About Kota
Kota is reimagining insurance and retirement benefits for the modern workforce. Through our two flagship products, Kota Platform, the first fully integrated benefits platform, and Kota Embed, our embedded insurance solution, we are making benefits more accessible, valued, and global.
Today, we power benefits for tens of thousands of employees at Europe's most forward-thinking companies, including Carwow, Tines, Zoe, and Remote. Founded in 2022, we have raised more than 20M EUR from leading investors like EQT Ventures, Eurazeo, Northzone, and Frontline, along with founders and executives from Workday, Remote, Personio, OpenAI, and more.
The Role
This is a new role on Kota's AI pod, sitting within the Platform team. We are building out a generative AI capability from the ground up, the first of its kind at Kota, and we need a senior engineer who can help us do that with rigour and taste.
You will work directly with the AI Product Lead to design, build, and evaluate agent systems that help Kota's employer admins and employees make better use of their benefits data. This is early-stage, high-ownership work. You will be making real architectural decisions, not executing a predefined playbook.
What You'll Do
- Design and ship AI agent systems end to end, from early experiments through to production, owning the data access layer, retrieval strategy, and integration with Kota's existing infrastructure including Metabase and internal APIs
- Build and own the evaluation framework from scratch, including golden datasets, regression harnesses, and the ability to distinguish retrieval from generation failures; think adversarially about prompt injection, data boundary violations, and silent failure modes in a regulated context
- Set the technical direction for AI at Kota, with a seat at the table on agent architecture, and where AI creates the most leverage across the product
- Work across the pod and Platform team to surface new AI opportunities, collaborate with the AI Product Lead, and raise the bar on engineering practice through peer review and documentation
- Pick up slack and expand the role, this is an early pod with room to shape it; the remit will grow with you
What We're Looking For
Essential
- 5+ years of software engineering experience, with at least 2 years working directly on LLM or AI agent systems in production
- Strong grasp of agent architecture, including context management, tool use, retrieval strategies, and prompt design, and the ability to make and defend tradeoffs between them
- Experience building evaluation frameworks, not just using them: golden datasets, regression testing, and retrieval vs. generation failure analysis
- Comfort working across the stack
- Clear written communication; you can explain a technical decision to a non-technical stakeholder without losing precision
Strong plus
- Background in fintech, payroll, HR tech, or benefits; you understand why data freshness and auditability matter in regulated contexts
- Experience with AWS, .NET, Azure, or the broader Microsoft ecosystem (our backend stack)
- Experience generating synthetic evaluation data to bootstrap eval coverage before real usage data is available