LLM Engineer

Job Description

You will join an existing development team to build and ship LLM-powered features in a complex, large-scale production application. This is a hands-on, full-stack role spanning backend services, APIs, and the LLM systems (retrieval, agents, and evaluation) that power them. You will work as an agentic engineer, leveraging AI coding tools and autonomous agents to write code, automate workflows, and optimize delivery. Working closely with globally distributed teams across multiple time zones, you will own features end-to-end.

In this role, you will:

• Bring senior-level expertise in Python and LLM engineering.
• Independently plan, execute, and deliver technical solutions.
• Collaborate effectively with Product Owners and stakeholders to solve complex problems.
• Partner cross-functionally to deliver impactful solutions across teams.
• Continuously expand your technical expertise and stay current with emerging technologies.
• Demonstrate curiosity, initiative, and a commitment to continuous learning.
• Apply a data-driven approach to technical decision-making and problem-solving.
• Use systems thinking to connect data science and engineering principles.
• Take full ownership of features and projects, delivering high-quality solutions with minimal oversight.

Qualifications

• Hands-on, daily use of AI-assisted and agentic coding tools (e.g., Claude Code, Cursor, GitHub Copilot) to write, refactor, and automate code.
• Strong Python expertise with proven experience building REST APIs using frameworks like FastAPI.
• Solid grounding in NLP, machine learning, and hands-on experience with major LLM model APIs (e.g., OpenAI, Anthropic).
• Demonstrated experience designing and implementing RAG systems end-to-end, including vector databases, semantic search, and retrieval optimization.
• Experience building and deploying multi-agent systems and MCP servers in production environments at scale.
• Strong systems thinking and critical thinking skills with proven ability to debug, optimize, and make sound engineering decisions across complex backend systems, including security best practices for authentication and data protection.
• Proficiency with event-driven architectures, server-side events, and messaging systems.