OpenAI

Forward Deployed Engineer - London

OpenAI8 months ago
Location

London, UK

Type

Full Time

Salary

GBP 180,000 – 280,000

Level

Senior

Role

Forward Deployed Engineer

Posted

Nov 13, 2025

Full TimeSenior

The role

Summary

OpenAI seeks a Forward Deployed Engineer in London to lead complex end-to-end production deployments of frontier AI models alongside strategic customers, bridging research breakthroughs and real-world implementation. The role requires ownership across discovery, technical scoping, system design, full-stack development, and production rollout while partnering directly with customer engineering teams, research, product, and platform development groups. This position demands 5+ years of engineering experience with customer-facing deployment expertise, proficiency in full-stack development with Python or JavaScript, hands-on LLM systems experience, and exceptional ability to drive complex projects to production success under ambiguous, high-pressure conditions.

What you'll do

End-to-End Technical Delivery Leadership: Own complete technical delivery across multiple concurrent deployments from initial prototype through stable production environments. This encompasses architecting scalable systems that serve strategic customers, managing deployment complexity, and ensuring successful production adoption of frontier AI models. You will be accountable for delivery timelines, system reliability, and measurable business impact.
Full-Stack Systems Development: Design and build full-stack systems spanning frontend interfaces, backend services, and AI model integration layers that deliver tangible customer value. Write production-grade code across both backend and frontend components, make architectural decisions that balance scalability with speed, and contribute directly to the codebase when critical for progress clarity or delivery velocity.
Customer Partnership and Discovery: Embed closely within customer teams to conduct thorough discovery, understand core business needs, technical constraints, and success metrics. Guide customer adoption of deployed systems through hands-on collaboration, translate customer requirements into technical specifications, and drive workflow impact measurement to validate deployment success.
Technical Scoping and Project Management: Scope complex engineering work across ambiguous deliverables, sequence work into achievable phases, and remove technical blockers proactively. Make critical trade-off decisions between scope, speed, and quality; manage stakeholder expectations; adjust plans dynamically to protect delivery timelines while maintaining system reliability and production standards.
LLM Systems and Model Integration Expertise: Leverage deep understanding of large language model behavior and capabilities to design systems that maximize model effectiveness in production. Conduct eval-driven feedback cycles to understand where frontier models succeed and fail, translate model limitations into product improvements, and guide research and product teams with field insights that inform model and platform roadmaps.
Cross-Functional Collaboration: Work seamlessly across Product, Research, Partnerships, GRC, Security, and Go-To-Market teams. Facilitate clear communication between technical teams and customer stakeholders, coordinate between internal functions to unblock dependencies, and maintain alignment on priorities and timelines.
Knowledge Codification and Playbook Development: Systematically document working patterns, deployment strategies, and solutions discovered during customer engagement into reusable tools, playbooks, and architectural building blocks. Create technical documentation and decision frameworks that enable other engineers to accelerate future deployments and scale organizational knowledge.
Production Risk Management: Identify and mitigate production risks early through proactive monitoring, thorough testing, and resilience planning. Spot emerging issues before they impact customers, implement appropriate safeguards and observability, and maintain composure during incidents or high-stakes production moments.

What we look for

Technical

Full-Stack Production DevelopmentDemonstrated proficiency writing and reviewing production-grade code across both frontend and backend systems. Strong competency with Python, JavaScript, or comparable modern stacks. Experience building scalable, maintainable systems with proper architecture, testing strategies, and deployment practices.
Large Language Model Systems ExperienceHands-on experience building, deploying, or operating systems powered by large language models or generative AI models in production environments. Deep understanding of how model behavior, inference latency, token economics, and model limitations directly impact product experience and customer outcomes.
Complex Systems ArchitectureAbility to design and scope complex distributed systems in fast-moving, ambiguous environments. Experience with system design tradeoffs including scalability, performance, reliability, and cost. Familiarity with observability, monitoring, and incident response in production systems.
Customer-Facing Technical DeliveryProven track record of scoping, designing, and shipping complex systems in customer-facing or deployment-oriented roles. Experience translating customer requirements into technical specifications and managing stakeholder expectations through delivery cycles.
API Integration and Deployment PatternsStrong understanding of API design, integration patterns, and deployment methodologies. Experience with containerization, infrastructure-as-code, CI/CD pipelines, and production deployment best practices. Familiarity with cloud platforms and modern DevOps tooling.

Education

Computer Science FoundationBachelor's degree in Computer Science, Software Engineering, or equivalent technical field preferred. Equivalent professional experience demonstrating mastery of computer science fundamentals may substitute for formal degree.
Continuous Learning OrientationDemonstrated commitment to staying current with emerging technologies, particularly in AI/ML systems, large language models, and modern software engineering practices. Self-directed learner with strong problem-solving fundamentals.

Experience

Senior Software Engineering ExperienceMinimum 5+ years of professional software engineering experience that includes significant customer-facing or deployment engineering work. Track record of owning end-to-end delivery from architecture through production rollout.
Technical Leadership in AmbiguityDemonstrated ability to lead complex technical initiatives in fast-moving, uncertain environments with incomplete requirements. Success at breaking down ambiguous problems, making sound technical decisions under pressure, and pivoting quickly when conditions change.
Stakeholder Influence and CommunicationStrong experience communicating complex technical concepts clearly to diverse audiences including engineers, product managers, executives, and non-technical customers. Ability to influence priorities and secure buy-in across organizational boundaries.
Production Systems OwnershipExperience owning production systems throughout their lifecycle with accountability for reliability, performance, and business outcomes. Exposure to production incidents, on-call responsibilities, and operational excellence practices.

