OpenAI

Forward Deployed Engineer - Munich

OpenAI10 months ago
Location

Munich, Germany

Type

Full Time

Salary

EUR 150,000 – 220,000

Level

Senior

Role

Lead Software Engineer

Posted

Sep 23, 2025

Full TimeSenior

The role

Summary

OpenAI seeks a Forward Deployed Engineer in Munich to lead end-to-end production deployments of frontier large language models alongside strategic customers. You'll own discovery through production rollout, building full-stack systems that deliver measurable impact while gathering field feedback that shapes product roadmaps. This role requires 5+ years of engineering experience with customer-facing technical deployments, production-grade coding across full-stack systems, hands-on LLM integration experience, and the ability to drive complex projects in ambiguous, fast-moving environments.

What you'll do

End-to-End Production Deployments: Own complete technical delivery lifecycle from prototype through stable production across multiple simultaneous deployments of frontier AI models. Manage the transition from proof-of-concept to scalable, production-grade systems serving strategic customers with complex infrastructure requirements.
Full-Stack System Architecture and Implementation: Design and build full-stack systems integrating large language models with customer infrastructure, including backend services, API layers, frontend interfaces, and data pipelines. Write production-grade code across Python, JavaScript, and comparable stacks while maintaining high quality and performance standards.
Customer Discovery and Technical Scoping: Conduct technical discovery sessions with customer engineering and domain teams to understand core requirements, constraints, and success metrics. Scope complex projects, define technical requirements, create implementation roadmaps, and translate ambiguous customer needs into actionable technical specifications.
Stakeholder Alignment and Delivery Planning: Partner directly with Product, Research, Partnerships, GRC, Security, and GTM teams to align deployments with organizational priorities. Make informed trade-offs between scope, speed, and quality; adjust plans proactively to protect delivery timelines and maintain stakeholder confidence.
Production Adoption and Impact Measurement: Drive production adoption of deployed systems by embedding closely with customer teams and guiding effective utilization. Measure success through adoption metrics, quantifiable workflow improvements, and evaluation-driven feedback that directly influences AI model and product roadmap decisions.
Feedback Loop and Model Improvement: Collect and synthesize detailed field feedback from production deployments, identifying where frontier models excel and where improvements are needed. Communicate these insights to Research and Product teams to shape model capabilities and inform future development priorities based on real-world usage patterns.
Process Documentation and Knowledge Codification: Develop reusable tools, playbooks, architectural patterns, and best practice documentation from field experience. Create building blocks and standardized approaches that accelerate future deployments and enable other engineers to execute complex LLM integrations efficiently.
Risk Mitigation and Blocker Resolution: Identify risks and technical blockers early in project lifecycles and implement mitigation strategies without slowing delivery momentum. Navigate ambiguous situations with calm judgment, make sound decisions under pressure, and maintain team momentum through clear communication and decisive follow-through.

What we look for

Technical

Full-Stack Production DevelopmentProven expertise writing and reviewing production-grade code across frontend and backend systems using Python, JavaScript, or comparable technology stacks. Demonstrated ability to architect scalable systems, implement robust APIs, and maintain high code quality standards in fast-moving environments.
Large Language Model Integration and DeploymentHands-on experience building or deploying systems powered by large language models and generative AI models. Deep understanding of how model behavior, latency, costs, and output variability affect product experience and customer satisfaction in production environments.
Complex System Design and ScopingAbility to design and architect complex, multi-component systems in ambiguous environments with unclear requirements. Experience scoping large projects, identifying technical dependencies, estimating effort accurately, and breaking down complex problems into manageable delivery phases.
Production Systems and DevOps FundamentalsUnderstanding of production infrastructure, deployment pipelines, monitoring, logging, and observability practices. Experience with cloud platforms, containerization, CI/CD practices, and the operational considerations of running AI systems at scale.

Education

Computer Science or Related Field (Preferred)Bachelor's degree in Computer Science, Software Engineering, or related technical discipline. Equivalent professional experience and demonstrable technical depth through portfolio or project work can substitute for formal degree requirements.

