Senior AI Enablement Engineer

We’re Fundraise Up - a global fundraising platform built to make donating to nonprofits fast, seamless, and accessible to all. Every month, our technology powers tens of millions of dollars in donations across the globe. We focus on innovation that directly impacts results: faster load times, higher conversion rates...

Our platform is trusted by many of the world’s leading nonprofits, including UNICEF, the Alzheimer’s Association, and a wide range of global NGOs. With a 4.9/5 rating across top software review platforms, we’re recognized not just for our impact - but for the quality of the product we deliver.

We operate in the enterprise segment, serving nonprofit organizations across North America, the United Kingdom, Australia, and Europe.

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.
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.

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.
Familiarity with observability practices and stacks (OpenTelemetry, Prometheus, Grafana, Loki, or similar) — 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 — 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.

We expect every team member to actively use AI in their day-to-day work, identify where AI can change the shape of problems in their function, and grow their fluency as the tools evolve. You should already be using AI meaningfully in your work and understand where it adds value and how it can improve the way you operate.