Senior LLM Engineer - Hybrid London

Isomorphic Labs; Greater London; Hybrid; GBP 110,000 - 160,000; Full time

Job summary

Isomorphic Labs in London is seeking a Senior Software Engineer (LLM Engineering) to architect and deploy scalable AI systems that power advanced drug discovery. You will join the LLM Engineering team building end-to-end infrastructure for generative AI and model tooling.

You will own system design, tooling, evaluation, and collaboration with researchers to translate scientific needs into robust AI specifications. The role follows a hybrid model with in-office collaboration several days a week.

Qualifications

• Strong coding skills in Python for production-grade systems.
• Ability to architect and maintain complex cloud-based systems (IaC).
• Deep understanding of model internals and training processes.
• Experience with LLM serving stacks and open weight models.
• Excellent communication and stakeholder management.

Responsibilities

• Architect LLM-integrated systems prioritizing scalability and security.
• Enable telemetry, observability, governance, and cost management.
• Implement advanced context management, tool-use (MCP), skill tooling, and RAG.
• Build rigorous testing/evals for probabilistic systems to ensure reliability and safety.
• Develop internal tooling and IDE integrations to support agentic workflows at scale.
• Support fine-tuning and RL efforts with AI researchers to optimise models.
• Partner with researchers to translate scientific needs into technical AI specs.

Skills

Python

System Design

LLM Internals

LLM Serving stack

ML Literacy

First-Principles Thinking

Communication

Job description

Isomorphic Labs in London is seeking a Senior Software Engineer (LLM Engineering) to architect and deploy scalable AI systems that power advanced drug discovery. You will join the LLM Engineering team building end-to-end infrastructure for generative AI and model tooling.

You will own system design, tooling, evaluation, and collaboration with researchers to translate scientific needs into robust AI specifications. The role follows a hybrid model with in-office collaboration several days a week.