Senior Backend Engineer

Senior Backend Engineer — London or England remote

London, UK
· Permanent
· Hybrid

Join a team small enough that what you build is what exists, and take agentic AI features from a founder's idea to something hundreds of investment firms rely on to make real capital decisions.

• Building and shipping production backend services and APIs in Python (FastAPI) that power the platform's AI features, used daily by professional investors
• Designing and owning the orchestration layer for agentic AI capabilities: how the system plans, calls tools, and retrieves the right data at the right time
• Working directly with PostgreSQL and Click House to enable fast, reliable data retrieval for AI-driven analysis at real scale
• Taking a feature from a founder's rough idea to something live in production within the same sprint, without layers of process in between
• Mentoring teammates and helping set engineering standards as the team grows from around seven engineers today to over thirty
• Making real calls on architecture and tooling rather than inheriting decisions frozen in place years ago
• Working closely enough with the founders that your technical judgment shapes what gets built next, not just how it gets built

• Agentic workflows and tool use sit on top of a data platform that has to stay fast and correct under real investor usage, not a demo
• Two different database workloads in the same system:
  PostgreSQL for transactional data, Click House for the columnar, analytics-heavy queries behind the AI insights
• AI coding tools (Cursor, Claude) are part of the actual day-to-day workflow, not a side experiment
• A genuinely small engineering team means no one else is quietly maintaining the parts you don't touch
• Retrieval and embeddings work that has to hold up against messy, high-stakes private market data rather than clean public datasets

• 5 to 15 years of backend engineering experience, most of it in Python, in production environments
• A track record of building and personally owning APIs or services used by real customers, not just maintaining systems someone else designed
• Time spent at a startup or scaleup (roughly 30 to 100 people), not exclusively large corporate environments
• Hands‑on experience shipping AI or LLM features to production: agentic workflows, RAG, or tool use
• Strong SQL and solid experience with PostgreSQL or an equivalent relational database
• A genuine preference for staying hands‑on and coding day to day rather than moving toward management
• Based in Europe (outside France and the Nordics); if based in London, comfortable working from the office five days a week
• Bonus: experience with columnar databases (Click House, Redshift, Snowflake) or general Dev Ops/infrastructure skills

An alternative data and private market intelligence platform, giving investors real-time data and AI-driven analysis to make faster, better-informed decisions. Used by hundreds of leading VC and PE firms across Europe and beyond. Small, fast-moving engineering team of around thirty people, still shaped day to day by its founders. Equity participation (ESOP) after six to nine months.

Languages:

English (fluent, working language of the team)