About Figure
Figure (NASDAQ: FIGR) is transforming capital markets through blockchain. We’re proving that blockchain isn’t just theory - it’s powering real products used by hundreds of thousands of consumers and institutions.
By combining blockchain’s transparency and efficiency with AI-driven automation, we’ve reimagined how loans are originated, funded, and traded in secondary markets. From faster processing times to lower costs and reduced bias, our technology is helping borrowers, investors, and financial institutions achieve better outcomes.
Together with our 170+ partners, we’ve originated over $22 billion in home equity loans (HELOCs) on our blockchain-native platform, making Figure the largest non-bank provider of home equity financing in the U.S. Figure’s ecosystem also includes YLDS, an SEC-registered yield-bearing stablecoin that operates as a tokenized money market fund, and several other products and platforms that are reshaping consumer finance and capital markets.
We’re proud to be recognized as one of Forbes’ Most Innovative Fintech Startups in 2025 and Fast Company’s Most Innovative Companies in Finance and Personal Finance.
About The Role
Figure’s AI Engineering team builds and operates production AI systems that directly support our capital markets platform. We are an engineering-first team focused on deploying practical, high-impact systems that improve risk, liquidity, and operational efficiency.
We’re hiring a Principal AI Engineer to work across modeling and production systems. This is a deeply hands-on role for someone who can move from ambiguous business problems to deployed solutions: designing models and decision systems, building the services around them, and ensuring they operate reliably in production.
This is not a pure research role, and it is not a prompt engineering role. You will be expected to work directly on model behavior and evaluation, while also building the data, backend, and infrastructure needed to make those systems production-grade.
You’ll partner closely with AI leadership on technical direction and execution. This role will influence architecture, roadmap, and implementation across a growing portfolio of AI systems.
What You'll Do
You’ll work across the AI stack, with particular focus on building systems that directly impact business outcomes.
Modeling & Decision Systems
- Design and build AI systems using the right approach for the problem, including generative AI, classical ML, optimization, or deterministic logic
- Work directly on model behavior, evaluation, and decision quality
- Apply first-principles thinking to determine where LLMs provide leverage and where other approaches are better suited
Production AI Services
- Build backend services and APIs that expose model capabilities reliably in production
- Design real-time and batch AI services that integrate into core business workflows
- Own service performance, reliability, and maintainability in production
- Improve evaluation, monitoring, and operational feedback loops for deployed systems
Data & Feature Pipelines
- Build reliable pipelines from on-chain events, warehouse data, and transaction systems
- Design scalable feature and data workflows that support production models and decision systems
- Ensure data quality, lineage, and operational robustness across the lifecycle of AI systems
AI Infrastructure & Platform
- Contribute to shared infrastructure for model and AI service serving
- Improve observability, autoscaling, reliability, and deployment patterns across AI systems
- Help build reusable tooling, patterns, and platform capabilities that make the broader team more effective
- Support infrastructure managed through Terraform, CI/CD pipelines, containerized services, and cloud-native systems
Technical Leadership
- Partner with leadership to translate business priorities into durable technical systems
- Help shape architecture and engineering standards across the team
- Raise the technical bar through sound judgment, strong design, and pragmatic execution
- Contribute as a high-agency technical leader without losing hands-on depth
What We Look For
Must-Haves
- 8+ years of experience building production ML, AI, or data-intensive software systems
- Strong Python skills, with the ability to design clean, maintainable production services
- Strong data skills, including SQL, data modeling, and experience building reliable pipelines
- Experience building and operating real-time serving systems, including APIs, model serving, autoscaling, and production monitoring
- Experience working across multiple layers of the stack, including modeling, data, backend systems, and infrastructure
- Experience with at least one major cloud platform (GCP, AWS, or Azure)
- Experience with containerization and production deployment workflows
- Experience with infrastructure as code (Terraform or similar) and CI/CD systems (GitHub Actions or similar)
Strong Signals
- Deep hands-on experience building production AI or ML systems end to end
- Ability to work directly on model behavior a
- nd evaluation, not just surrounding infrastructure
- Strong first-principles thinking and sound technical judgment
- Ability to translate ambiguous business problems into robust technical systems
- Strong business intuition and a pragmatic instinct for choosing the right solution rather than the most fashionable one
- Track record of building reusable systems, patterns, and tooling rather than one-off features
- Experience in regulated environments such as fintech, healthcare, or similar domains
Nice-to-Haves
- Experience with Kubernetes or other container orchestration systems
- Experience with distributed compute frameworks such as Ray or Spark
- Experience building AI or ML platform components such as feature stores, model registries, serving layers, or observability systems
- Experience with LLM systems and orchestration frameworks
- Familiarity with LLM ops, including gateway proxies, token management, and caching
- Background in capital markets, lending, or fintech
- Blockchain or on-chain data experience
What We’re Not Looking For
- Pure research candidates who are not interested in production ownership
- Pure data scientists who rely on others to productionize their work
- Engineers who want to work only on infrastructure and not directly on models or decision systems
- Candidates who approach AI as prompt engineering alone, without a strong grounding in systems, data, and modeling
- Engineers who specialize narrowly in a single layer of the stack and are uncomfortable operating across disciplines
Why This Role Is Unique
- Figure has a structural data advantage that very few fintech companies have: on-chain ground truth for asset state, ownership, settlement, and servicing
- You’ll be building AI systems on canonical financial data, not reconciled approximations
- You’ll join a high-impact AI function with executive sponsorship and a clear roadmap
- You’ll work on systems already driving real business outcomes, not speculative side projects
- You’ll operate across modeling, backend systems, infrastructure, and data in a role with unusual breadth and real ownership
- You’ll have the opportunity to influence core technical direction while remaining deeply hands-on
- Figure is a public company (NASDAQ: FIGR) with approximately $507M in annual revenue and $134M in net income (FY 2025, +49% YoY revenue growth)
Salary
- Base Compensation Range: $176,000.00 - $264,000/yr
- 25% annual bonus target, paid quarterly
- Company equity in the form of RSUs
This is the compensation range for the role in the United States. Actual compensation may vary based on a candidate’s experience, skills, location, internal equity, and evolving business needs. While most offers are generally made within the middle of the range, final compensation is determined based on the factors above.
Benefits
- Comprehensive medical, dental, and vision coverage, with 100% employer-paid premiums for employees and their dependents on select plans
Company HSA, FSA, Dependent Care FSA, 401(k), and commuter benefits
Employer-paid life and disability insurance
11 observed holidays and PTO plan
Up to 12 weeks of paid family leave
Continuing education reimbursement
Depending on your residential location certain laws might regulate the way Figure manages applicant data. California Residents, please review our California Employee and General Workforce Privacy Notice for further information. By submitting your application, you are agreeing and acknowledging that you have read and understand the above notice.
Figure will not sponsor work visas for this position. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.
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