AI Engineer
Posted 19hrs ago
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Job Description
Associate AI Engineer operating conversational AI systems for Figure, a blockchain-powered lending fintech. Building Python services, APIs, evaluations, and production AI integrations.
Responsibilities:
- Improve AI-powered chat and voice services supporting customer-service and lending workflows
- Build and maintain agent workflows, API-integrated tools, guardrails, retrieval rules, and escalation paths
- Review workflows for logic errors, unsafe behavior, routing conflicts, and unnecessary model context
- Establish disciplined development, staging, testing, review, and production-release practices
- Partner with domain experts who own customer experience, policies, and lending operations
- Determine whether problems are best solved through workflow logic, deterministic code, retrieval, an LLM, or a product change
- Build automated tests and simulations for conversational workflows
- Define and measure containment, escalation, answer quality, task completion, and customer-impact metrics
- Develop tagging, monitoring, and quality-assurance systems for production conversations
- Analyze failures and turn production evidence into prioritized improvements
- Build pipelines that make conversational data available to analytics and reporting systems
- Design controlled experiments and incremental rollouts that measure business outcomes
- Build Python services and APIs that expose AI capabilities
- Develop integrations between AI systems and Figure's internal services
- Build data and evaluation pipelines using Python and SQL
- Contribute to internal tools and user interfaces
- Learn and apply Figure's deployment, monitoring, containerization, and CI/CD practices
- Gradually own increasingly substantial production engineering projects
- Inventory and review conversational tools that access internal or third-party APIs
- Ensure sensitive operations use deterministic validation instead of unreliable model judgment
- Support appropriate handling of customer data, credentials, PII, and regulated workflows
- Maintain auditability for workflow changes and production behavior
- Escalate security, compliance, and reliability concerns using sound technical reasoning
- Within the first six months, understand Figure's conversational AI workflows and integrations, strengthen testing/monitoring/security/release discipline, resolve workflow reliability issues, produce performance reporting, ship at least one production integration/service/internal tool, and demonstrate increasing independence across Python, APIs, data, evaluation, and deployment
- Over time, shift toward broader full-stack AI engineering as conversational systems become better governed and operational responsibilities become more distributed
Requirements:
- Strong programming fundamentals and practical Python experience
- Working knowledge of SQL and structured data analysis
- Ability to break ambiguous problems into testable components
- Comfort reading unfamiliar code and tracing system behavior
- Strong written communication and attention to detail
- Interest in AI behavior, analytics, backend systems, and product workflows
- A habit of validating assumptions and measuring outcomes
- Ability to collaborate with engineers and nontechnical domain experts
- Desire to grow into a full-stack production AI engineer
- Experience building an API, backend service, automation, data pipeline, or internal tool
- Experience evaluating LLMs, conversational agents, or other probabilistic systems
- Knowledge of experimental design, statistics, causal inference, or applied econometrics
- Experience testing nondeterministic systems
- Familiarity with retrieval-augmented generation, agent tools, workflow engines, or model evaluation
- Ability to distinguish problems requiring deterministic logic from those suited to an LLM
- Experience translating domain or policy requirements into software behavior
- A degree or research background in economics, computer science, statistics, engineering, or another quantitative discipline is a nice-to-have
- Graduate training involving empirical research and substantial programming is a nice-to-have
- Experience with TypeScript or a modern frontend framework is a nice-to-have
- Familiarity with cloud platforms, Docker, CI/CD, or infrastructure as code is a nice-to-have
- Experience with experimentation systems, analytics platforms, or business-intelligence tools is a nice-to-have
- Experience in lending, fintech, healthcare, or another regulated environment is a nice-to-have
- Experience with customer-support or contact-center systems is a nice-to-have
- A PhD is welcome but not required
- Candidates must verify identity and eligibility to work in the United States
- Figure will not sponsor work visas for this position
Benefits:
- 25% annual bonus target, paid quarterly
- Company equity in the form of RSUs
- 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


