Skills

Required skills

Python Backend DevelopmentStrong proficiency in Python for building production backend services, APIs, and infrastructure code. Experience with async frameworks, testing strategies, and performance optimization.
JavaScript/TypeScript Frontend DevelopmentProduction-level capability building modern web interfaces using JavaScript/TypeScript, including component architecture, state management, and responsive UI implementation.
System Design and ArchitectureAbility to architect scalable, reliable systems making informed tradeoffs between performance, maintainability, and deployment complexity. Strong grasp of distributed systems concepts and microservices patterns.
LLM Integration and Prompt EngineeringHands-on expertise integrating large language models into production systems. Understanding of prompt design, few-shot learning, retrieval augmented generation, fine-tuning approaches, and model behavior optimization for customer use cases.
Technical Project ManagementAbility to scope work, sequence delivery across dependencies, manage timelines, and communicate status clearly. Experience managing stakeholder expectations and making scope/speed/quality tradeoffs transparently.
Customer Collaboration and Requirements TranslationSkill translating customer business needs into technical requirements, asking clarifying questions to understand root problems, and presenting solutions in business-relevant terms. Ability to build trust with non-technical stakeholders.
Production Deployment and DevOpsSolid understanding of deployment processes, infrastructure management, containerization (Docker/Kubernetes), CI/CD pipelines, and cloud platforms. Experience monitoring and troubleshooting production systems.
Debugging and Problem-SolvingStrong systematic approach to diagnosing complex technical issues across multiple system layers. Ability to root cause problems, implement fixes, and prevent recurrence through monitoring and architecture improvements.

Nice to have

Experience with OpenAI APIsPrior hands-on experience building applications using OpenAI models (GPT-4, GPT-3.5 Turbo) or similar frontier language models. Understanding of model capabilities, limitations, token costs, and best practices for production integrations.
Venture Capital or Startup Technical LeadershipBackground working at high-growth startups or venture-backed companies facing rapid scaling challenges, ambiguous requirements, and resource constraints. Experience adapting quickly to changing priorities and making high-impact technical decisions with incomplete information.
Enterprise Customer Success and DeploymentExperience shipping complex systems to enterprise customers with strong governance, security, and compliance requirements. Familiarity with customer implementation support, training, and long-term success metrics.
ML Systems and InfrastructureUnderstanding of ML infrastructure, model serving platforms, inference optimization, and monitoring specialized considerations for ML systems. Experience with MLOps tools and practices.
Solutions ArchitectureBackground as a Solutions Architect, Solutions Engineer, or similar role bridging customer needs with technical implementation. Experience designing reference architectures and customer-specific solutions.
Security and Compliance in AI SystemsFamiliarity with security considerations specific to AI systems including prompt injection vulnerabilities, data privacy in LLM systems, and compliance frameworks relevant to AI deployment.
Quantitative Analysis and MetricsExperience designing and implementing metrics for measuring system success, conducting A/B testing, analyzing performance data, and making data-driven decisions about tradeoffs and improvements.

Compensation & benefits

Salary

GBP 180,000 – 280,000 (annual)

Stock options

Available

Benefits

Equity Compensation

Significant stock options with competitive vesting schedules reflecting the strategic importance of the role. Opportunity to participate in OpenAI's growth as equity holder with real upside potential.

Health and Wellness Benefits

Comprehensive health insurance coverage including medical, dental, and vision. Mental health and wellness programs with access to counseling, fitness stipends, and wellness initiatives.

Retirement and Financial Planning

Competitive pension schemes meeting or exceeding UK statutory requirements. Financial planning resources and retirement advisory services to support long-term financial wellbeing.

Flexible Work Model

Hybrid work arrangement with 3 days per week in London office. Flexibility for remote work during customer engagements or when appropriate for project needs. Clear work-life balance expectations.

Relocation Support

Comprehensive relocation assistance package covering moving expenses, temporary housing, visa sponsorship, and family support. Ongoing support to ease transition to London if relocating from outside UK.

Professional Development

Robust learning and development budget for conferences, courses, and professional certifications. Access to internal training, mentorship from OpenAI's research teams, and opportunities to engage with cutting-edge AI research.

Paid Time Off

Generous vacation allowance exceeding UK statutory minimums with unlimited sick leave policy. Parental leave benefits supporting family planning and flexible return-to-work arrangements.

Technology and Tools

Top-tier computing equipment including high-performance laptops and monitors. Access to premium development tools, cloud credits, and necessary infrastructure to execute technical work at scale.

Dining and Office Amenities

Subsidized or complimentary meals in London office. Modern office facilities with collaboration spaces, quiet work areas, and access to fitness facilities.

Commute and Transportation

Commute benefits package reducing transportation costs to London office. Potentially eligibility for cycle to work schemes and transportation assistance.

Apply for this position

You'll be redirected to the company's application page

OpenAI

OpenAI

View all jobs

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

Interview Guides

5 guides available for OpenAI

Apply Now

On this page