Product Engineer, Personal AI

We are seeking exceptional product engineers who can move seamlessly across the stack: backend systems, web and mobile surfaces, LLM-powered workflows, infrastructure, reliability, and product iteration.

You will work close to the model, close to the user, and close to production, taking end-to-end ownership to turn new AI capabilities into software people use every day.

• Design, build, and launch polished, responsive user-facing product experiences across modern web and mobile stacks, partnering closely with design.
• Architect high-performance backend services in Rust and Python, managing APIs, data systems, job queues, event pipelines, and distributed systems at scale.
• Integrate large language models into real user workflows, managing tool use, memory, retrieval, structured outputs, latency optimization, and cost control.
• Own the core infrastructure needed to run a high-scale consumer AI product, including deployment, monitoring, CI/CD, cloud infrastructure, and incident response.
• Partner with research and infrastructure teams to take ambiguous ideas from prototype to production, translating new model capabilities into understandable and trustworthy product experiences.

• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical industry experience.
• A proven track record of building and launching meaningful production software, ideally in consumer products, large-scale systems, or high-growth startups.
• Deep backend expertise with practical experience in Rust, Python, databases, APIs, distributed systems, and production architecture.
• Strong frontend or mobile capability with modern technologies such as TypeScript, React, React Native, Swift, or Flutter.
• Exceptional product judgment with the ability to reason backward from user needs, alongside a high degree of ownership to navigate ambiguity.

Preferred Qualifications: (We encourage you to apply even if you don't meet all of these)

• Hands-on experience with LLM systems, including APIs, agents, tool calling, prompt iteration, eval frameworks, and inference constraints.
• Fluency with modern infrastructure and deployment platforms, including cloud environments, containers, Kubernetes, and Terraform or equivalent IaC.
• AI-native product instincts, with an understanding that LLM products require continuous evaluation, instrumentation, and close attention to real user behavior.
• Experience with systems reliability, including metrics, logs, alerts, and performance tuning for high-scale consumer products.

• Location: Palo Alto, California.
• Compensation: Depending on experience and skills the expected base pay is $200,000 - $420,000 USD per year, plus equity.
• Benefits: Comprehensive health, dental, and vision insurance; unlimited PTO; and relocation assistance as needed.
• Visa Sponsorship: We sponsor visas and are committed to supporting the process for the right candidate.

At River AI, our mission is to create personal AI owned and shaped by each individual. To achieve this, we are rewriting the entire stack from scratch: personal hardware for local inference, bespoke training infrastructure, next-generation UIs, and frontier deep learning research.

We are scientists, engineers, and builders from the industry's top tech companies and AI labs. We bring a proven track record of scaling consumer systems for hundreds of millions of users and architecting the pre-training infrastructure behind today's frontier models.