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About Distyl AI
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 research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.
Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.
What We’re Looking For
We’re opening an office in London, UK and looking for AI Engineers to design and deploy production-grade AI systems powered by LLMs.
At Distyl, AI Engineers work directly with Fortune 500 companies to transform complex workflows using cutting-edge AI. You’ll build and ship real-world AI applications — from intelligent agents to full-stack AI products — and see them operate at scale in mission-critical environments.
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This role is highly hands-on. You’ll collaborate closely with customers, define system architectures, and build reliable, high-impact AI systems from prototype to production. Engineers at Distyl also help shape technical direction across major customer engagements, guiding enterprise teams through AI adoption and deployment.
Key Responsibilities
- Build Production AI Systems: Design, develop, and deploy robust AI applications using LLMs, including prompt engineering, agent workflows, tool use, and full-stack AI products
- Work Directly with Customers: Partner closely with enterprise stakeholders to understand complex problems and translate them into impactful AI solutions
- Lead System Architecture: Design scalable architectures for production AI systems, balancing performance, reliability, cost, and maintainability
- Develop Our Internal Platform: Contribute to Distillery, our internal LLM application platform, by building reusable infrastructure, tools, and workflows used across customer deployments
- Evaluate AI Systems Rigorously: Develop evaluation frameworks that measure model performance across accuracy, latency, cost, reliability, and safety
- Ship Production-Grade Systems: Ensure systems meet high standards for observability, reliability, security, and maintainability
- Raise the Engineering Bar: Improve development workflows, evaluation practices, and deployment strategies as our AI platform continues to evolve
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Who You Are
- 3+ 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
- Experience deploying AI systems in enterprise environments is a plus
- Experience working across cloud platforms (AWS, GCP, or Azure) is a plus
- Experience with agent architectures and long-horizon task execution is a plus
- Familiarity with responsible AI practices, including auditability and governance is a plus
What We Offer
- Competitive salary, meaningful equity, and a comprehensive benefits package
- Private medical, dental, and vision cover for you and your family
- Generous holiday allowance
- 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
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