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Addepar is a global data and AI platform serving 1,500+ firms managing nearly $10 trillion in assets across 60 countries. The Applied AI team works embedded with strategic clients to identify where AI can transform their workflows, then builds those capabilities from prototype through production.
In this role, you'll own the full lifecycle of AI-powered agent systems: understanding client problems deeply, prototyping quickly, rigorously evaluating performance, and shipping to production. You'll design and implement LLM integrations (prompt engineering, function calling, structured outputs, RAG workflows), define evaluation criteria for ambiguous AI correctness, work directly with clients to validate behavior, and partner with core engineering teams to generalize solutions into product features. You'll also contribute to shared AI infrastructure and monitor production systems for reliability, cost, and performance.
The role requires occasional work outside standard business hours to accommodate client time zones and up to 15% travel to client sites for multi-day engagements. Visa sponsorship is not available; you must have the right to work in the UK from day one.
You'll be part of a new team shaping what ships next. The work emphasizes speed, client feedback loops, and seeing projects through from zero to one—not just executing specifications.
REQUIREMENTS:
- Prior professional software engineering experience
- Professional experience with Python (primary team language)
- Experience working with LLM APIs (Claude, GPT, or similar) including function calling and structured outputs
- Comfort with SQL for data exploration and building data-grounded AI workflows
- Experience with AI-assisted development tools (Claude Code, Codex, or similar)
- Demonstrated ability to build something from zero to one; drawn to figuring out what to build, not just building what's specified
- Bias for action: ship quickly, learn from feedback, iterate
- See projects through from prototype to production with focus on client experience
- BS/MS in Computer Science, Mathematics, or another quantitative field, or equivalent experience
NICE TO HAVE:
- Experience building agentic systems (multi-step tool use, agent orchestration, durable workflows)
- Additional backend languages (Java valuable in this environment)
- Familiarity with financial data (portfolios, transactions, securities, accounting)
- Cloud infrastructure experience (AWS) and container-based deployments
- Experience with evaluation frameworks or methodologies for AI system quality
