Product/ AI Engineer

• Design, build, and improve LLM-powered features that create real value for users
• Work on multi-agent architectures, orchestration, and context management in the service of real user goals
• Build evaluation and quality systems for AI features
• Make model selection, cost, and latency trade-offs for production AI systems
• Leverage user interaction data to inform and improve AI-powered features - from exploratory analysis to production pipelines
• Explore emerging AI capabilities and assess where they add real value versus where simpler solutions win
• Act as a central figure of applied AI expertise within the team and the broader engineering organization
• Stay current with a fast-moving field and bring what you learn back to the team

Who you are

You have genuine enthusiasm for building AI-driven products and have shipped LLM-powered work into live environments, where user behavior, cost, latency, and failure modes were part of the job. Your background might be in software engineering, data science, ML engineering, or something else entirely – what matters is that you combine solid judgment on LLMs and data with a product-centric approach and ship product experiences that users value. You’re comfortable navigating uncertainty in a rapidly developing space, and you have a track record of tackling complex technical challenges. We’re especially interested in LLM work that reached production or sustained real use – commercial products, internal platforms with serious adoption, or open-source with a clear quality bar – and we’re open to other paths if you can show depth (what you owned, how you measured quality, what failed in the wild). You think about what to build as well as how to build it. You communicate clearly, simplify complex technical concepts, and share ownership of outcomes with the rest of the team. You're comfortable working across team boundaries - liaising with other product teams, thinking about broader architectural needs, and representing AI expertise in cross-team discussions. We don’t optimize for a specific number of years on a CV – careers aren’t linear. What we do need is seniority in the type and depth of experience. With that said, this is not an entry-level role – we’re hiring someone who can contribute at a senior level from early on.