Forward Deployed Engineer (FDE) - NYC

Engineering Manager · Senior · Full Time

New York CityUSD 185k – 300k4d ago
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Role

What you'll do.

Forward Deployed Engineers at OpenAI lead complex end-to-end deployments of frontier AI models in production with strategic customers, owning discovery through rollout while working at the intersection of customer delivery and core platform development. This role requires 5+ years of engineering experience with proven success deploying production systems in ambiguous environments, strong full-stack coding capabilities in Python or JavaScript, and hands-on expertise with large language models and generative AI systems. You'll partner directly with customer engineering teams, research, and product organizations to measure success through production adoption and feedback that shapes OpenAI's product roadmap.

Responsibilities

  • Own End-to-End Technical Delivery: Lead complete deployment lifecycle from initial customer discovery and prototype development through stable production rollout for multiple concurrent strategic deployments, ensuring successful adoption and measurable workflow impact.
  • Build Full-Stack Production Systems: Design and implement comprehensive systems that integrate frontier models into customer workflows, writing production-grade code across frontend and backend to deliver customer value while maintaining system reliability and performance.
  • Customer Enablement and Adoption: Embed closely with customer engineering and domain teams to understand business requirements, guide adoption of deployed systems, manage customer expectations, and ensure technical solutions align with business outcomes and strategic objectives.
  • Scope Management and Delivery Planning: Define project scope, sequence technical delivery milestones, identify and remove blockers proactively, make critical trade-offs between scope, speed, and quality, and adjust plans dynamically to protect on-time delivery against ambiguity and changing requirements.
  • Hands-On Engineering Contributions: Directly contribute code and technical implementation when clarity or progress depends on it, ensuring personal involvement in critical system components while mentoring customer and internal engineering teams on best practices.
  • Capture and Codify Knowledge: Document working patterns, deployment playbooks, and reusable building blocks that standardize processes across deployments, enabling other engineers and teams to accelerate future implementations and reduce rework.
  • Gather and Share Product Feedback: Collect field insights from customer deployments regarding model behavior, system performance, and user experience to inform Research and Product teams, directly influencing model improvements and product roadmap prioritization.
  • Lead Cross-Functional Collaboration: Coordinate and communicate across Product, Research, Partnerships, GRC, Security, and GTM teams, maintaining alignment on customer needs, technical constraints, and strategic priorities while keeping all stakeholders synchronized on progress.

Qualifications

What we look for.

Technical

  • Production-Grade Full-Stack Development

    Demonstrated ability to write, review, and deploy production-quality code across both frontend and backend systems, understanding performance optimization, code maintainability, and operational reliability requirements.

  • Large Language Model and Generative AI System Experience

    Hands-on experience building or deploying systems powered by LLMs or generative models, with deep understanding of how model behavior, latency, cost, and reliability affect end-user product experience and customer workflows.

  • Complex Systems Design and Architecture

    Experience scoping, designing, and deploying complex distributed systems in fast-moving or ambiguous environments, managing technical trade-offs and ensuring scalability, reliability, and maintainability of production infrastructure.

  • Full-Cycle Software Development

    Expertise across the complete software development lifecycle including architecture design, implementation, testing, deployment, and production monitoring, with ability to move fluidly between strategic planning and tactical execution.

  • API Integration and System Integration

    Proficiency integrating third-party APIs, building custom integrations with customer systems, and designing robust interfaces between LLM platforms and customer applications to ensure seamless data flow and reliability.

Education

  • Bachelor's Degree in Computer Science or Related Field

    Formal education in Computer Science, Software Engineering, Computer Engineering, or related technical discipline providing foundational knowledge in algorithms, system design, and software development principles. Equivalent professional experience may substitute.

Experience

  • 5+ Years of Engineering or Technical Deployment Experience

    Minimum five years of professional software engineering, systems engineering, or technical deployment experience with proven track record of shipping production systems at scale.

  • Customer-Facing Technical Work

    Substantial experience working directly with customers or end-users in technical capacity, understanding customer business problems, translating requirements into technical solutions, and ensuring customer satisfaction with delivered systems.

  • Complex System Delivery in Ambiguous Environments

    Proven success scoping, planning, and delivering complex technical projects with incomplete requirements or rapidly changing contexts, demonstrating ability to navigate uncertainty while maintaining delivery momentum.

  • AI/ML System Deployment at Scale

    Experience deploying machine learning or AI systems in production environments, understanding model serving infrastructure, managing model performance monitoring, and addressing challenges specific to generative AI applications.

  • Cross-Functional Leadership and Stakeholder Management

    Track record of leading technical initiatives that require coordination across engineering, product, research, and business teams, with ability to communicate effectively across technical and non-technical audiences.

Skills

Required

  • Python

    Production-level expertise in Python for backend systems, data processing, API development, and integration with LLM platforms and customer infrastructure.

  • JavaScript/TypeScript

    Strong capability in JavaScript or TypeScript for full-stack development including frontend interfaces, Node.js backend services, and API development for integrating generative AI capabilities.

  • LLM Integration and Prompt Engineering

    Deep understanding of integrating large language models into applications, optimizing prompts for reliable outputs, managing model parameters, and implementing retrieval-augmented generation (RAG) patterns.

  • System Design and Architecture

    Ability to design scalable, reliable systems that integrate frontier models with customer infrastructure, considering latency, cost, error handling, and operational requirements in production environments.

