AI Enablement Engineer
About The Position
We're scaling AI adoption across our engineering organization. We've rolled out modern AI coding tools to our engineers, and we're now deepening the workflows and pushing into agentic development. We're hiring an AI Enablement Engineer to sit at the center of that effort: evaluating every new AI coding tool worth our attention, building proofs-of-concept, and turning the best of what's out there into adopted practice across the organization. This is a hands-on engineering role, not a research or strategy seat. You'll write code, ship integrations, run experiments, and measure what actually moves the needle.
Requirements
- 3–5 years of professional software engineering experience shipping production code
- Deep hands-on experience with AI coding agents — Claude Code, Cursor, GitHub Copilot, Codex, or similar. Not "I tried it once." You actively use these tools daily and have opinions.
- Experience writing effective agent context (CLAUDE.md, custom instructions, skills, prompt libraries) that measurably improved output quality
- Comfortable across the stack: backend, CI/CD, scripting, light frontend. You don't need to be senior in any one area, but you can't be afraid of any of them.
- Voracious curiosity. The AI tooling landscape changes monthly; you read release notes, follow practitioners, and try things on weekends because you want to.
- Strong written and verbal communication — you'll be teaching, recommending, and influencing constantly
- Comfortable with ambiguity and rapidly changing conditions
Nice To Haves
- Experience building MCP server integrations or agent tool integrations
- Familiarity with prompt engineering, evals, or LLM-as-judge patterns
- Exposure to developer productivity measurement (DORA, SPACE, DX framework)
- Background in regulated or mission-critical software
Responsibilities
- Scout and evaluate new AI coding tools, agents, IDEs, models, and MCP servers (Claude Code, GitHub Copilot, Cursor, Codex, Antigravity, OpenCode, Amp, and whatever ships next). Run structured evaluations against our real codebases and workflows.
- Build prototypes quickly to test whether a tool, agent, or workflow is worth adopting.
- Make clear, data-backed recommendations on what to adopt, what to drop, and where to invest. Run pilots with one or two teams before broader rollout.
- Author agent guidance files (CLAUDE.md, agents.md, custom skills, context files) and MCP server integrations connecting agents to issue trackers, documentation systems, source control, CI/CD, code quality tools, and chat platforms. Make AI tools work well on our code, not in the abstract.
- Participate in the engineering innovation program with Proof of Concepts (e.g., AI-assisted defect triage, automated code review, agentic test generation, AI-augmented documentation), and collaborate with team leads across product lines.
- Hold office hours, run internal demos and lunch "brown bags", write playbooks, debug other engineers' agent workflows.
- Partner with engineering analytics to track AI tool adoption, usage depth, code generation rates, and downstream effects on PR throughput, defect rates, and cycle time.
Benefits
- medical
- dental
- vision
- life and disability coverage
- paid time off
- a 401(k) retirement plan
- paid parental leave
- access to a robust library of personal and professional training resources
- employee discounts
- critical illness
- hospital indemnity
- access to legal support
- pet insurance
- identity theft protection
- an EAP (Employee Assistance Program) that includes free mental health resources/support
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
