Software Engineer - Customer Facing Applied AI

Addepar
United States
Remote

Who this role is best for

Customer-facing applied AI engineers with Python and LLM integration experience will find this role's emphasis on agentic systems and client collaboration rewarding.

Best fit for

  • Candidates with Python expertise and experience in LLM function calling and structured outputs
    — “Professional experience with Python (the team's primary language)”
  • Individuals who have built products from zero to one and thrive in client-facing roles
    — “You've built something from zero to one. You're drawn to figuring out what to build”
  • Engineers comfortable with SQL and data-grounded AI workflows for financial clients
    — “Comfort with SQL for data exploration and building data-grounded AI workflows”

Things to consider

  • The role requires legal authorization to work in the U.S. without visa sponsorship
    — “Applicants must be legally authorized to work in the United States”
  • Occasional travel and work outside standard business hours may be necessary
    — “This role may require occasional work outside standard business hours”

How to stand out

  • Highlight end-to-end AI agent development projects in your resume and interview examples
    — “Build AI-powered agents and tools end-to-end”
  • Emphasize experience with client collaboration and iterative feedback loops
    — “Work directly with clients to understand their workflows, validate AI behavior”
  • Showcase your ability to generalize client work into product features
    — “Partner with core engineering teams to generalize client-specific work into product features”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Build AI-powered agents and tools end-to-end
  • 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
Typical background
2+ years of professional software engineering experience

Skills & requirements

Required

Professional Software Engineering ExperienceExperience With PythonExperience Working With LLM Apis (claude, GPT, Or Similar)Comfort With SQL For Data Exploration And Building Data-grounded AI WorkflowsExperience With Ai-assisted Development Tools (claude Code, Codex, Or Similar)

Preferred

Restaurant Operations ExperienceExperience Using Salesforce To Keep Track Of Sales ActivitiesSandler Sales Training

Stack & domain

PythonLLM ApisSQLAi-assisted Development ToolsLLM IntegrationsPrompt EngineeringFunction CallingStructured OutputsRetrieval-augmented WorkflowsEvaluation CriteriaTest HarnessesAI SystemsAgent BehaviorTool IntegrationsDeployment PipelinesProduction AI SystemsReliabilityCostPerformanceCommunicationTeamworkProblem-solvingAdaptabilityBias For ActionAISoftware EngineeringCustomer FacingApplied AI

About the role

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.

Applicants must be legally authorized to work in the United States for any employer without requiring current or future visa sponsorship (for example, employment-based visas such as H-1B, F-1/OPT, or similar), and must be authorized to begin work in the U.S. on their first day of employment.

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

2+ years of 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

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.

Base Salary Range$163,000—$203,500 USDOur 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)

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