Staff Applied AI Engineer - Platform & Production

Addepar, Inc.; United States; Remote; USD 158,000 - 248,000; Full time

Job summary

Addepar, a global data and AI platform for investment professionals, seeks a Staff Applied AI Engineer to set technical direction, build production-grade AI capabilities, and partner with clients and core engineering teams to ship broad AI features.

You will mentor engineers, shape the AI platform's architecture, and drive reliability through observability and SLOs while influencing product direction from real client engagements.

Qualifications

• 6+ years of professional software engineering experience.
• Experience designing technical systems that scale and are used by other engineers.
• Experience working directly with customers or external stakeholders to scope and deliver technical work.

Responsibilities

• Set the technical direction for AI engineering across the team (agent architecture, evaluation, deployment).
• Design the AI platform layer with shared frameworks, tools, and evaluation infra.
• Work directly with clients on complex engagements to design AI capabilities for novel workflows.
• Decide on production readiness and balance speed with reliability.
• Lead the handoff from prototype to product and generalize client capabilities.
• Own production quality for AI systems including observability and SLOs.
• Mentor and grow AI and full stack engineers and set high technical standards.
• Translate client learnings into roadmap priorities to shape product direction.

Skills

Python

AI/LLM production

Agent architectures

Multi-model orchestration

Client engagements

Communication

Leadership

Education

BS/MS in CS, Math, or related field

Tools

Claude Code

Codex

Job description

Addepar, a global data and AI platform for investment professionals, seeks a Staff Applied AI Engineer to set technical direction, build production-grade AI capabilities, and partner with clients and core engineering teams to ship broad AI features.

You will mentor engineers, shape the AI platform's architecture, and drive reliability through observability and SLOs while influencing product direction from real client engagements.