OpenAI

Forward Deployed Engineer - Paris

OpenAI10 months ago
Location

Paris, France

Type

Full Time

Salary

EUR 180,000 – 280,000

Level

Senior

Role

Lead Engineer

Posted

Sep 23, 2025

Full TimeSenior

The role

Summary

Forward Deployed Engineer at OpenAI, based in Paris, leading end-to-end production deployments of frontier AI models with strategic customers. This role bridges customer delivery and core platform development, requiring 5+ years of engineering experience with customer-facing expertise, full-stack development capabilities in Python/JavaScript, and hands-on experience deploying LLM-powered systems. You will own technical scoping, system design, production rollout, and drive measurable adoption while gathering field feedback that shapes product and model roadmaps.

What you'll do

Lead End-to-End Technical Deployments: Own complete deployment lifecycle from discovery and technical scoping through system design, implementation, and stable production rollout. Manage multiple concurrent deployments of frontier AI models alongside OpenAI's most strategic customers, ensuring each deployment meets production quality standards and customer success metrics.
Design and Build Full-Stack Systems: Architect and develop production-grade full-stack systems that deliver quantifiable customer value. Write clean, maintainable code across frontend and backend layers, integrating frontier models into scalable production environments while maintaining code quality and system reliability.
Drive Customer Success and Adoption: Embed directly with customer engineering teams to understand business requirements, technical constraints, and workflow needs. Guide customers through adoption of deployed systems, remove technical blockers, and measure success through production adoption rates and measurable workflow impact metrics.
Scope Work and Manage Trade-offs: Define project scope, sequence delivery milestones, and make strategic trade-offs between scope, speed, and quality. Adjust implementation plans proactively to protect delivery timelines while maintaining system reliability and customer satisfaction in fast-moving environments.
Contribute Hands-On Technical Implementation: Actively participate in development when progress or technical clarity depends on engineering contribution. Balance leadership and project management responsibilities with hands-on coding to unblock teams, establish technical direction, and maintain connection to implementation details.
Codify and Scale Working Patterns: Transform field learnings into reusable tools, playbooks, architectural patterns, and building blocks that other engineers and customers can leverage. Document best practices and deployment strategies to accelerate future engagements and build organizational knowledge.
Provide Strategic Field Feedback: Gather detailed feedback from customer deployments about frontier model behavior, real-world performance, edge cases, and user experience gaps. Share actionable insights with Research, Product, and GTM teams that directly inform model improvements, feature prioritization, and product roadmap decisions.
Lead with Clarity and Follow-Through: Maintain transparent communication with cross-functional teams including Product, Research, Partnerships, GRC, Security, and GTM. Keep teams aligned and moving forward through clear status communication, proactive risk management, and reliable execution under pressure.

What we look for

Technical

Production-Grade Full-Stack DevelopmentDemonstrated expertise writing and reviewing production-quality code across both frontend and backend systems using Python, JavaScript, or equivalent modern programming languages. Must have experience optimizing for performance, reliability, and maintainability in customer-facing systems.
LLM and Generative Model SystemsProven experience building, deploying, or significantly contributing to systems powered by Large Language Models (LLMs) or generative AI models. Must understand how model behavior, latency, output quality, and stochasticity affect end-user product experience and system reliability.
Complex System Design and ScopingStrong ability to scope complex technical projects, design scalable system architectures, and manage technical dependencies. Must excel at breaking down ambiguous requirements into actionable engineering work and sequencing delivery to balance competing priorities.
API Integration and Third-Party SystemsExperience integrating multiple APIs, third-party services, and platform capabilities into cohesive customer solutions. Must understand API design patterns, error handling, rate limiting, and integration testing for production reliability.
Performance Optimization and DebuggingCapability to identify and resolve performance bottlenecks, troubleshoot production issues under pressure, and implement monitoring and observability solutions. Must be comfortable using profiling tools, distributed tracing, and log analysis to diagnose complex system issues.

Education

Computer Science or Related Technical DisciplineBachelor's degree in Computer Science, Software Engineering, or equivalent technical field is preferred. Advanced degrees in related disciplines or equivalent professional certifications can substitute for formal education with sufficient professional experience.

