Candidates with hands-on AI development experience and a client-facing mindset will find this role's emphasis on building agentic systems and collaborating with strategic clients highly aligned with their background.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Addepar via Greenhouse
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 an Applied AI Engineer, you'll build agentic systems from idea through production. The work starts with understanding the problem well enough to know what to build, then moves fast through prototyping and iteration. You'll design agent behavior, wire up tool integrations, tune evaluations until the AI actually works in practice. You'll sit close to the people who use what you build, and that feedback loop is how both the product and your skills grow fast. The team is new. Your work shapes what we ship.
This role may require occasional work outside standard business hours to accommodate client time zones and up to 15% travel to client sites, including occasional overnight and multi-day engagements.
What You'll Do
Build AI-powered agents and tools end-to-end: identify the problem with clients and domain experts, prototype quickly, evaluate rigorously, and ship to production
Design and implement LLM integrations including prompt engineering, function calling, structured outputs, and retrieval-augmented workflows
Define evaluation criteria and build test harnesses for AI systems where correctness is ambiguous and domain-specific
Work directly with clients to understand their workflows, validate AI behavior, and iterate toward production quality
Partner with core engineering teams to generalize client-specific work into product features
Contribute to shared AI infrastructure (agent frameworks, tool integrations, deployment pipelines)
Monitor and maintain production AI systems with attention to reliability, cost, and performance
Who You Are
Extensive professional software engineering experience
Professional experience with Python (the team's primary language)
Experience working 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)
You've built something from zero to one. You're drawn to figuring out what to build, not just building what's specified.
A bias for action. You ship quickly, learn from feedback, and iterate.
You see projects through from prototype to production and care about what the client experiences, not what the code does
BS/MS in Computer Science, Mathematics, or another quantitative field, or equivalent experience
Nice to Have
Experience building agentic systems (multi-step tool use, agent orchestration, durable workflows)
Experience with additional backend languages (Java is valuable in our environment)
Familiarity with financial data (portfolios, transactions, securities, accounting)
Exposure to cloud infrastructure (AWS) and container-based deployments
Experience with evaluation frameworks or methodologies for measuring AI system quality
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.
In addition to our core values, 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.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
PHISHING SCAM WARNING: Addepar is among several companies recently made aware of a phishing scam involving con artists posing as hiring managers recruiting via email, text and social media. The imposters are creating misleading email accounts, conducting remote “interviews,” and making fake job offers in order to collect personal and financial information from unsuspecting individuals. Please be aware that no job offers will be made from Addepar without a formal interview process. Additionally, Addepar will not ask you to purchase equipment or supplies as part of your onboarding process. If you have any questions, please reach out to ta-operations@addepar.com.
Source: Addepar careers (Greenhouse)