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Product Pulse, a private market data platform, seeks a Senior Backend Engineer in London or remote England to build production backend services in Python and drive AI-enabled features for professional investors.
You will own the orchestration layer for agentic AI capabilities, work with PostgreSQL and ClickHouse at scale, and influence architecture while mentoring a growing team in a fast-paced startup environment.
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 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
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
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
Languages: English (fluent, working language of the team)