AI Engineers

We’re looking for experienced AI Engineers to build, deploy, and own production-grade AI systems. This is not a research-only role and not a junior position — we need people who have already shipped LLM-based solutions into real environments, where reliability, performance, and correctness actually matter.

Responsibilities

• Design, build, and deploy LLM-based systems into production environments
• Own end-to-end AI pipelines: experimentation, evaluation, deployment, and maintenance
• Build APIs and services for AI features using FastAPI or similar frameworks
• Implement and maintain RAG pipelines, agent-based systems, and orchestration logic
• Work closely with product and engineering teams to turn vague problems into reliable AI solutions
• Ensure production readiness: scalability, latency, observability, and failure handling
• Take responsibility for systems where errors have real consequences (business, legal, or safety-related)

Requirements

• Strong experience deploying LLMs in real production systems
• Ability to work independently without hand-holding
• Solid Python engineering skills
• Experience with PyTorch and modern LLM tooling
• Hands-on experience with Docker and production APIs (FastAPI or equivalent)

• Deep understanding of what “production-ready” actually means (monitoring, retries, edge cases, costs)

   

Nice to Have / Extra Credit

• Experience with ML infrastructure and model serving at scale
• Background in startups or contract-based engineering environments
• Experience in regulated or high-stakes domains (healthcare, finance, AI safety)
• Knowledge of Rust and/or C++
• Experience with reinforcement learning or multi-agent systems
• Experience designing systems where correctness and robustness are critical