  • API Design and Integration

    Expertise designing and implementing robust APIs, integrating with customer systems, managing authentication and authorization, and building reliable interfaces between LLM services and customer applications.

  • Production Debugging and Performance Optimization

    Skills in troubleshooting production issues, profiling system performance, identifying bottlenecks, implementing optimizations, and maintaining reliability of complex distributed systems under load.

  • Technical Decision Making Under Pressure

    Ability to quickly assess trade-offs between conflicting priorities, make sound technical decisions with incomplete information, and communicate decisions clearly to technical and non-technical stakeholders.

  • Customer Communication and Requirements Translation

    Skilled at translating customer business problems into technical requirements, managing expectations, communicating progress transparently, and ensuring customer success with technical solutions.

Preferred

  • Experience with OpenAI Products

    Nice to have

    Familiarity with GPT models, OpenAI API, fine-tuning approaches, or other OpenAI tooling demonstrates practical knowledge of cutting-edge generative AI capabilities and deployment patterns.

  • Kubernetes and Cloud Infrastructure

    Nice to have

    Experience containerizing applications with Docker, orchestrating with Kubernetes, and deploying on cloud platforms (AWS, Google Cloud, Azure) for managing scalable LLM infrastructure.

  • Vector Databases and Semantic Search

    Nice to have

    Knowledge of vector databases like Pinecone, Weaviate, or Milvus, and experience implementing semantic search, similarity matching, or RAG systems for enhanced LLM applications.

  • LLM Observability and Monitoring

    Nice to have

    Experience implementing monitoring, logging, and observability for LLM systems, including token counting, cost tracking, latency monitoring, and quality metrics for generative outputs.

  • Enterprise Software Integration

    Nice to have

    Background integrating with enterprise systems like Salesforce, ServiceNow, Slack, or similar platforms, understanding SSO, data security requirements, and compliance considerations for mission-critical systems.

  • Solutions Architecture

    Nice to have

    Experience in solutions engineering or solutions architecture roles where you've designed and communicated technical solutions to customer requirements and influenced product strategy based on customer feedback.

  • Product Management Collaboration

    Nice to have

    Experience working closely with product managers and research teams to translate customer insights into product improvements and roadmap decisions, bridging technical and business perspectives.

Tech stack

Languages

PythonJavaScript/TypeScriptSQL

Frameworks

FastAPINext.js / ReactLangChain / LlamaIndexPydantic

Databases

PostgreSQLVector Databases (Pinecone, Weaviate, Milvus)Redis

Tools

OpenAI APIGit & GitHubDockerKubernetesCI/CD Platforms (GitHub Actions, CircleCI)Monitoring & Observability (Datadog, New Relic, Prometheus)Slack & Collaborative Tools

Other

REST and GraphQL API DesignPrompt Engineering and OptimizationModel Evaluation and BenchmarkingSystem Design and ScalabilitySecurity and Data Protection

Compensation

Pay and benefits.

Base·USD 185,000 – 300,000

Equity·Stock options

Benefits

  • Health Insurance and Medical Benefits

    Comprehensive medical, dental, and vision coverage with employer contributions to support employee wellness and healthcare needs.

  • 401(k) Retirement Plan

    Employer-sponsored retirement savings plan with competitive matching to support long-term financial planning and retirement security.

  • Paid Time Off and Flexible Vacation

    Generous paid time off policies including vacation days, sick leave, and mental health days with flexibility to support work-life balance.

  • Professional Development and Learning

    Budget and support for conference attendance, technical training, professional certifications, and continuous learning opportunities in AI and emerging technologies.

  • Relocation Assistance

    Comprehensive relocation support package to facilitate transition for employees moving to New York for the role, including housing assistance and logistics support.

  • Equity Compensation

    Stock options or equity grants providing ownership stake in OpenAI and aligning employee success with company growth and mission achievement.

  • Hybrid Work Environment

    Flexible hybrid arrangement requiring three days in office per week in New York headquarters with option for remote work on other days, balancing collaboration with flexibility.

  • Collaborative Culture and Mission-Driven Work

    Opportunity to work on frontier AI technology directly impacting global challenges, surrounded by leading researchers and engineers passionate about responsible AI development.

Full posting

Original listing.

About the team

OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development.

 

About the role

Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams.

 

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams.

 

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% is required.

 

In this role you will

  • Own technical delivery across multiple deployments from first prototype to stable production

  • Build full-stack systems that deliver customer value and sharpen how we learn

  • Embed closely with customer teams, understand their needs, and guide adoption of what you build

  • Scope work, sequence delivery, and remove blockers early

  • Make trade-offs between scope, speed, and quality; adjust plans to protect delivery

  • Contribute directly in the code when progress or clarity depends on it

  • Codify working patterns into tools, playbooks, or building blocks that others can use

  • Share field feedback that helps Research and Product understand where the models succeed and where they can improve

  • Keep teams moving through clarity and follow-through

 

You might thrive in this role if you

  • Bring 5+ years of engineering or technical deployment experience that includes customer-facing work

  • Have scoped and delivered complex systems in fast-moving or ambiguous environments

  • Write and review production-grade code across frontend and backend using Python, JavaScript, or comparable stacks

  • Have built or deployed systems powered by LLMs or generative models and understand how model behavior affects product experience

  • Simplify complexity and make fast, sound decisions under pressure

  • Communicate clearly with engineers, product teams, and customer stakeholders

  • Spot risks early and adjust without slowing down

  • Model calm and judgment when the stakes are high

About OpenAI

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. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

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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At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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