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# Software Engineer (LLM Engineering)

- **Company:** Isomorphic Labs
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Python (Programming Language), Software Engineering, Google Cloud, Large Language Models, Agentic-AI, Machine Learning Operations, Software Coding
- **Published:** November 7, 2026
- **Apply:** https://startup.jobs/senior-software-engineer-llm-engineering-london-isomorphic-labs-9761324

## About the Role

* Software Engineering: Strong coding skills (Python) with a focus on production-grade, maintainable systems.
 * System Design: Ability to architect and maintain (IaC) complex systems across multiple verticals (Security, UX, and Scalability) in the cloud.
 * LLM Internals: Deep understanding of how models are trained, how they work internally, and their inherent limitations.
 * LLM Serving stack: Experience with the LLM serving stack (e.g. vLLM) for open weight models for bringing the latest models to internal users.
 * ML Literacy: Experience evaluating probabilistic ML systems and managing model "tool use", contexts and loops.
 * First-Principles Thinking: A hype-detached approach to solving problems and selecting the right tech stack.
 * Communication: Excellent stakeholder management and the ability to explain technical risks to non-experts., * Applied LLM Experience: Prior success building and scaling systems centered around Large Language Models.
 * ML Infrastructure: Experience setting up the underlying hardware or orchestration for ML systems.
 * GCP: Prior experience building and deploying systems on Google Cloud (GCP).
 * Scientific Domain: Interest or experience in biology, chemistry, or drug discovery; an interest in applying AI to scientific discovery.
 * Fast-Moving Tooling: Familiarity with the latest in agentic tooling and developer frameworks.

## Description

As a member of the LLM Engineering team, you will work on a subset of the following:

 * System Architecture: Architect LLM-integrated systems by incorporating scalability, security, and user experience considerations from the earliest stages of development.
 * Operational Excellence: Enable telemetry, observability, governance and cost management. Build platform components and tools for routing and making optimal use of various models.
 * LLM & Agentic Infrastructure: Implement advanced context management, tool-use (MCP), skill tooling, and RAG to enhance research workflows and help scale our agentic infrastructure.
 * Evaluation Frameworks: Build rigorous testing for probabilistic systems to ensure model reliability and safety. Build and maintain evals for different tasks.
 * Agentic Tooling: Develop the internal frameworks and IDE integrations to leverage agentic coding and agentic workflows at scale. Contribute to shaping best practices and providing a great user experience.
 * Refinement & Training: Support fine-tuning and RL efforts in collaboration with AI researchers to optimise models for complex biological and chemical data.
 * Strategic Collaboration and Solutioning: Partner with researchers to translate scientific needs into technical AI specifications. Partner with other parts of the business to unlock LLM-based use-cases.