OpenAI

Forward Deployed Engineer (FDE) - Seattle

OpenAI4 months ago
Location

Seattle

Type

Full Time

Salary

USD 162,000 – 280,000

Level

Senior

Role

Full Stack Engineer

Posted

Mar 4, 2026

Full TimeSenior

The role

Summary

Forward Deployed Engineers at OpenAI lead end-to-end production deployments of frontier AI models alongside strategic customers, bridging research innovation with real-world implementation. This role combines full-stack engineering, customer partnership, and technical leadership to drive adoption of generative AI systems while gathering field feedback that shapes product and model roadmaps. You'll need 5+ years of engineering experience, production-grade coding skills across multiple stacks, and demonstrated expertise deploying LLM-powered systems in complex, fast-moving environments.

What you'll do

Own End-to-End Technical Delivery: Lead complete product lifecycle from initial prototype through stable production deployment across multiple concurrent customer engagements. Manage technical architecture decisions, implementation strategy, and rollout planning while maintaining accountability for system reliability, performance, and user adoption metrics.
Build Full-Stack Production Systems: Design and implement comprehensive systems that integrate frontend interfaces, backend APIs, and cloud infrastructure to deliver measurable customer value. Write production-grade code in Python, JavaScript, or comparable languages, implementing proper error handling, monitoring, and scalability patterns.
Drive Customer-Centric Technical Engagement: Embed deeply within customer teams to understand their operational challenges, technical constraints, and success metrics. Guide adoption of deployed systems, conduct technical training, and establish feedback loops that ensure solutions meet real-world business requirements and workflow integration.
Scope and Manage Complex Deployments: Break down ambiguous requirements into concrete technical work streams, establish delivery sequencing, and identify blockers early. Make informed trade-offs between scope, development speed, and code quality while adjusting plans proactively to protect delivery timelines and system stability.
Contribute Direct Technical Implementation: Write code across the full stack when technical clarity or development velocity requires hands-on contribution. Participate in code reviews, establish development standards, and ensure implementation aligns with architectural decisions and production readiness criteria.
Develop Reusable Patterns and Tools: Codify successful deployment patterns, technical approaches, and operational processes into reproducible tools, playbooks, and building blocks. Create internal documentation and frameworks that accelerate future deployments and enable other engineers to leverage proven solutions.
Bridge Research and Product Feedback Loops: Translate field observations into actionable insights about model behavior, system performance, and customer needs. Share comprehensive deployment data and use case learnings with research and product teams to inform model improvements, feature prioritization, and future product roadmaps.
Lead Through Clarity and Execution: Maintain team momentum through clear communication, transparent status updates, and decisive follow-through on commitments. Model calm judgment under pressure, provide technical leadership to customer and internal teams, and navigate high-stakes situations with composure and sound decision-making.

What we look for

Technical

Production-Grade Full-Stack DevelopmentDemonstrate expertise writing and reviewing production-quality code across frontend, backend, and infrastructure layers. Experience building robust systems with proper error handling, observability, unit testing, and performance optimization.
LLM and Generative AI Systems ExperienceProven track record building or deploying systems powered by large language models or generative AI models. Deep understanding of how model behavior, hallucinations, latency, and output variability affect end-user experience and system reliability.
Complex System Architecture and DesignExperience scoping and delivering complex, distributed systems in ambiguous or fast-moving environments. Ability to design system architectures that balance competing priorities and scale reliably under varying workloads.
Customer-Facing Technical DeliveryDemonstrated ability to lead technical implementations alongside customer engineering teams with varying technical sophistication. Experience translating customer business requirements into technical solutions and managing stakeholder expectations.
Cloud Infrastructure and DevOpsWorking knowledge of cloud platforms (AWS, GCP, Azure), containerization, deployment automation, and infrastructure-as-code principles. Experience with monitoring, logging, and incident response in production environments.

Education

Bachelor's Degree in Computer Science or Related FieldFormal education in computer science, software engineering, or equivalent technical discipline providing foundational knowledge in algorithms, data structures, system design, and computer architecture.

Experience

5+ Years of Software Engineering ExperienceMinimum five years of professional software engineering or technical deployment experience, with substantial hands-on development work and demonstrated progression in complexity and scope of systems built.
Customer-Facing Technical LeadershipProven experience owning technical relationships with external customers or partners, managing expectations, addressing technical concerns, and driving adoption of delivered solutions in production environments.
Multi-Functional Team CollaborationTrack record collaborating effectively across product, research, operations, and business teams. Ability to influence without direct authority and navigate competing priorities while maintaining technical integrity.
Fast-Paced Environment NavigationDemonstrated success operating in ambiguous, rapidly evolving environments where requirements change frequently and decision-making velocity is critical. Comfort with incomplete information and ability to make sound technical trade-offs under uncertainty.

