Description

You will own problems end-to-end, taking ideas from initial exploration through to production deployment and ongoing iteration.

This role is hybrid.

Responsibilities

• Design, build, and deploy AI agents that operate reliably in real-world environments.
• Integrate AI systems into products, APIs, and business processes to ensure usability and scalability.
• Collaborate with engineering teams to ensure systems are robust, observable, and maintainable in production.
• Make pragmatic decisions balancing model performance, system latency, and cost efficiency.

Required Skills

• Strong Python skills with the ability to write clean, production-grade code.
• Proven experience shipping LLM-powered systems into production, including deployed LangChain/LangGraph solutions.
• Hands-on experience building AI agents or agentic workflows, including tool use, orchestration, and multi-step reasoning.
• Experience designing and implementing RAG systems that deliver meaningful improvements.
• Familiarity with MCP or similar orchestration patterns (e.g., FastMCP/FastAPI) for structured context handling.
• Understanding of LLM limitations and trade-offs, with the ability to mitigate hallucination, latency, and cost issues.
• Experience deploying systems in cloud environments (AWS, GCP, or Azure) using modern engineering practices.

Preferred Skills

• 5+ years of experience in data science or machine learning engineering.

Key Skills

Education

Any Gradute