Senior AI Enablement Engineer

As an AI Enablement Engineer, you multiply the output of engineering (and GTM) teams by driving effective adoption of AI-assisted development. You work at the intersection of engineering culture and internal tooling — coaching engineers, propagating proven practices, removing adoption blockers, and building the internal integrations that make AI-driven work the standard. You measure impact through real, data-backed productivity gains rather than sentiment. Success is whether people actually change how they build — not how many sessions you ran.

Responsibilities

Enablement & coaching — work directly with engineers through 1:1s, pair programming, workshops, office hours, and cohorts to raise their effectiveness with AI-assisted development: prompting, workflow design, and model/tool selection. Identify under-adoption and lift teams up to the standard; Best-practice propagation — capture what works (and what fails) in one team and systematically transfer it: living best-practice guides, prompt libraries, troubleshooting playbooks, and an internal AI knowledge base and skills registry; Scale through champions — stand up and support a network of embedded AI champions so enablement scales past a single person; Unblocking & feedback loop — be the go-to when engineers get stuck with AI tooling. Proactively tour teams to surface blockers early, aggregate them into patterns, and escalate systemic issues to leadership; Internal integrations & tooling — build internal AI integrations and reusable tooling hands-on (Node.js/TypeScript, MCP) — from prototype to production independently, including auth, access control, security review, and CI/CD; Evaluation & scouting — run structured evaluations of AI tools, models, and internal integrations; monitor the fast-moving landscape (Claude Code, Cursor, Copilot/Codex, new model releases) and deliver curated, actionable recommendations; Measurement & impact — define and track adoption and productivity metrics by team, tool, and individual. Build dashboards on real usage and output — adoption/active-usage rate, assistant acceptance rate, PR throughput and cycle time — with a quality guardrail (change failure rate) so speed never comes at the cost of quality. Reference frameworks: DX Core 4, DORA; Cross-functional partnering — partner with security/compliance on safe-by-design guardrails, and with GTM to translate field needs into internal enablement and feed adoption patterns back

Requirements

Fluent in English and Russian; Senior, hands-on engineer with a strong full-stack background — 7+ years shipping in a product-driven environment; Proficiency in Node.js/TypeScript for building services and integrations, with working knowledge of relational and document databases; Deep, hands-on fluency with agentic coding tools (Claude Code, Cursor, Codex) — how they work internally, not just how to use them — and with the end-to-end AI-assisted development workflow; Track record of taking internal integrations from prototype to production independently — design, authn/authz, deployment, security review, CI/CD; Experience building integrations against third-party APIs and agent-tooling protocols (e.g., MCP); Working knowledge of GenAI building blocks: LLMs, prompting, RAG, orchestration, agentic flows, and AI/tooling security; Strong teaching, facilitation, and technical-writing skills — able to explain complex topics to engineers at different levels and produce guides, workshops, and walkthroughs; Cross-functional operating skill — comfortable influencing without authority and coordinating with IT, DevOps, security, and GTM; Ability to structure ambiguous, open-ended problems autonomously and drive them to completion, distilling many inputs (1:1s, feedback, surveys) into prioritized action; English proficiency C1 sufficient for written and verbal technical communication with external and internal audiences

Nice to have

Familiarity with observability practices and stacks (OpenTelemetry, Prometheus, Grafana, Loki, or similar); Experience deploying on edge or serverless compute (Workers, Durable Objects, KV, or similar); Experience building and operating an internal plugin/package registry or marketplace with automated publishing; Prior developer-experience, developer-advocacy, or internal-tooling role; Instructional-design or learning-science experience — building durable learning, not one-off demos; Experience running technical workshops, hackathons, or enablement programs at organizational scale; Experience in a distributed, remote-first engineering organization

Benefits

31 days off; 100% paid telemedicine plan; Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace; English learning courses; Relevant professional education; Gym or swimming pool; Co-working; Remote working; Equity options