Principal AI Engineer

About the role

This Principal AI Engineer role at Figure focuses on building and maintaining AI systems that directly contribute to business outcomes within the capital markets. The work involves designing and implementing AI solutions using various approaches, including generative AI, classical machine learning, and optimization. A key responsibility is to ensure these models perform effectively and contribute to high-quality decision-making.

The position requires developing robust backend services and APIs that reliably expose model capabilities in a production environment. This includes creating real-time and batch AI services that integrate with core business workflows, and taking ownership of their performance, reliability, and maintainability. The engineer will also improve evaluation, monitoring, and operational feedback loops for deployed systems to ensure continuous improvement.

Beyond model development and service deployment, the role involves building reliable data and feature pipelines from various sources like on-chain events and transaction systems. This ensures data quality and operational robustness throughout the AI system lifecycle. The Principal AI Engineer will also contribute to shared AI infrastructure, enhancing observability, autoscaling, and deployment patterns, and providing technical leadership to translate business priorities into durable technical systems.

The base compensation for this role ranges from $176,000.00 to $264,000 per year, with an additional 25% annual bonus target and company equity.

Skills that matter here

• Python: This role requires strong Python skills for designing and building clean, maintainable production services.
• SQL: The position demands strong data skills, including SQL and data modeling, for building reliable pipelines.
• ML: The engineer will design and build AI systems, applying various machine learning and AI approaches to solve business problems.
• AI: The core of this role involves developing and operating production AI systems that leverage blockchain technology for capital markets.
• Terraform: The role involves supporting infrastructure managed through Terraform or similar infrastructure as code tools.
• GCP: Experience with at least one major cloud platform like GCP is required for building and operating AI systems.

Who this role suits

• A person who has over eight years of experience building and deploying production machine learning or AI systems.
• Someone who possesses strong first-principles thinking and sound technical judgment, capable of translating ambiguous business problems into robust technical solutions.
• An individual who can work across the entire AI stack, from modeling and data to backend systems and infrastructure.
• A pragmatic engineer with a strong business intuition, focused on choosing the most effective solution rather than the most trendy one.

From the employer

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 and 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

Salary

• Base Compensation Range: $176,000.00 - $264,000/yr
• 25% annual bonus target, paid quarterly
• Company equity in the form of RSUs

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