Staff AI Engineer

Own end-to-end delivery of AI-powered products — from problem framing and architecture through implementation, deployment, and production operations

Design, build, and ship full-stack systems: frontend, backend APIs, data layers, and AI/ML services — not just models or prompts

Take a product from idea to production independently: design APIs, build UIs, wire data flows, integrate models, and operate the system

Build and productionize LLM / GenAI features (RAG, agents, tool-calling, evaluation, guardrails) and integrate them into real user-facing applications

Design scalable application and model-serving architectures that are reliable, observable, and cost-aware

Own data pipelines, retrieval, embeddings, and evaluation loops so AI features stay accurate and measurable in production

Work across the stack as needed — React/Next (or equivalent), Node/Python/Go services, databases, queues, cloud, and CI/CD — without waiting on a specialist for every layer

Partner with product, design, and engineering to turn ambiguous problems into shipped features

Review code, raise the bar on system design, and mentor engineers on both AI and full-stack practices

Establish engineering standards for AI quality, evaluation, security, and release confidence

Debug production issues across the full path: UI, API, infra, data, and model behavior

15+ years of software engineering, with recent hands-on ownership of production systems

Proven full-stack depth: can design and implement frontend, backend, APIs, data stores, and cloud infrastructure — not limited to AI-only work

Hands-on with AI-assisted development tools (Cursor, GitHub Copilot, and similar) as part of day-to-day engineering

Hands-on experience shipping LLM / GenAI or ML systems in production (RAG, agents, fine-tuning, evaluation, or equivalent)

Comfortable choosing and using the right stack for the problem (e.g. TypeScript/Python, React or similar, REST/GraphQL, SQL/NoSQL, queues, object storage)

Experience with CI/CD, distributed systems, and production debugging

Strong ownership: can take an ambiguous brief and deliver a working product end to end

Clear communication and the ability to work with product, design, and other engineers without hand-holding

Degree in Computer Science / Engineering or equivalent practical experience

Hands-on engineer with a production-level coding mindset — writes, reviews, and ships code

Track record of building scalable, reliable systems, not just prototypes or notebooks

Good documentation and collaboration skills

Bias toward owning the whole problem: product, architecture, implementation, and operations.

Day off on the 3rd Friday of every month (one long weekend each month)

Monthly Wellness Reimbursement Program to promote health well-being

Monthly Office Commutation Reimbursement Program

Paid paternity and maternity leaves

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