OpenAI

Technical Deployment Lead, Forward Deployed Engineering (FDE) - SF

OpenAI4 months ago
Location

San Francisco

Type

Full Time

Salary

USD 198,000 – 294,000

Level

Senior

Role

Lead

Posted

Feb 26, 2026

Full TimeSenior

The role

Summary

Lead technical delivery and customer deployment of complex AI/LLM systems at OpenAI's Forward Deployed Engineering team. As Technical Deployment Lead, you'll own end-to-end delivery of high-stakes enterprise engagements, translating business outcomes into technical roadmaps while managing day-to-day execution across engineering teams, researchers, and customer stakeholders. This role requires 7+ years of customer-facing technical delivery leadership, deep AI/LLM system knowledge, and ability to operate at the intersection of strategy and execution in ambiguous, high-impact environments.

What you'll do

Own Technical Delivery Planning: Define and translate business objectives into comprehensive technical roadmaps with clear milestones, interdependencies, and acceptance criteria. Map complex work streams and create detailed delivery plans that balance scope, timeline, and resource constraints while maintaining alignment with customer success metrics.
Drive Day-to-Day Engineering Execution: Track and unblock progress across OpenAI Forward Deployed Engineering teams and customer engineering organizations. Manage critical path sequencing, make real-time trade-offs between scope and priority, escalate blockers, and maintain delivery momentum through daily coordination and status management.
Embed with Customer Teams and Drive Production Adoption: Work directly with enterprise customers to map workflows, shape tool integrations, and translate business requirements into executable technical plans. Lead onboarding, adoption, and change management initiatives that ensure deployed systems become critical to customer operations.
Partner with Product and Research Leadership: Collaborate with OpenAI Product and Research teams to ensure platform components and research work streams deliver on schedule and meet deployment objectives. Surface field insights that inform roadmap priorities, architecture decisions, and model improvements.
Codify and Scale Solution Patterns: Extract reusable patterns from customer deployments and package field learnings into repeatable playbooks. Document solutions, evaluation frameworks, and best practices that improve efficiency across future enterprise engagements.
Own Value Cases and Impact Measurement: Define impact hypotheses, establish baseline metrics, and set key performance indicators for deployments. Execute pre- and post-deployment measurement, quantify ROI, and report business outcomes to executive sponsors with clear attribution of value delivered.

What we look for

Technical

AI/LLM System ArchitectureDeep understanding of large language model architecture, deployment patterns, fine-tuning approaches, and integration methodologies. Knowledge of production pitfalls, scaling challenges, and performance optimization for AI systems in enterprise environments.
System Design and Technical SequencingAbility to design complex system architectures, understand technical trade-offs at scale, and make sequencing decisions that optimize for delivery velocity. Proficiency in breaking down ambiguous technical problems into manageable execution roadmaps.
Production Deployment and DevOpsHands-on experience deploying systems to production, managing infrastructure considerations, monitoring, and operational readiness. Understanding of continuous integration/deployment pipelines, reliability patterns, and production incident management.
Technical Leadership and Cross-functional CoordinationExperience leading technical teams through complex multi-workstream projects involving research, product, and engineering functions. Ability to facilitate technical decision-making across organizational boundaries while maintaining delivery focus.

Education

Bachelor's Degree in Computer Science or Related FieldFoundational education in computer science, software engineering, mathematics, physics, or equivalent technical discipline providing strong fundamentals in computing principles.

Experience

Customer-Facing Technical Delivery Leadership7+ years leading large, complex, high-stakes customer engagements where outcomes depended on tight coordination, fast decision-making, and technical precision. Track record of successfully navigating customer politics, technical constraints, and business pressure.
AI/LLM System DeploymentShipped AI or large language model systems to production with demonstrated understanding of solution integration patterns, production deployment challenges, and customer adoption mechanics. Experience translating AI capabilities into customer business value.
Strategic Problem Framing and Pattern RecognitionAbility to step back from execution details, recognize trends across multiple engagements, and connect disparate customer needs into scalable, reusable solutions. Experience influencing roadmap and architecture based on field insights.
Enterprise Sector Deep DivesExpertise in at least one major sector such as healthcare, energy, financial services, semiconductors, or IT operations. Domain knowledge that elevates solution framing, builds customer credibility, and enables rapid contextualization of technical requirements.

