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Senior Backend Engineer
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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.
What you'd actually work on
- 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 ClickHouse 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
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Where it gets technically interesting
- 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, ClickHouse 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
What we're looking for
- 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 (ClickHouse, Redshift, Snowflake) or general DevOps/infrastructure skills
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The company
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)
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