Engineer in Residence, AI Regulatory Intelligence & Operations

Job description

**Who we are:** AI is the new electricity: Just as electricity transformed numerous industries starting 100 years ago, AI is now poised to do the same. AI Fund is a venture studio founded by Dr. Andrew Ng in 2017. Our portfolio companies use AI technology to build applications across numerous industry sectors. The AI Fund team combines their experiences as AI pioneers, entrepreneurs, venture capitalists, investors, and operators. We are backed by a $390-million dollar fund from top-tier global corporations and VC firms. Our purpose is to build AI companies that move humanity forward **What We’re Looking For:** For the Engineer in Residence role, we are seeking an AI Full-Stack Engineer with fluency in software development and proficient in rapid prototyping. You should possess intense curiosity and leverage modern Generative AI frameworks. The ideal candidate thrives in fast-paced environments where the goal is to quickly build and iterate on full-stack applications leveraging cutting-edge AI techniques, as well as guiding technical vision and defining architectural patterns. You're passionate about staying ahead of the curve in AI constantly exploring new tools, frameworks, and best practices. You’ll collaborate closely with Andrew Ng to bring experimental ideas to life through functional prototypes. This role puts you in the front row of where AI is heading, working with technologies that are helping shape the future. If you’re driven by ambition, innovation, and the thrill of building what’s next this is the role for you. ### What you will do: - Drive rapid engineering efforts to build full-stack applications using GenAI tools, enabling deep exploration of product ideas, user experiences, and technical feasibility - Apply GenAI building blocks (prompt engineering, graphDBs, vectorDBs, agentic frameworks, evals, and guardrails) to real-world development - Make key decisions around infrastructure and platform choices, balancing short-term prototyping needs with long-term scalability - Collaborate cross-functionally with product, design, and AI experts to create, test, and iterate on new concepts - Use AI-assisted coding tools (e.g., Cursor, Windsurf, GitHub Copilot, Claude Code) to enhance productivity and speed of iteration - Gather user feedback and iterate quickly based on insights to improve usability and effectiveness - Deploy and manage applications on cloud infrastructure (e.g., AWS, GCP, Supabase) - Build and integrate APIs and third-party services - Participate in architecture discussions and technical planning - Identify and troubleshoot issues across the stack - Contribute to improving development processes, tools, and team practices - Stay current with industry trends and emerging technologies ### What you must bring: - Demonstrated experience building applications that incorporate Generative AI - Proficiency with GenAI tools and frameworks: prompt engineering, Retrieval-Augmented Generation (RAG), vector databases (e.g., Pinecone, Weaviate), agentic platforms (e.g., LangGraph, CrewAI), LLM evals, and guardrails - Experience with front-end technologies like JavaScript, HTML, CSS, and modern frameworks - Strong back-end skills, particularly with Python - Familiarity with SQL and NoSQL databases (PostgreSQL, MongoDB, etc.) - Hands-on experience using AI-assisted coding tools (e.g., Cursor, Claude Code) and understanding of best practices for effective use - Proven track record of architecting, implementing, and deploying scalable and maintainable AI-powered systems - Expertise in designing end-to-end system architectures involving front-end, back-end, APIs, and AI/ML components - Deep curiosity and a fast-learning mindset especially around emerging trends in AI - Ability to write scrappy, disposable code for fast prototyping, and clean code for scalable products - Strong communication skills and ability to work collaboratively across disciplines ### Nice to have: - Experience gathering user feedback directly and iterating based on insights - Exposure to rapid prototyping methodologies and shipping MVPs - Interest or experience in product design and product thinking - Contributions to open-source GenAI projects or tools - Familiarity with serverless architectures or edge computing - Prior experience as a technical lead or architect on teams delivering AI-driven products - Knowledge of advanced architecture patterns (microservices, event-driven architectures, datastore design) - Experience with large-scale system design and high-performance cloud infrastructures - Familiarity with governance, compliance, and security aspects in AI application architecture