Skills

Required skills

Technical Project ManagementExpert-level ability to manage complex technical programs with multiple interdependencies, competing priorities, and high ambiguity. Mastery of roadmap planning, milestone tracking, dependency management, and scope management.
Executive CommunicationFluency in translating complex technical trade-offs and architectural decisions into clear business language for C-level and executive stakeholders. Ability to communicate progress, risks, and decisions with precision and confidence.
Customer Partnership and NegotiationDeep skills in collaborative problem-solving with enterprise customers, stakeholder management, and navigating conflicting priorities. Ability to build trust, extract nuanced requirements, and partner through difficult implementation challenges.
Systems Thinking and ArchitectureAbility to understand complex systems holistically, identify critical dependencies, model system behavior under different scenarios, and make architectural trade-offs that optimize for both immediate delivery and long-term scalability.
LLM/AI Product UnderstandingDeep working knowledge of large language models, generative AI capabilities and limitations, fine-tuning, prompt engineering, and how to architect production systems that leverage these technologies effectively in enterprise contexts.
Judgment Under PressureDemonstrated ability to make high-confidence decisions with incomplete information, manage competing demands, and maintain clarity and focus during complex technical emergencies or timeline pressures.

Nice to have

Experience with AI/ML Platform DevelopmentBackground building or scaling AI/ML platforms, developer tooling for AI applications, or ML infrastructure that supports enterprise adoption of AI technologies.
Consulting or Professional Services BackgroundExperience in technology consulting, systems integration, or professional services delivery where managing complex client relationships and delivering measurable business outcomes were core responsibilities.
Developer Relations and Community BuildingExperience driving adoption through technical communities, creating developer tooling, or establishing go-to-market patterns that accelerate customer implementation and adoption velocity.
Startup Scale-Up ExperienceBackground scaling technical teams and systems from early stage through rapid growth, demonstrating ability to codify processes, establish replicable patterns, and maintain quality during explosive expansion.
Open Source Contribution and Technical AuthorityActive participation in open source communities, technical speaking, or published technical work demonstrating deep expertise and thought leadership in AI/systems engineering domains.

Compensation & benefits

Salary

USD 198,000 – 294,000 (annual)

Stock options

Available

Benefits

Equity and Stock Options

Competitive equity package with stock options reflecting your role as a senior technical leader shaping OpenAI's future. Participate directly in company upside and align incentives long-term.

Comprehensive Health and Wellness

Inclusive health insurance (medical, dental, vision), mental health services, wellness programs, and fitness benefits supporting holistic employee wellbeing.

Generous Paid Time Off

Flexible vacation policy, paid holidays, parental leave, and sabbatical options enabling work-life balance and personal renewal.

Professional Development and Learning

Access to conferences, training programs, technical certifications, and continuous learning opportunities supporting your growth as a technical leader.

Relocation Assistance

Comprehensive support for relocating to San Francisco Bay Area including logistical planning, temporary housing, and financial assistance.

Hybrid Work Model

Flexible work arrangement with 3 days per week in office, enabling collaboration while maintaining work flexibility. Travel budget for 25-50% customer engagement time.

Mission-Driven Culture

Join a team focused on AI safety, responsible AI deployment, and ensuring artificial intelligence benefits all of humanity. Direct impact on frontier AI technology and enterprise adoption.

Interview process

  1. 1
    Initial Screening Call — 30-45 minute conversation with OpenAI recruiter covering background, customer-facing technical leadership experience, and understanding of AI/LLM systems. Assess alignment with role requirements and cultural fit.
  2. 2
    Technical Leadership Deep Dive — 60-90 minute interview with current members of Forward Deployed Engineering team. Discuss specific customer engagements, technical decision-making approaches, how you handle ambiguity, and examples of scaling reusable patterns from deployments.
  3. 3
    Case Study and Problem-Solving — Work through a realistic scenario involving complex customer deployment, competing priorities, and technical/business trade-offs. Demonstrate sequencing instincts, architecture thinking, and ability to communicate decisions to stakeholders.
  4. 4
    Customer Empathy and Execution Aptitude — Panel discussion with FDE team members exploring your experience embedding with customers, translating business outcomes into technical plans, driving adoption, and collecting field signals for product improvement.
  5. 5
    Executive Presence and Impact Assessment — Interview with senior leadership (potentially VP or Director level) focused on strategic thinking, executive communication, judgment under pressure, and track record of delivering measurable business impact through technical deployment.
  6. 6
    Final Conversation — Opportunity to discuss role expectations, team dynamics, growth trajectory, and ask questions about OpenAI's mission, culture, and your potential impact on the organization's AI deployment strategy.
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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
PythonTypeScript/JavaScript
Frameworks
Large Language Models (LLMs) and TransformersLangChain/Orchestration FrameworksRetrieval Augmented Generation (RAG)
Databases
Vector DatabasesEnterprise Data Stores
Tools
OpenAI API and PlatformCloud Platforms (AWS, GCP, Azure)CI/CD and DevOps ToolsCollaboration and Project Management
Other
Evaluation Frameworks and MetricsChange Management and Adoption PlaybooksEnterprise Sector Domain Knowledge

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