Teams at AI Fund

Own full-cycle recruiting for Engineer in Residence candidates and AI Fund’s internal team, especially senior engineers and technical builders. Responsibilities include sourcing, screening, candidate closing, pipeline reporting, stakeholder communication, hiring event coordination, and process optimization. The recruiter will use AI for research, outreach, screening, and workflow development while evaluating hands-on technical and GenAI experience.

Build and operate production AI and LLM systems for safety-critical enterprise applications. Responsibilities include multi-step agent orchestration, retrieval across Neo4j and vector stores, evaluation frameworks, model comparison, observability, quality monitoring, failure handling, and production incident response. The role requires strong Python and experience with asynchronous services, LLM workflows, evaluation, retrieval, graph reasoning, and enterprise AI security. It also contributes to model selection, technical direction, and the AI roadmap.

Build and operate production AI systems for safety-critical enterprise applications. Responsibilities include multi-step LLM pipelines, agent orchestration, graph and hybrid retrieval, evaluation frameworks, observability, model selection, and production incident response. The role requires strong Python, FastAPI, asynchronous services, testing, and experience with LLM deployment, tool-calling workflows, evaluation, retrieval, and production operations. Graph expertise with Neo4j and Cypher is preferred, along with enterprise AI security and Azure experience.