Staff AI Engineer

Responsibilities

• 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

Requirements

• 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

Qualifications

• 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.

Perks: 

• 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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