Technical Builder

AI Fund is a venture studio founded by Dr. Andrew Ng, focused on building AI companies that advance humanity. They are seeking a Technical Builder to develop full-stack AI prototypes, design AI systems, and collaborate with cross-functional teams to validate venture ideas.

Responsibilities:

• Build full-stack AI prototypes that pressure-test venture ideas before founder or entrepreneur-in-residence handoff
• Design AI systems from composable building blocks and make the tradeoffs visible to product and engineering partners
• Choose retrieval and context strategies that fit the data and task, from structured queries and hybrid search to reranking, graph traversal, and long-context or human-curated context
• Build agentic and workflow-based systems with clear control flow, bounded autonomy, useful tool interfaces, state management, recovery paths, and human review where appropriate
• Make architecture and platform choices that fit the stage of an idea, keeping prototypes cheap to change while leaving a credible path to production if the idea validates
• Build and integrate APIs, databases, third-party services, internal tools, and cloud infrastructure
• Define evaluation loops for AI behavior, including task success, retrieval quality, factuality, tool-call correctness, grounding, safety, latency, cost, and user-perceived quality
• Use error analysis to decide whether to improve prompts, data, retrieval, tools, orchestration, model choice, UX, or product scope
• Collaborate cross-functionally with product, design, and AI experts to create, test, and iterate on new concepts using direct user feedback
• Present build results to potential entrepreneurs-in-residence and founders: what worked, what failed, what they need to know to decide next steps
• Direct frontier coding agents to turn clear product and technical intent into working software, while owning the architecture, review, debugging, and quality bar
• Identify and troubleshoot issues across the full stack, including frontend, backend, AI orchestration, data pipelines, deployment, and production behavior
• Contribute to better development processes, reusable engineering practices, and shared technical judgment across the team