardrails. Define and implement the policies, human-in-the-loop checkpoints, audit trails, and security controls that let us adopt agentic AI responsibly in environments where trust is non-negotiable
- Formalize and scale. Turn what works into repeatable frameworks, playbooks, and internal platforms that extend agentic acceleration beyond engineering to the whole organization
- Champion the practice. Evangelize, teach, and support AI adoption across the team; you'll be a force multiplier, not a silo
Skills
- 2–3+ years of hands-on experience building with AI/LLM systems in production settings
- 2+ years designing and operating agentic workflows and pipelines including multi-step agent orchestration, tool use, evaluation, and governance
- Experience embedded in modern development teams practicing GitOps and CI/CD (required)
- Working knowledge of grounded AI patterns: RAG, context engineering, structured outputs, and evaluation/observability for LLM systems
- Solid software engineering fundamentals in JavaScript/TypeScript and/or Python; comfort working in and around our stack (Angular/React frontends on Express web applications)
- Genuine alignment with continuous delivery culture the Allspaw/Hammond, Phoenix Project (Kim) school of small batches, fast feedback, blameless learning, and operational excellence
- A self-starter's bias for action: you see an opportunity to accelerate the team and you build it, measure it, and share it
- Strong communication skills you can explain an agentic architecture to an engineer and its ROI to an executive
- Must be authorized to work in the United States; role is US-remote
- Experience with agent frameworks and protocols (e.g., LangGraph/LangMem, Claude Agent SDK, MCP, OpenAI Agents) and AI coding tools (Claude Code, Copilot, Cursor)
- Building developer platforms, internal tooling, or platform engineering / DevEx functions
- DORA-style delivery metrics and engineering analytics
- Familiarity with AI governance frameworks (NIST AI RMF) and secure SDLC practices
Benefits
- Plus benefits
Company Overview