AI Workflow Engineer

Ultimate Knowledge

8h•$150,000 - $200,000•Remote

About The Position

UKi is seeking an AI Workflow Engineer to architect and build an agentic Software Development Life Cycle (SDLC) from the ground up. This role involves designing formalized pipelines where AI agents collaborate with senior engineers to plan, build, test, review, and ship software. The focus is on creating workflows, guardrails, and feedback loops that enhance delivery speed while maintaining engineering excellence. This position directly supports the mission of delivering workforce readiness to the nation's cyber warfighters. Agentic development is presented as a significant shift in software development, comparable to the advent of continuous delivery, offering a unique opportunity to shape this transformation.

Requirements

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.
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 (Allspaw/Hammond, Phoenix Project school of small batches, fast feedback, blameless learning, and operational excellence).
A self-starter's bias for action: ability to identify opportunities, build, measure, and share solutions.
Strong communication skills, capable of explaining agentic architecture to engineers and ROI to executives.
Must be authorized to work in the United States; role is US-remote.

Nice To Haves

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.

Responsibilities

Build our agentic SDLC pipeline, designing, implementing, and operating agentic workflows across the development lifecycle (planning, code generation, review, testing, documentation, and release), integrated with GitOps and CI/CD infrastructure.
Level up developer experience by integrating modern AI into the daily workflow of the engineering team, including coding agents, automated review, intelligent test generation, and self-service tooling.
Engineer grounded, trustworthy AI systems that produce reliable, verifiable results, and design evaluation harnesses to prove their efficacy.
Establish governance and guardrails by defining and implementing policies, human-in-the-loop checkpoints, audit trails, and security controls for responsible AI adoption.
Formalize and scale successful agentic practices into repeatable frameworks, playbooks, and internal platforms for broader organizational use.
Champion the practice of AI adoption across the team, acting as a force multiplier.