Forward Deployed Engineer Financial Services

AI research and deployment company building and deploying frontier AI products, including ChatGPT, Codex, and its API platform.

Recently funded151 current maintainers88 active leads20 new active leads99 lead step-downs12 early lead departures
San Francisco, United States
About OpenAI

OpenAI’s mission is to ensure artificial general intelligence benefits all of humanity. It consists of the nonprofit OpenAI Foundation and OpenAI Group, a public benefit corporation governed by the Foundation.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will lead end-to-end deployments of production AI systems in financial-services environments. You will translate workflows and regulatory requirements into system requirements, integrations, evaluations, launch controls, and delivery plans. You will build reliable systems, manage delivery trade-offs, and turn deployment learnings into reusable architectures, tools, and playbooks.

Requirements

  • 5+ years of software engineering, ML engineering, or technical deployment experience with customer-facing ownership in financial services or regulated industries
  • Experience owning complex AI or data-driven systems through production adoption
  • Experience with financial workflows such as research, trading, risk, compliance, underwriting, operations, or investment processes
  • Production-grade backend and frontend coding experience using Python, JavaScript, or comparable stacks
  • Experience deploying LLM or generative-model systems
  • Knowledge of model evaluation and guardrails

Responsibilities

  • Design and ship production AI systems, including integrations, data flows, reliability, observability, and on-call readiness
  • Lead discovery and scoping from pre-sales through post-production
  • Define and enforce launch criteria, controls, audit artifacts, benchmarks, and acceptance thresholds
  • Build in sensitive data environments with access controls, data lineage, explainability, and failure-mode considerations
  • Run evaluation loops against financial benchmarks
  • Own delivery across multiple workstreams
  • Distill deployment learnings into reusable architectures, playbooks, and tooling
  • Surface field feedback that informs model behavior and product capabilities

Benefits

  • Equity
  • Medical, dental, and vision insurance
  • Employer contributions to Health Savings Accounts
  • Pre-tax Health FSA, Dependent Care FSA, and commuter accounts
  • 401(k) retirement plan with employer match
  • Paid parental, medical, and caregiver leave
  • Flexible PTO or up to 15 days of annual PTO, depending on exemption status
  • Paid company holidays, office closures, and sick or safe time
  • Mental health and wellness support
  • Employer-paid basic life and disability coverage
  • Daily office meals and eligible meal-delivery credits
  • Relocation support for eligible employees
  • Charitable donation matching and wellness stipends may be provided