Customer-Facing Applied AI Engineer

Remote; San Francisco (CA); On-site; USD 163,000 - 204,000; Full time

Job summary

Addepar in San Francisco seeks an Applied AI Engineer to build agentic systems from idea to production, partnering with clients and core engineering to ship AI capabilities across our platform. You will design LLM integrations, prompt engineering, function calling, and retrieval-augmented workflows, and you will wire up tool integrations and evaluation harnesses to ensure AI behaves reliably.

The role requires 2+ years of software engineering, Python experience, work with LLM APIs, and a strong

Qualifications

• 2+ years of professional software engineering experience.
• Experience with Python as primary language.
• Experience 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).
• Built something from zero to one and shipped production-ready work.
• Strong bias for action: ship quickly, learn, and iterate.
• BS/MS in Computer Science, Mathematics, or related field, or equivalent experience.

Responsibilities

• Build AI-powered agents and tools end-to-end: identify client problems, prototype quickly, evaluate rigorously, and ship to production.

Skills

Python

LLM APIs

Prompt engineering

SQL

Data-grounded AI

Client collaboration

Education

BS in Computer Science or related

Tools

Claude

GPT

Codex

AWS

Job description

Addepar in San Francisco seeks an Applied AI Engineer to build agentic systems from idea to production, partnering with clients and core engineering to ship AI capabilities across our platform. You will design LLM integrations, prompt engineering, function calling, and retrieval-augmented workflows, and you will wire up tool integrations and evaluation harnesses to ensure AI behaves reliably.

The role requires 2+ years of software engineering, Python experience, work with LLM APIs, and a strong