Aifund

Technical Builder

Palo Alto, CA

Sponsorship not specified$160k-$200kDetected 385 days ago

Full-Stack DevelopmentSQLNoSQLMachine LearningData EngineeringLLMsAI OrchestrationProduct StrategyCommunication

About the role

The AI Fund team combines their experiences as AI pioneers, entrepreneurs, venture capitalists, investors, and operators.
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 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.

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.
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.
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.
Demonstrated experience building applications that use large language models, multimodal models, or other modern AI capabilities in product workflows.
Habit of reading papers, model cards, technical postmortems, and production writeups, then folding useful lessons into the next build.

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.
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.

Experience shipping MVPs, prototypes, or early-stage products under ambiguity.
Contributions to open-source AI, developer tools, evals, retrieval, agents, or applied ML infrastructure.

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.
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 start with the simplest design that can answer the open question about an idea, and tighten the architecture only as evidence justifies it.
You will collaborate closely with product thinkers, designers, AI experts, and engineers to validate or falsify venture ideas through functional prototypes.

This listing is sourced directly from Aifund's careers page and normalized into a canonical job model.