AI Enablement Engineer

AI Enablement Engineer – Role Overview

We are scaling AI adoption across our engineering organization. We’ve built modern AI coding tools for our engineers and are now deepening the workflows and pushing into agentic development. The AI Enablement Engineer will 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.

• Scout and evaluate. Continuously track new AI coding tools, agents, IDEs, models, and MCP servers (Claude Code, Git Hub Copilot, Cursor, Codex, Antigravity, Open Code, Amp, and whatever ships next). Run structured evaluations against our real codebases and workflows.
• Build POCs. Stand up prototypes quickly to test whether a tool, agent, or workflow is worth adopting. Most won’t be, but some will be transformative – your job is to tell the difference fast.
• Propose and pilot. 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.
• Build the paved path. 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.
• Contribute to the innovation program. Participate in the engineering innovation program with Proofs of Concept (e.g., AI‑assisted defect triage, automated code review, agentic test generation, AI‑augmented documentation) and collaborate with team leads across product lines.
• Enable other engineers. Hold office hours, run internal demos and lunch "brown bags", write playbooks, debug other engineers’ agent workflows. Your impact is measured in their productivity, not yours.
• Measure impact. 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.

• 3–5 years of professional software engineering experience shipping production code.
• Deep hands‑on experience with AI coding agents — Claude Code, Cursor, Git Hub Copilot, Codex, or similar. You actively use these tools daily and have informed 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 navigate all.
• 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.

• 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.

We offer a comprehensive benefits package that includes 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 and hospital indemnity coverage, legal support, pet insurance, identity theft protection, a free mental health EAP, and more. The starting salary is anticipated between $100,000 and $120,000 and will be commensurate with experience.