OpenAI

Forward Deployed Engineer - Zurich

OpenAI4 days ago
Location

Zurich, Switzerland

Type

Full Time

Salary

USD 180,000 – 280,000

Level

Senior

Role

Forward Deployed Engineer

Posted

Jul 21, 2026

Full TimeSenior

The role

Summary

Forward Deployed Engineer at OpenAI leads complex end-to-end deployments of frontier AI models in production environments, partnering directly with strategic enterprise customers. This role requires 5+ years of full-stack engineering experience with demonstrated success in customer-facing technical delivery, production-grade code in Python/JavaScript, and hands-on experience with LLM-powered systems. You will own the complete lifecycle from discovery through deployment, measure success via production adoption and workflow impact, and bridge customer needs with OpenAI's Product and Research teams.

What you'll do

End-to-End Technical Delivery Leadership: Own complete technical delivery of multiple concurrent deployments spanning from initial prototype phase through stable production environments, managing timelines, resource allocation, and quality standards across the entire deployment lifecycle.
Full-Stack System Architecture and Development: Design and build complete full-stack systems that deliver measurable customer value, including both frontend and backend components, while maintaining production-grade code quality and system reliability.
Customer Collaboration and Adoption Guidance: Embed directly within customer engineering teams, conduct discovery sessions to understand domain-specific needs, guide technology adoption decisions, and ensure successful integration of deployed AI models into customer workflows.
Project Scoping and Risk Management: Scope complex technical work, sequence delivery priorities, identify blockers early, make strategic trade-offs between scope, speed, and quality to protect delivery timelines, and adjust project plans proactively.
Hands-On Software Development: Contribute directly to production codebase when clarity or progress depends on implementation work, writing and maintaining high-quality code alongside team members.
Operationalization and Knowledge Transfer: Codify working patterns, deployment approaches, and architectural decisions into reusable tools, playbooks, and building blocks that enable other engineers to accelerate future deployments.
Feedback Translation and Product Influence: Collect and synthesize field feedback from customer deployments, identify patterns where models succeed or underperform, and communicate actionable insights to Research and Product teams to inform model and product roadmap priorities.
Cross-Functional Team Coordination: Maintain momentum across distributed teams including Product, Research, Partnerships, Security, and GTM, providing clarity on technical decisions and ensuring follow-through on commitments.

What we look for

Technical

Full-Stack Software DevelopmentProficiency writing and reviewing production-grade code across both frontend and backend systems, with demonstrated ability to make sound architectural decisions across the full stack.
Python ProgrammingAdvanced proficiency in Python for backend systems, data processing, and integration work; ability to write maintainable, well-tested production code.
JavaScript/TypeScript DevelopmentStrong capability in JavaScript or TypeScript for frontend interfaces and full-stack systems, with understanding of modern web frameworks and client-side patterns.
LLM Integration and API DesignTechnical expertise integrating language models into applications, designing APIs that expose model capabilities safely, and optimizing prompt engineering for reliable production behavior.
System Design and ArchitectureCapability to design scalable, reliable systems architecture, evaluate trade-offs between different technical approaches, and communicate designs clearly to both technical and non-technical stakeholders.

Education

Computer Science or Related FieldBachelor's degree in Computer Science, Software Engineering, or equivalent practical engineering experience demonstrating equivalent technical depth and problem-solving capability.

Experience

Advanced Customer-Facing Technical DeliveryMinimum 5+ years of engineering or technical deployment experience with substantial direct customer engagement, demonstrating ability to understand enterprise requirements and translate them into technical solutions.
Complex Systems Delivery in Ambiguous EnvironmentsProven track record scoping and delivering sophisticated technical systems in fast-moving, ambiguous, or early-stage environments where requirements evolve and rapid iteration is necessary.
Large Language Model and Generative AI SystemsHands-on experience building, deploying, or integrating systems powered by LLMs or generative models, with demonstrated understanding of how model behavior, output quality, and latency affect end-user product experience.
Production Systems and InfrastructureExperience owning production systems through their full lifecycle, including operational stability, monitoring, debugging, and scaling considerations for high-stakes customer deployments.

