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 behaviour.

Requirements:

• 10 - 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.

Skills

AI, API, GenAI, GraphQL, LLM, ML, Node.js, Python, React, TypeScript, backend, cloud, frontend, full-stack