Experience

5+ Years Customer-Facing Technical DeliveryMinimum 5 years of professional software engineering or technical deployment experience that includes substantial customer-facing work. Track record of leading complex technical projects from requirements gathering through production deployment with direct customer engagement.
Complex Project Delivery in Ambiguous EnvironmentsDemonstrated success scoping and delivering sophisticated systems in fast-moving, ambiguous conditions with evolving requirements. Ability to maintain delivery momentum, manage stakeholder expectations, and adapt plans based on emerging information without losing progress.
Cross-Functional Collaboration and Technical LeadershipExperience working effectively across engineering, product, research, partnerships, and business teams. Ability to communicate complex technical concepts to diverse audiences including executives, researchers, and non-technical stakeholders while maintaining credibility and influence.
Decision-Making Under Uncertainty and PressureProven ability to simplify complexity, make sound decisions with incomplete information, and maintain composure when stakes are high. Track record of spotting risks early, implementing mitigation strategies, and adjusting course effectively without slowing team progress.

Skills

Required skills

Python ProgrammingProduction-level Python development expertise for backend services, data processing, API development, and integration with machine learning frameworks.
JavaScript/TypeScript Full-Stack DevelopmentFrontend and backend JavaScript/TypeScript skills for building user-facing applications and services that integrate with AI models and APIs.
API Design and ImplementationExperience designing and implementing RESTful or GraphQL APIs, managing API versioning, authentication, rate limiting, and integration with frontend systems.
LLM Integration and Prompt EngineeringHands-on experience integrating large language models into applications, understanding API patterns, managing context windows, implementing retrieval-augmented generation, and optimizing prompt patterns for production use.
System Architecture and DesignAbility to design scalable architectures considering performance, reliability, security, and cost. Experience with distributed systems patterns, microservices architecture, and deployment strategies.
Technical CommunicationExcellent written and verbal communication skills for translating between technical teams, customers, product managers, and executives. Ability to document complex systems clearly and present technical concepts to diverse audiences.
Project Scoping and Delivery ManagementProven ability to scope complex projects, break down ambiguous requirements into concrete deliverables, manage timelines, and adjust plans based on emerging constraints.
Debugging and Problem-SolvingStrong analytical skills and ability to debug complex, distributed systems involving multiple components, third-party services, and AI models with non-deterministic behavior.

Nice to have

GenAI Product DevelopmentPrior experience building or shipping products that leverage generative AI, including understanding of model selection, fine-tuning strategies, and user experience considerations for AI-powered features.
Enterprise SaaS ArchitectureExperience building systems serving enterprise customers with requirements around data privacy, security compliance, role-based access control, and audit logging.
Cloud Platform ExpertiseFamiliarity with major cloud providers (AWS, Google Cloud, Azure) and their AI/ML services, including managed inference endpoints, scaling patterns, and cost optimization.
Infrastructure and DevOpsExperience with Docker, Kubernetes, CI/CD pipelines, infrastructure-as-code, monitoring platforms, and the operational aspects of deploying and maintaining production systems.
Agile and Rapid IterationBackground working in fast-moving startups or fast-moving teams within larger organizations with experience shipping features rapidly while maintaining quality.
Technical Consulting or Solutions EngineeringExperience in technical pre-sales, solutions architecture, or consulting roles where you've advised customers on technology decisions and custom implementations.
Observability and Production MonitoringPractical experience with logging platforms, metrics collection, distributed tracing, and incident response in production environments serving real users.
Security and Data PrivacyUnderstanding of application security principles, secure API design, data encryption, privacy compliance considerations (GDPR, regional regulations), and secure handling of sensitive customer data.

Compensation & benefits

Salary

EUR 150,000 – 220,000 (annual)

Stock options

Available

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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
React or Vue.jsNode.js/ExpressFastAPI or DjangoLangChain or LlamaIndex
Databases
PostgreSQLVector Databases (Pinecone, Weaviate, Milvus)Redis
Tools
Git and GitHubDocker and Container TechnologiesKubernetes (optional)CI/CD Platforms (GitHub Actions, GitLab CI, Jenkins)Monitoring and Logging (DataDog, New Relic, ELK Stack)API Testing and Documentation (Postman, Swagger/OpenAPI)
Other
OpenAI API and Model EcosystemLLM Evaluation FrameworksCloud Infrastructure (AWS, Google Cloud, Azure)Prompt Engineering and Model OptimizationSecurity and Compliance Standards

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