Staff Software Engineer - Customer Facing Applied AI

Engg; United States; Remote; USD 158,000 - 248,000; Full time

Job summary

Addepar is seeking a Staff Applied AI Engineer to set the technical direction for AI work, build production-grade AI capabilities, and partner with core engineering to ship solutions for clients. You’ll own architecture, evaluation, and patterns for scalable AI systems.

You will directly engage with clients on complex engagements, balance speed and reliability, and mentor other engineers while shaping product roadmaps and internal platforms.

Qualifications

• 6+ years of professional software engineering experience.
• 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.
• Experience with AI-assisted development tools (Claude Code, Codex, or similar).
• Experience taking products from zero to one and delivering to customers.
• Experience working directly with customers or external stakeholders.
• Strong judgment in ambiguous, high-stakes environments.
• Ability to lead technical direction without formal authority.

Responsibilities

• Set the technical direction for AI engineering across the team and define architecture patterns.
• Design the AI platform layer, including shared agent frameworks, tools, and evaluation infra.
• Work directly with clients on complex engagements to design AI capabilities for new workflows.
• Determine production readiness and balance speed with reliability.
• Drive handoffs from prototype to product and generalize client-specific capabilities.
• Lead production quality for AI systems with observability and SLOs.
• Mentor and grow AI and full-stack engineers; set technical and cultural bar.
• Translate client learnings into roadmap priorities.

Skills

Python

AI/LLM systems

Agent architectures

Multi-model orchestration

Production readiness

Customer engagement

Leadership

Communication

Problem solving

Education

BS/MS in Computer Science or Mathematics

Job description

Who We Are

Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore.

The Role

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. You'll spend time understanding a client's world, identify what's worth building, prototype it, prove it works, and then partner with core engineering teams to ship it as product for all customers. 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. You'll also build the patterns and tools that help other engineering teams across Addepar adopt AI effectively. The problems are largely unsolved. The team is new. The right person sees that as the opportunity.

What You'll Do

• 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

Who You Are

• 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. You think in platforms and patterns, not individual features
• Experience with AI-assisted development tools (Claude Code, Codex, or similar)
• You've repeatedly taken products or capabilities from zero to one. You're as comfortable identifying the right problem as you are 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. You know when to move fast and when to be careful
• Ability to lead technical direction without formal authority. You influence across teams through the quality of your thinking and your 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 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

Compensation

Base Salary Range $158,000 - $248,000 USD

Addepar takes a market-based approach to pay. A successful candidate's starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions. The range displayed on each job posting reflects the minimum and maximum target base salary for this role within the United States. Compensation for this role includes base salary + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Additionally, these ranges reflect the base salary only, and do not include bonus, equity, or benefits.

Our Values

• Act Like an Owner - Think and operate with intention, purpose and care. Own outcomes.
• Build Together - Collaborate to unlock the best solutions. Deliver lasting value.
• Champion Our Clients - Exceed client expectations. Our clients’ success is our success.
• Drive Innovation - Be bold and unconstrained in problem solving. Transform the industry.
• Embrace Learning - Engage our community to broaden our perspective. Bring a growth mindset.

Equal Opportunity Employment

Addepar is proud to be an equal opportunity employer. We seek to bring together diverse ideas, experiences, skill sets, perspectives, backgrounds and identities to drive innovative solutions. We commit to promoting a welcoming environment where inclusion and belonging are held as a shared responsibility.