Senior AI Enablement Engineer

Fundraise Up•Georgia - Remote, GA

9h•GEL 13,900 - GEL 16,000•Remote

About The Position

Fundraise Up is seeking a Senior AI Enablement Engineer to join their AI Platform team. This role focuses on driving the adoption of AI-assisted development across engineering and go-to-market (GTM) teams. The engineer will work at the intersection of engineering culture and internal tooling, coaching engineers, propagating best practices, removing adoption blockers, and building internal integrations to make AI-driven work the standard. Success will be measured by actual changes in how people build and demonstrable productivity gains, rather than just sentiment or session counts. The role involves hands-on work with AI tools and integrations, but not building the core agentic development platform itself.

Requirements

Senior, hands-on engineer with a strong full-stack background and 7+ years of experience shipping products 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), understanding how they work internally, and the end-to-end AI-assisted development workflow.
Track record of independently taking internal integrations from prototype to production, including design, authentication/authorization, deployment, security review, and 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, with the ability to explain complex topics to engineers at various 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 autonomously structure ambiguous, open-ended problems and drive them to completion, distilling various inputs into prioritized actions.
English proficiency C1 sufficient for written and verbal technical communication with external and internal audiences.
Fluent in English and Russian.

Nice To Haves

Familiarity with observability practices and stacks (OpenTelemetry, Prometheus, Grafana, Loki, or similar) for instrumenting usage and building dashboards.
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 focused on building durable learning.
Experience running technical workshops, hackathons, or enablement programs at organizational scale.
Experience in a distributed, remote-first engineering organization.

Responsibilities

Enablement & coaching: Work directly with engineers through 1:1s, pair programming, workshops, office hours, and cohorts to improve their effectiveness with AI-assisted development (prompting, workflow design, model/tool selection). Identify under-adoption and lift teams to the standard.
Best-practice propagation: Capture successful and unsuccessful AI usage patterns from one team and systematically transfer them through living best-practice guides, prompt libraries, troubleshooting playbooks, and an internal AI knowledge base and skills registry.
Scale through champions: Establish and support a network of embedded AI champions to scale enablement beyond a single person.
Unblocking & feedback loop: Act as the primary point of contact for engineers encountering issues with AI tooling. Proactively identify blockers, aggregate them into patterns, and escalate systemic issues to leadership.
Internal integrations & tooling: Independently build internal AI integrations and reusable tooling using Node.js/TypeScript, including authentication, access control, security review, and CI/CD, from prototype to production.
Evaluation & scouting: Conduct structured evaluations of AI tools, models, and internal integrations. Monitor the AI landscape (e.g., Claude Code, Cursor, Copilot/Codex, new model releases) and provide curated, actionable recommendations.
Measurement & impact: Define and track adoption and productivity metrics by team, tool, and individual. Build dashboards to visualize real usage and output, such as adoption/active-usage rate, assistant acceptance rate, PR throughput, and cycle time, while ensuring quality is maintained (change failure rate).
Cross-functional partnering: Collaborate with security/compliance teams on safe-by-design guardrails and with GTM teams to translate field needs into internal enablement and feed adoption patterns back.
Actively use AI in day-to-day work, identify where AI can change problem-solving approaches, and grow AI fluency as tools evolve.