Skills

Required skills

PythonAdvanced proficiency writing production Python code including async programming, testing frameworks, and deployment tooling. Experience with Python-based data processing and integration with cloud services.
JavaScript / TypeScriptStrong capability building frontend applications and backend services with JavaScript or TypeScript. Experience with modern frameworks, REST/GraphQL APIs, and client-server communication patterns.
System Design and ArchitectureAbility to design scalable distributed systems, make trade-off decisions between different architectural patterns, and communicate design decisions clearly to technical and non-technical stakeholders.
API Design and IntegrationExperience designing RESTful or GraphQL APIs, integrating third-party services, and building robust integrations that handle edge cases, rate limiting, and error scenarios gracefully.
Version Control and CollaborationProficiency with Git-based workflows, code review processes, and collaborative development practices. Understanding of CI/CD pipelines and deployment automation.
Debugging and TroubleshootingStrong problem-solving skills including ability to debug complex systems, read unfamiliar code, and use profiling and monitoring tools to identify performance bottlenecks and reliability issues.
Technical CommunicationAbility to explain complex technical concepts to diverse audiences including non-technical customers, product managers, and research teams. Clear documentation and diagramming skills.

Nice to have

Kubernetes and Container OrchestrationExperience deploying and managing containerized applications using Kubernetes, including configuration, scaling, and operational best practices in production environments.
Machine Learning Operations (MLOps)Familiarity with ML model deployment pipelines, versioning, monitoring, and A/B testing frameworks. Understanding of ML-specific infrastructure requirements and challenges.
Real-Time Systems and StreamingExperience with event-driven architectures, message queues, or real-time data processing systems that handle high-throughput, low-latency requirements.
Security and ComplianceWorking knowledge of authentication, authorization, data encryption, and compliance requirements relevant to enterprise deployments. Familiarity with security best practices in cloud environments.
Observability and MonitoringHands-on experience implementing comprehensive logging, metrics, tracing, and alerting systems. Proficiency with tools like Datadog, New Relic, or Prometheus for production monitoring.
Generative AI and LLM FrameworksDirect experience with LLM frameworks such as LangChain, LlamaIndex, or OpenAI APIs. Understanding of prompt engineering, model fine-tuning, and evaluation methodologies for generative systems.
Enterprise Software and Solutions EngineeringBackground in solutions architecture, customer success engineering, or professional services delivery in enterprise SaaS environments. Experience managing complex customer deployments and multi-stakeholder projects.

Compensation & benefits

Salary

USD 162,000 – 280,000 (annual)

Stock options

Available

Benefits

Equity and Stock Options

Significant ownership stake through competitive equity packages that align your success with company growth in the high-growth AI sector

Comprehensive Health Insurance

Medical, dental, and vision coverage with low out-of-pocket costs for you and your family

Retirement Planning

401(k) plan with employer matching contributions to support long-term financial security

Flexible Work Arrangement

Hybrid work model requiring 3 days per week in Seattle office with flexibility for remote work days, supporting work-life integration

Relocation Assistance

Comprehensive relocation package available for candidates moving to Seattle, including moving expenses and temporary housing support

Professional Development

Learning budget and conference attendance support to keep your skills current in rapidly evolving AI and software engineering domains

Mental Health and Wellness

Counseling services, meditation apps, and wellness programs supporting overall health and stress management

Parental Leave

Generous paid parental leave policies supporting family planning decisions

Paid Time Off

Flexible PTO policy providing ample time for rest, travel, and personal pursuits

Employee Discounts

Access to OpenAI's tools and products at preferential rates, plus partnerships with local Seattle businesses

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OpenAI

OpenAI

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OpenAI is an American artificial intelligence research organization developing advanced AI models like GPT. Focused on ensuring AI benefits humanity, it creates tools for natural language processing and generative AI applications.

San Francisco, California, United StatesFounded 2015openai.com

Tech Stack

Languages
PythonJavaScript/TypeScriptSQL
Frameworks
FastAPI / DjangoReactNext.jsNode.jsLangChain / LlamaIndex
Databases
PostgreSQLRedisVector Databases (Pinecone/Weaviate)
Tools
DockerKubernetesAWS / GCPGitHubTerraformDatadog / Prometheus
Other
OpenAI APIGraphQLPrompt EngineeringAgile Development

Interview Guides

5 guides available for OpenAI

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