Senior AI Enablement Engineer

Highlights:

• Location:
  
  Georgia, Remote
• Language:
  Fluent in English and Russian

We7re 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, global payment support, and accessibility-first design.

Our platform is trusted by many of the worlds leading nonprofits, including UNICEF, the Alzheimers Association, and a wide range of global NGOs. With a 4.9/5 rating across top software review platforms, were 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.

Were building a large and complex product ecosystem that serves nonprofits, donors, and partners around the world. The platform includes a modern checkout experience and customizable widgets (each a standalone SPA),
donor, organization, and partner portals
, admin tools
, and several internal apps.

Our backend is powered by Node.js (Koa, NestJS) and MongoDB
. The frontend stack includes Webpack, Vue.js, and React
, with nearly all code written in Type Script . For high-throughput messaging and background processing, we use Kafka (for millions of events) and Bull (Redis). Analytics data is stored in Click House
, and we use Elasticsearch for search.

We are a distributed team of 160+ product professionals, including 80+ engineers. Our team members are mainly based across Spain, Poland, Portugal, Georgia, Armenia, Serbia, Turkey, and Cyprus. Many of our developers bring 5 - 10+ years of experience, and we foster a culture of deep technical curiosity and knowledge sharing.

Despite our scale, we operate like a focused team - where every task matters and every voice is heard. We value thoughtful collaboration, strong engineering practices, and a product mindset. You9ll be joining a team where quality, mentorship, and mutual respect come first.

Youll join the AI Platform team inside our Engineering department. The team builds the tooling and integrations that make AI-assisted development the frictionless default across engineering 7 e 9 0 0 0 — and works hands-on with non-engineering teams to turn that capability into real, measured productivity. This role is the human-and-integration side of that mission: you multiply what our engineers can do with AI.

You will not be building the agentic development platform itself (agent runner, one-shot PR agents, dev containers, orchestration) a separate team in the same org owns that.

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 2c 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 1 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/Type Script, 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.…