Experience

Customer-Facing Technical LeadershipMinimum 5+ years of engineering or technical deployment experience with substantial customer-facing responsibilities. Must have directly engaged with enterprise or strategic customers to understand their requirements, translate needs into technical solutions, and drive adoption.
Fast-Moving and Ambiguous EnvironmentsProven track record scoping and delivering complex systems in fast-paced, rapidly changing environments with incomplete information. Must demonstrate ability to make sound technical decisions with imperfect data and adapt strategies as new requirements emerge.
Technical Leadership and MentorshipExperience leading technical projects, making architectural decisions, and working effectively with senior engineering and product teams. Should have mentored junior engineers or guided technical decisions for teams larger than just themselves.
Stakeholder Communication Across FunctionsProven ability to communicate effectively with diverse stakeholder groups including engineers, product managers, executives, and customer technical teams. Must translate between technical and business contexts and build alignment across different perspectives.

Skills

Required skills

PythonExpert-level proficiency in Python for building scalable backend systems, data processing pipelines, and ML-adjacent applications. Must be able to write clean, well-tested code following production best practices.
JavaScript/TypeScriptStrong capability in JavaScript or TypeScript for frontend development and Node.js backend services. Should include experience with modern frameworks and asynchronous programming patterns.
System Architecture and DesignAbility to design scalable, reliable system architectures that handle production workloads. Must understand microservices patterns, API design, database design, caching strategies, and deployment architectures.
Production Deployment and DevOpsPractical experience deploying and operating systems in production environments. Must understand CI/CD pipelines, containerization, infrastructure management, and monitoring/observability for production reliability.
Problem-Solving Under PressureDemonstrated ability to simplify complexity, make fast and sound decisions in ambiguous situations, and maintain composure when stakes are high. Must stay calm and maintain judgment while troubleshooting production issues.

Nice to have

LLM API IntegrationDirect experience integrating OpenAI APIs (GPT, Embeddings) or other LLM provider APIs into production applications. Understanding of prompt engineering, token accounting, and cost optimization for model APIs.
Machine Learning Operations (MLOps)Experience managing ML model deployment pipelines, A/B testing, monitoring model performance, and handling model versioning. Understanding of evaluation metrics and feedback loops for iterative model improvement.
Enterprise Software and SecurityFamiliarity with enterprise software requirements including security compliance (SOC2, GDPR), access controls, audit logging, and data privacy considerations relevant to regulated industries.
Cloud Platform ExperienceHands-on experience with major cloud platforms (AWS, Google Cloud, Azure) including compute services, databases, networking, and managed services relevant to production deployments.
Customer Success and Sales EngineeringBackground in customer-facing technical roles such as Solutions Architect, Sales Engineer, or Customer Success Engineer. Understanding of customer buying processes, technical evaluation criteria, and post-sale implementation challenges.
React or Vue.jsProfessional experience building interactive user interfaces using React or Vue.js. Familiarity with state management, component design patterns, and modern frontend tooling.

Compensation & benefits

Salary

EUR 180,000 – 280,000 (annual)

Interview process

  1. 1
    Initial Screening Call — 30-minute conversation with a recruiter to discuss your background, customer-facing experience, and alignment with the Forward Deployed Engineering role. Expect questions about your most complex technical deployment and how you've managed ambiguity.
  2. 2
    Technical Depth Interview — 60-90 minute conversation with a senior engineer focusing on your system design capabilities, production experience, and technical decision-making. You may be asked to walk through a complex system you've built, discuss trade-offs you've made, or solve architectural problems.
  3. 3
    Customer Engagement Simulation — Technical conversation with a Forward Deployed Engineer or Product Manager simulating a customer engagement scenario. You'll discuss how you'd approach understanding customer needs, scope a technical solution, and communicate trade-offs to non-technical stakeholders.
  4. 4
    Full-Stack Code Review — Technical assessment where you review production code and discuss improvements, or complete a take-home coding exercise demonstrating full-stack capabilities in Python and JavaScript. Expect questions about code quality, testing, and production readiness.
  5. 5
    Leadership and Communication Round — Interview with a hiring manager or team lead evaluating your ability to lead cross-functional projects, communicate with diverse stakeholders, and make decisions under pressure. Discuss how you've influenced product or research decisions through field feedback.
  6. 6
    Executive Conversation — Optional final conversation with a senior leader at OpenAI to discuss your vision for the role, interest in OpenAI's mission, and how you approach building systems that benefit end users.
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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
FastAPIReact or Vue.jsNode.js/ExpressDjango
Databases
PostgreSQLRedisVector Databases
Tools
Git and GitHubDockerKubernetesCI/CD PipelinesMonitoring and ObservabilityAPI Documentation
Other
OpenAI API PlatformPrompt EngineeringLLM Evaluation FrameworksAgile and Project Management

Interview Guides

5 guides available for OpenAI

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