The opportunity
OpenAI’s Forward Deployed Engineering team partners with banks, asset managers, insurers, and private capital firms to deploy production-grade AI systems in high-stakes financial environments. We operate at the intersection of customer delivery and core platform development,…
What you'll do
Design and ship production AI systems around models, owning integrations,: data flows, reliability, observability, and on-call readiness across financial workflows.
Lead discovery and scoping from pre-sales through post-production,: translating ambiguous business problems into hypothesis-driven problem framing, system requirements, and delivery plans with measurable outcomes.
Define and enforce launch criteria for regulated financial environments,: including controls, audit artifacts, evaluation benchmarks, and acceptance thresholds tied to risk and performance.
Build in sensitive data environments where access controls, data lineage,: explainability, and failure modes shape architecture and operating procedures.
Run evaluation loops that measure model and system quality against: workflow-specific financial benchmarks (e.g., accuracy, latency, coverage, false positives) and use results to drive iteration.
Own delivery state across multiple workstreams, making trade-offs between: scope, speed, and quality to protect production outcomes.
What they're looking for
- Distill deployment learnings into hardened primitives, reference: architectures, playbooks, and tooling that scale across financial institutions.
- Surface field feedback that informs model behavior, product capabilities, and: platform gaps in real-world financial use cases.
- Bring 5+ years of software engineering, ML engineering, or technical: deployment experience with customer-facing ownership in financial services or adjacent regulated industries.
- Have owned complex AI or data-driven systems end-to-end, from scoping through: production adoption, in environments where errors carry real financial or regulatory consequences.
