
Forward Deployed Engineer (FDE), Financial Services- NYC
Primary stack
Job description
About the Position
Forward Deployed Engineer (FDE), Financial Services- NYC
New York City
About the Team
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, embedding deeply with customers to translate frontier model capabilities into reliable, auditable systems that create measurable business impact. Our work turns early deployments into repeatable solution patterns, operating standards, and evaluation practices that scale across regulated financial institutions.
About the Role
We are hiring a Forward Deployed Engineer (FDE) to lead end-to-end deployments of OpenAI’s models inside financial services organizations where correctness, latency, explainability, and control matter. You will work with customers who are experts in investment banking, trading, risk, compliance, underwriting, research, operations, or investment decision-making, translating complex workflows, data constraints, and regulatory requirements into production systems.
You will measure success through production adoption, workflow efficiency, risk reduction, revenue impact, and evaluation-driven feedback loops that inform product, model, and GTM strategy. You’ll work closely with Product, Research, GTM, Security, Legal, and GRC to deliver systems that meet enterprise standards for governance, auditability, and operational resilience.
You will also play a central role in shaping OpenAI’s Financial Services offering - identifying high-value use cases, defining solution patterns, and building the first repeatable deployments that scale across institutions.
This role is based in New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% may be required.
Responsibilities
- 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.
- 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.
Requirements
- 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.
- Have experience with financial workflows such as research, trading, risk, compliance, underwriting, operations, or investment processes, and understand how incentives and controls shape adoption.
- Write and review production-grade code across backend and frontend systems using Python, JavaScript, or comparable stacks.
- Have deployed systems powered by LLMs or generative models and understand how model behavior, evaluation, and guardrails affect user trust and business outcomes.
- Communicate clearly across engineering, product, risk, compliance, and executive stakeholders, translating technical trade-offs into decision quality and risk posture.
- Apply systems thinking with high execution standards, turning incidents, escalations, and failures into improved operating standards and repeatable deployment patterns.
- Stay calm and decisive when delivery is urgent, ambiguous, and high-stakes.
We Offer
- Competitive salary
- Relocation assistance
- Hybrid work model (3 days in the office per week)
- Opportunity to shape the future of AI in financial services
About the Company
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
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Label Your Data provides secure and high quality data annotation services for Computer Vision or NLP applications since 2020. We help Data Scientists and AI Engineers streamline the dataset labeling and focus on model development.About Label Your Data:— Founded in 2020;— 200+ annotation experts in Europe, LATAM and Africa;— 98%+ annotation accuracy benchmark;— 55 supported languages;— PCI/DSS certified;— ISO/IEC 27001:2013 certified;— GDPR, CCPA and HIPAA-compliant;— HQs in North America, EU and Asia.Our experience spans over 20 industries including Automotive, Robotics, Agriculture, E-commerce, Retail, Healthcare, Manufacturing, Fintech and Insurance.Our core services include but are not limited to:— Image & video annotation: 2D boxes, OCR, object/action detection, polygons, key points, semantic segmentation, 3D cuboids;— Text annotation: classification, NER, intent & sentiment analysis, prompts creation, Q&A pairs generation;— Audio annotation: transcription, sentiment recognition;— Sensor data annotation;— Data classification & categorization;— Data entry;— Data collection;— Model validation.
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