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
We are seeking an AI engineer with architecture judgment, product instincts, and fluency across the modern AI application stack.
You should be able to decompose AI products into composable building blocks: model selection, prompting, tool use, retrieval, structured outputs, memory and state, workflow orchestration, planning, reflection, evaluation, observability, and safety controls. You should understand the reason each component belongs in a system, the tradeoffs it introduces, and the evidence needed to know whether it is working.
You start with the simplest design that can answer the open question about an idea, and tighten the architecture only as evidence justifies it.
You follow where AI is heading and ground engineering decisions in product goals, user behavior, the data available for the problem, system constraints, and measured performance. You will collaborate closely with product thinkers, designers, AI experts, and engineers to validate or falsify venture ideas through functional prototypes.
What You Will Do:
- 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.
What You Must Bring:
- 3+ years of software engineering experience, including end-to-end ownership of at least one production AI application architecture spanning UI, backend, data, models, tools, and evaluation.
- Demonstrated experience building applications that use large language models, multimodal models, or other modern AI capabilities in product workflows.
- Strong technical fluency across frontend, backend, APIs, databases, and cloud deployment, with enough depth to review, debug, and steer implementation.
- Expert ability to work with frontier coding agents, including writing precise specs, decomposing work, inspecting generated code, catching architectural mistakes, and deciding when to intervene directly.
- Ability to justify retrieval choices against corpus structure, freshness, permissions, latency, precision, recall, and cost.
- Experience with SQL and NoSQL data systems, including the ability to model data for application use, retrieval, analytics, and operational reliability.
- Strong communication skills and the ability to work collaboratively across disciplines.
- Habit of reading papers, model cards, technical postmortems, and production writeups, then folding useful lessons into the next build.
Nice To Have:
- Experience shipping MVPs, prototypes, or early-stage products under ambiguity.
- Experience as a technical lead, architect, founding engineer, or senior builder on AI-driven products.
- Contributions to open-source AI, developer tools, evals, retrieval, agents, or applied ML infrastructure.
- Interest or experience in product design, product strategy, or company creation.
Skills Required
- 3+ years of software engineering experience with end-to-end ownership of a production AI application architecture (UI, backend, data, models, tools, evaluation).
- Demonstrated experience building applications using large language models, multimodal models, or modern AI capabilities.
- Strong technical fluency across frontend, backend, APIs, databases, and cloud deployment with depth to review and debug implementations.
- Expert ability to work with frontier coding agents: write precise specs, inspect generated code, and intervene appropriately.
- Ability to justify retrieval and context strategies against corpus structure, freshness, permissions, latency, precision, recall, and cost.
- Experience with SQL and NoSQL data systems and modeling data for retrieval, analytics, and operational reliability.
- Strong communication skills and ability to collaborate across product, design, and engineering.
- Habit of reading research papers, model cards, postmortems, and production writeups and applying lessons learned.
- Experience shipping MVPs, prototypes, or early-stage products under ambiguity.
- Experience as a technical lead, architect, founding engineer, or senior builder on AI-driven products.
- Contributions to open-source AI, developer tools, evals, retrieval, agents, or applied ML infrastructure.
- Interest or experience in product design, product strategy, or company creation.
AI Fund Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AI Fund and has not been reviewed or approved by AI Fund.
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Healthcare Strength — Health coverage is portrayed as strong with great healthcare and dental coverage, plus vision insurance, long-term disability, and life insurance. Feedback suggests this aligns with tech-standard benefits for US roles at a small venture studio.
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Retirement Support — Retirement benefits include a 401(k) plan with employer match for US employees. Feedback suggests this forms part of a competitive total package for fund roles.
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Parental & Family Support — Family support includes fully paid parental leave for applicable roles. Feedback suggests this is a standout benefit for an organization of this size.
AI Fund Insights
What We Do
Who is AI Fund? We are a team of AI pioneers, proven entrepreneurs, seasoned operators, and venture capitalists that collaborates with leading entrepreneurs to solve big challenges using artificial intelligence. Founded in 2017 by Dr. Andrew Ng, AI Fund is backed with $176 million in capital by some of the leading VC firms and investors, including NEA, Sequoia, and Greylock. How Are We Different? We work with entrepreneurs during their startup’s most critical and risky phase, from 0 to 1. At the earliest stages, your company strategy is still being formed, and you’re still on the path to demonstrating your idea’s full potential – this is a reality we understand. This is the period when decisions on product strategy, market fit, and team are most critical, moving fast and fixing parts of your business when you have limited resources is a challenge. We believe the best way to help entrepreneurs is by providing our time, expertise, and resources to help flesh out these key strategic decisions. Making the right decisions at the right time can often make the difference. We are here to improve these dynamics, at a time when the help matters the most. Why Work With AI Fund? Getting a startup from idea to Series A funding is not easy. We’ve been there and understand the challenges you must overcome. Whether you desire limited help and just want access to our unique ecosystems of AI experts and entrepreneurs or you would like our full support, we are interested in the opportunity to help in your success. We are flexible in how we work with companies, but ultimately, we are here to maximize your chance of success and accelerate getting your company to market. We provide the capital, expertise, and resources to accelerate the work required to minimize risks in your startup, help you rise above the noise, and make your company more attractive to new investors.
