ironquill.tech/board

$ cat jobs/staff-ai-engineer-algo1-dfbf54358f4d.json

Staff AI Engineer

Algo1·UK·London·senior
restmlllm
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About algo1 We’re a VC-backed stealth-mode company building behavioural AI solutions for the retail industry. Our platform is designed from the ground up — no legacy, no patchwork systems — just a clean slate and a clear vision. Our mission is to bring the intelligence of modern machine learning directly to the in-store shopping experience. The Role You will be an expert in agentic development familiar with both the latest advancements in models as well as the agentic toolchain and best practices. You will work closely with product, design, mobile, and machine learning team members to design & build agents that drive everything from user experience to platform automation and efficiency. Alongside product development, you will bring your expertise to enable the rest of the company to deliver faster and more effectively, whilst maintaining quality, using the latest agentic approaches and tools. What You Will Own - Defining and implementing complex, high-impact agentic AI platform solutions. - Driving best practices and enablement for agentic development across the engineering organization. - Establishing and maintaining robust evaluation (Evals) strategies for LLM agents, focusing on performance, latency, quality, and explainability. - Keeping up with the latest developments in models (Frontier Labs and Open Source) as well as agent development toolchains and best practices. - Deployment, scaling, monitoring, and cost-efficiency of agentic applications. Essential Qualifications - Deep understanding and hands-on experience with modern agentic development frameworks (e.g. Pydantic AI). - Familiarity with designing and implementing complex, multi-step agentic workflows and planning/reasoning capabilities. - Proven ability to design and implement robust evaluation (Evals) strategies for large language model (LLM) agents, including metrics for performance, latency, and quality. - Expertise in advanced context management techniques, including retrieval-augmented generation

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