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Salary: USD 158,000 - 248,000 / annual
Addepar is a global data and AI platform serving 1,500+ firms managing nearly $10 trillion in assets. The Applied AI team works embedded with strategic clients to identify where AI can transform their workflows, then builds and ships those capabilities as products for all customers.
As a Staff Applied AI Engineer, you will set the technical direction for the team's AI work: agent architectures, evaluation methodologies, and the process of taking client-specific prototypes to general product. You'll take on the most complex client engagements yourself, defining new problem domains and making high-stakes production-readiness decisions. You'll also build the patterns and tools that help other engineering teams across Addepar adopt AI effectively.
Key responsibilities:
- Set technical direction for AI engineering: agent architecture patterns, evaluation methodology, deployment and monitoring strategies
- Design the AI platform layer, including shared agent frameworks, tool integrations, and evaluation infrastructure
- Work directly with clients on complex engagements: identifying new problem domains, designing AI capabilities for workflows never before automated, ensuring production quality
- Make high-judgment calls on AI readiness, balancing speed with reliability in high-stakes domains
- Drive handoff from prototype to product, working with core engineering teams to generalize client-specific capabilities
- Lead production quality for AI systems: design observability, establish SLOs, build operational practices for reliability
- Mentor and grow AI and full-stack engineers, setting technical and cultural bar for a new team
- Shape product direction by translating client engagement learnings into roadmap priorities
Requirements:
- 6+ years of professional software engineering experience
- Professional experience with Python (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; think in platforms and patterns, not individual features
- Experience with AI-assisted development tools (Claude Code, Codex, or similar)
- Demonstrated ability to take products or capabilities from zero to one; comfortable identifying the right problem and building the right system
- Experience working directly with customers or external stakeholders to scope and deliver technical work
- Strong judgment in ambiguous, high-stakes environments; know when to move fast and when to be careful
- Ability to lead technical direction without formal authority; influence across teams through quality of thinking and work
- Excellent communication skills; credible with clients, engineers, and executive leadership
- BS/MS in Computer Science, Mathematics, or another quantitative field, or equivalent experience
Nice to have:
- Experience designing multi-service AI platform architectures (model serving, agent orchestration, evaluation infrastructure)
- Experience with additional backend languages (Java valuable in their 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
