The Role

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. You'll spend time understanding a client's world, identify what's worth building, prototype it, prove it works, and then partner with core engineering teams to ship it as product for all customers.

As an Applied AI Engineer, you'll build agentic systems from idea through production. The work starts with understanding the problem well enough to know what to build, then moves fast through prototyping and iteration. You'll design agent behavior, wire up tool integrations, tune evaluations until the AI actually works in practice. You'll sit close to the people who use what you build, and that feedback loop is how both the product and your skills grow fast. The team is new. Your work shapes what we ship.

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

What You'll Do

• 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

Who You Are

• Extensive professional software engineering experience
• Professional experience with Python (the team's primary 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)
• You've built something from zero to one. You're drawn to figuring out what to build, not just building what's specified.
• A bias for action. You ship quickly, learn from feedback, and iterate.
• You see projects through from prototype to production and care about what the client experiences, not what the code does
• 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)
• 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