About the Role
Distyl is an applied AI technology company partnering with the world's most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We're opening an office in London, UK and looking for AI Engineers to design and deploy production-grade AI systems powered by LLMs.
Responsibilities
•Design, develop, and deploy robust AI applications using LLMs, including prompt engineering, agent workflows, tool use, and full-stack AI products
•Partner closely with enterprise stakeholders to understand complex problems and translate them into impactful AI solutions
•Design scalable architectures for production AI systems, balancing performance, reliability, cost, and maintainability
•Contribute to Distillery, our internal LLM application platform, by building reusable infrastructure, tools, and workflows used across customer deployments
•Develop evaluation frameworks that measure model performance across accuracy, latency, cost, reliability, and safety
•Ensure systems meet high standards for observability, reliability, security, and maintainability
•Improve development workflows, evaluation practices, and deployment strategies as our AI platform continues to evolve
Requirements
•8+ years of professional software engineering experience
•Strong proficiency in Python or TypeScript
•Experience building and deploying LLM-powered applications or AI agents in production
•Experience with modern LLM tooling such as LangChain, LlamaIndex, Guardrails, MCP, or agent frameworks
•Experience implementing RAG pipelines, tool use, or multi-step AI workflows
•Strong understanding of AI system evaluation, debugging, and observability
•Experience building reliable production systems with modern DevOps practices
Nice to Have
•Experience deploying AI systems in enterprise environments
•Experience working across cloud platforms (AWS, GCP, or Azure)
•Experience with agent architectures and long-horizon task execution
•Familiarity with responsible AI practices, including auditability and governance
Benefits
•Competitive salary, meaningful equity, and a comprehensive benefits package
•Workplace Pension Scheme with employer contributions
•Private Medical Insurance (PMI) offered
•Flexible Time Off + Holidays
•Lunch provided on office days
•Access to state-of-the-art models, generous usage of modern AI tools, and real-world business problems
•Ownership of high-impact projects across top enterprises
•A mission-driven, fast-moving culture that prizes curiosity, pragmatism, and excellence
