Software Engineer (Customer Facing Applied AI)

• 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
• 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

Benefits

• Equity: Stretch the idea of ownership beyond your day-to-day and take pride in being an owner in the growth of Addepar
• Global Hybrid Workforce: Whether you work remotely or on-site, you’ll have the opportunity to build and collaborate with colleagues around the world
• Flexible Time Off: Spend time traveling, celebrating with friends and family or relax on your schedule
• Benefits Packages: Competitive medical, dental and vision benefits along with a monthly wellness allowance to keep you healthy and happy
• Learning & Development Allowance: Your continued growth and development are important to us
• Dynamic Team: Strong investment in the best talent at the intersection of technology and finance- BS/MS in Computer Science, Mathematics, or another quantitative field, or equivalent experience
• Professional experience with Python (the team’s primary language)
• Prior professional software engineering experience
• Comfort with SQL for data exploration and building data-grounded AI workflows
• Experience with AI-assisted development tools (Claude Code, Codex, or similar)
• Experience working with LLM APIs (Claude, GPT, or similar) including function calling and structured outputs
• 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
• You’ve built something from zero to one. You’re drawn to figuring out what to build, not just building what’s specified
• Experience with evaluation frameworks or methodologies for measuring AI system quality
• Exposure to cloud infrastructure (AWS) and container-based deployments
• Familiarity with financial data (portfolios, transactions, securities, accounting)
• Experience with additional backend languages (Java is valuable in our environment)
• Experience building agentic systems (multi-step tool use, agent orchestration, durable workflows)