Staff Software Engineer - Customer Facing Applied AI

Remote · USD 158,000-248,000 · 6+ years experience · Remote · Posted Sep 23, 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 a Staff Applied AI Engineer, you'll set the technical direction for the team's AI work: how we build agents, how we evaluate them, and how we take a capability from client-specific prototype to general product.
You'll take the hardest client engagements yourself, defining new problem domains and making high-stakes calls on what's production-ready.

Set the technical direction for AI engineering across the team: agent architecture patterns, evaluation methodology, deployment and monitoring strategies
Design the AI platform layer, including the shared agent frameworks, tool integrations, and evaluation infrastructure the team builds on
Work directly with clients on the most complex engagements: identifying new problem domains, designing AI capabilities for workflows that have never been automated, and ensuring production quality
Make high-judgment calls on AI readiness: deciding what is production-worthy and what is not, balancing speed with reliability in a domain where the stakes are real
Drive the handoff from prototype to product, working with core engineering teams to generalize client-specific capabilities for all customers
Lead production quality for AI systems: designing observability, establishing SLOs, and building the operational practices that keep AI reliable
Mentor and grow AI and full stack engineers, setting the technical and cultural bar for a new team
Shape product direction by translating what you learn from client engagements into roadmap priorities

6+ years of professional software engineering experience
Professional experience with Python (the team's primary language)
Deep experience building and operating AI/LLM-powered systems in production: agent architectures, multi-model orchestration, evaluation at scale
Track record of designing technical systems that other engineers build on
Experience with AI-assisted development tools (Claude Code, Codex, or similar)
Repeatedly taken products or capabilities from zero to one
Experience working directly with customers or external stakeholders to scope and deliver technical work
Strong judgment in ambiguous, high-stakes environments
Ability to lead technical direction without formal authority
BS/MS in Computer Science, Mathematics, or another quantitative field, or equivalent experience

Experience designing multi-service AI platform architectures (model serving, agent orchestration, evaluation infrastructure)
Experience with additional backend languages (Java is valuable in our environment)
Financial services domain knowledge (portfolios, trading, document management, regulatory workflows)
Experience with production observability and SaaS operational excellence at scale
Background in developer experience or internal platform work, building tools that change how engineering teams operate