Skills

Required skills

Full-Stack EngineeringComprehensive expertise spanning frontend, backend, databases, and infrastructure; ability to own technical decisions across all layers and make pragmatic architectural choices.
Python Backend DevelopmentProduction-level Python coding with design patterns, testing strategies, and performance optimization; familiarity with async frameworks and web APIs.
Modern JavaScript/TypeScriptProficiency in contemporary JavaScript or TypeScript stack including component frameworks, state management, and tooling; ability to build intuitive user interfaces.
LLM Application DevelopmentHands-on experience building production applications with language models including prompt engineering, token management, cost optimization, and handling model limitations.
Customer Discovery and Technical ScopingAbility to conduct effective discovery conversations, extract requirements from ambiguous situations, and translate customer needs into technical scope and architecture.
Production Systems ThinkingDeep understanding of production operational concerns including monitoring, error handling, observability, data integrity, security, and recovery procedures.
Complexity Reduction and Decision-MakingSkill in breaking down complex problems into manageable components, making sound technical decisions under time pressure with incomplete information, and communicating rationale clearly.
Cross-Functional CommunicationExcellent verbal and written communication skills tailored to different audiences including engineers, product managers, executives, and non-technical customer stakeholders.

Nice to have

Startup or High-Growth Environment ExperienceExperience operating in early-stage startups or rapidly scaling organizations where you've worn multiple hats and adapted to changing priorities.
Enterprise Systems and IntegrationBackground integrating complex enterprise systems, managing stakeholder expectations, and understanding enterprise procurement, security, and compliance requirements.
ML/AI Model Deployment and OperationsDeployment experience with machine learning or AI models in production including A/B testing, evaluation frameworks, feedback loops, and model monitoring.
Database Design and OptimizationStrong SQL and database design expertise; ability to optimize query performance and design schemas that support application requirements at scale.
API Design and REST/GraphQLExperience designing and implementing well-documented APIs that balance flexibility with usability, including versioning strategies and backward compatibility.
Cloud Infrastructure and DevOpsFamiliarity with cloud platforms (AWS, GCP, or Azure), containerization, CI/CD pipelines, and infrastructure-as-code practices.
Security and Privacy Best PracticesUnderstanding of application security, data privacy considerations, authentication/authorization patterns, and ability to implement security controls appropriately.
Technical Leadership and MentoringExperience leading small technical teams or mentoring junior engineers; ability to elevate code quality and engineering practices through example and guidance.

Compensation & benefits

Salary

USD 180,000 – 280,000 (annual)

Stock options

Available

Benefits

Equity and Stock Options

Competitive equity package aligned with OpenAI's long-term value creation, providing meaningful upside participation as the company scales.

Health and Wellness Coverage

Comprehensive medical, dental, and vision insurance; mental health and wellness programs including therapy and fitness benefits.

Flexible Work Arrangement

Hybrid work model with 3 days in office per week based in Zurich, providing flexibility while maintaining team collaboration and culture.

Relocation Assistance

Comprehensive support for relocating to Zurich including visa sponsorship, housing assistance, and relocation logistics.

Professional Development

Budget for conferences, courses, and learning opportunities to develop technical skills and stay current with AI and software engineering advancements.

Paid Time Off

Generous vacation policy and paid leave, with flexibility to balance work intensity on customer projects with personal time.

Parental Leave

Comprehensive parental leave benefits supporting work-life balance for employees at all family stages.

Meals and Wellness Amenities

On-site meals, snacks, and wellness facilities at Zurich office supporting employee health and productivity.

Interview process

  1. 1
    Initial Screening Call — Conversation with recruiter covering background, motivation for OpenAI, relevant experience with LLMs, and understanding of the Forward Deployed Engineer role and team structure.
  2. 2
    Technical Systems Design Interview — Deep technical conversation assessing your ability to design and architect production systems. You will discuss how you would approach building a customer-facing application powered by LLMs, including technology choices, trade-offs, and scalability considerations.
  3. 3
    Practical Coding Assessment — Hands-on coding challenge evaluating your proficiency in Python and JavaScript/TypeScript. Typically focuses on building a small but complete system component that might include API development, data handling, and clean code practices.
  4. 4
    Customer Collaboration and Soft Skills Interview — Behavioral interview exploring your experience with customer-facing technical work, how you handle ambiguous requirements, make decisions under pressure, and communicate with non-technical stakeholders.
  5. 5
    LLM Product Experience Discussion — Conversation about your specific experience with language models, generative AI applications, and how you've thought about model limitations and product implications in real deployments.
  6. 6
    OpenAI Integration and Culture Fit — Final round typically involving senior team members assessing your understanding of OpenAI's mission, fit with the organization's culture of shipping with impact, and vision for AI deployment.
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

Tech Stack

Languages
PythonJavaScript/TypeScriptSQL
Frameworks
FastAPI or DjangoReact or Vue.jsNext.js
Databases
PostgreSQLRedisVector Databases
Tools
Docker and KubernetesGit and GitHubCI/CD PipelinesMonitoring and Observability ToolsOpenAI API and SDKs
Other
LLM Prompt EngineeringEvaluation FrameworksAPI Integration PatternsSecurity and Compliance

Interview Guides

5 guides available for OpenAI

Apply Now

On this page