Sr. Software Engineer - Customer Facing Applied AI

London · Remote · Remote · Posted Oct 9, 2026

At a glance

The Applied AI team works embedded with Addepar's strategic clients to figure out where AI can change how they work and then build those capabilities from scratch.
As an Applied AI Engineer, you'll build agentic systems from idea through production, spending time understanding a client's world, identifying what's worth building, prototyping it, proving it works, and partnering with core engineering teams to ship it as product.

Build AI-powered agents and tools end-to-end: identify the problem with clients and domain experts, prototype quickly, evaluate rigorously, and ship to production
Design and implement LLM integrations including prompt engineering, function calling, structured outputs, and retrieval-augmented workflows
Define evaluation criteria and build test harnesses for AI systems where correctness is ambiguous and domain-specific
Work directly with clients to understand their workflows, validate AI behavior, and iterate toward production quality
Partner with core engineering teams to generalize client-specific work into product features
Contribute to shared AI infrastructure (agent frameworks, tool integrations, deployment pipelines)
Monitor and maintain production AI systems with attention to reliability, cost, and performance

Extensive professional software engineering experience
Professional experience with Python
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)
BS/MS in Computer Science, Mathematics, or another quantitative field, or equivalent experience

Experience building agentic systems (multi-step tool use, agent orchestration, durable workflows)
Experience with additional backend languages (Java is valuable in our environment)
Familiarity with financial data (portfolios, transactions, securities, accounting)
Exposure to cloud infrastructure (AWS) and container-based deployments
Experience with evaluation frameworks or methodologies for measuring AI system quality

This role may require occasional work outside standard business hours to accommodate client time zones
Up to 15% travel to client sites, including occasional overnight and multi-day engagements