OpenAI

Technical Deployment Lead, Forward Deployed Engineering - Paris

OpenAI2 weeks ago
Location

Paris, France

Type

Full Time

Salary

EUR 180,000 – 260,000

Level

Senior

Role

Lead

Posted

Jul 10, 2026

Full TimeSenior

The role

Summary

OpenAI seeks a Technical Deployment Lead for its Forward Deployed Engineering team based in Paris to own end-to-end delivery of AI/LLM systems to enterprise customers. This high-autonomy role requires translating complex business outcomes into executable technical plans, coordinating cross-functional teams (FDEs, researchers, customer engineers), and embedding with customers to ensure adoption and measurable impact. Ideal candidates bring 7+ years of customer-facing technical delivery leadership with proven expertise in shipping AI systems and managing high-stakes, ambiguous enterprise engagements across major industry verticals.

What you'll do

Own Technical Delivery Planning: Define and execute comprehensive technical roadmaps for multiple interdependent workstreams. Translate business objectives and customer outcomes into detailed delivery plans with clear milestones, dependency mapping, acceptance criteria, and success metrics. Maintain visibility across all project phases from 0→1 prototypes through MVP and production scale.
Drive Day-to-Day Engineering Execution: Lead daily technical delivery operations across OpenAI Forward Deployed Engineers, researchers, and customer engineering teams. Track progress against milestones, unblock dependencies in real-time, sequence work intelligently, and make critical trade-offs between scope and priority to protect the critical path and ensure on-time delivery.
Embed with Customer Teams and Drive Adoption: Work closely with enterprise customers to map their existing workflows, understand success criteria, and shape AI/LLM solution design and integration requirements. Lead technical onboarding, change management, and adoption initiatives to ensure deployed systems become critical to customer operations and deliver sustained value.
Partner with Product and Research Functions: Collaborate with OpenAI product and research teams to ensure platform components, model improvements, and research workstreams align with and land in time to support customer deployment timelines. Serve as liaison translating field needs back to internal stakeholders to influence roadmap prioritization.
Codify Patterns and Extract Reusable Solutions: Document and package repeatable solution patterns, evaluation frameworks, and integration templates from customer deployments. Extract and communicate field signals, customer insights, and architectural lessons learned to improve product capabilities and inform model development priorities.
Own Value Measurement and ROI Accountability: Define impact hypotheses, establish baseline metrics, and set key performance indicators (KPIs) aligned with customer business outcomes. Conduct pre- and post-deployment measurement, quantify ROI impact, prepare executive summaries, and report value realization to customer sponsors and leadership.
Make Strategic Technical Decisions Under Pressure: Evaluate architectural trade-offs, technology choices, and integration approaches in high-ambiguity environments. Demonstrate technical judgment in pressure situations, simplify complex problems, and make binding decisions that balance customer needs, technical constraints, and delivery timelines.
Bridge Technical and Business Leadership: Translate complex technical trade-offs, architectures, and constraints into clear business language for executive stakeholders. Convert strategic business objectives into actionable technical execution plans, maintaining executive presence and credibility with C-level customer leadership.

What we look for

Technical

AI/LLM Systems Architecture and IntegrationDeep understanding of large language model (LLM) solution patterns, production deployment architectures, fine-tuning approaches, and API integration methodologies. Experience with prompt engineering, RAG (Retrieval-Augmented Generation), and common integration pitfalls in production AI systems.
Enterprise Systems IntegrationExpertise in integrating AI systems with complex enterprise infrastructure, data pipelines, existing software systems, and legacy architectures. Understanding of data governance, security, compliance requirements, and technical constraints in regulated industries.
Cloud Platform and DevOps FundamentalsSolid understanding of cloud infrastructure (AWS, Azure, GCP), containerization, deployment pipelines, monitoring, and observability. Ability to discuss infrastructure trade-offs, scalability considerations, and operational readiness with technical teams.
Technical Project Management and SequencingExpert-level ability to manage complex, multi-team technical projects with unclear scope, high interdependencies, and competing priorities. Proficiency in identifying critical paths, managing dependencies, making trade-off decisions, and maintaining unblocked execution.
Customer Technical Requirements ElicitationStrong capability to conduct discovery, map customer workflows, extract technical requirements from business problems, and translate ambiguous customer needs into executable technical specifications and design documents.

Education

Bachelor's Degree in Engineering, Computer Science, or Related FieldTechnical degree providing foundation in software architecture, systems thinking, and engineering principles. Advanced degrees or equivalent professional experience demonstrating deep technical expertise are valued but not required.

Experience

7+ Years Customer-Facing Technical Delivery LeadershipExtensive background leading customer-facing technical initiatives, ideally in customer success engineering, professional services, solutions architecture, or forward-deployed engineering roles. Demonstrated track record of high-stakes customer delivery where business outcomes directly depended on technical execution and tight coordination.
Large-Scale Complex Customer Engagements with AIProven success leading significant enterprise customer projects involving AI, machine learning, or advanced analytics systems. Experience navigating the unique complexity of AI deployment including model evaluation, uncertain timelines, and managing customer expectations around AI capabilities and limitations.
Cross-Functional Team Leadership and CoordinationDemonstrated ability to lead and coordinate across multiple functional teams (engineers, researchers, data scientists, customer teams) without direct management authority. Experience influencing outcomes through relationships, credibility, and technical judgment rather than hierarchical authority.
Operating in High-Ambiguity EnvironmentsTrack record of successfully operating in roles characterized by unclear requirements, emergent scope, dynamic priorities, and incomplete information. Ability to make progress despite ambiguity and simplify complex problems into actionable work.
Industry-Specific Domain ExpertiseDeep expertise in at least one major industry vertical such as healthcare, energy, financial services, semiconductors, manufacturing, or enterprise IT. Understanding of industry-specific workflows, compliance requirements, regulatory landscape, and business drivers to elevate solution framing.

Skills

Required skills

Technical Project ManagementExpert-level project planning, execution tracking, dependency management, risk mitigation, and stakeholder communication across complex technical initiatives with high stakes and ambiguity.
LLM and AI System FundamentalsComprehensive understanding of large language model capabilities, limitations, common application patterns (RAG, fine-tuning, agents), production deployment considerations, and integration approaches with enterprise systems.
Customer Engagement and Requirements GatheringExceptional ability to understand customer business objectives, map workflows, extract technical requirements, build customer trust, and maintain strong relationships with C-level executive sponsors throughout extended engagements.
Systems Thinking and Architectural DesignAbility to evaluate complex system architectures, understand tradeoffs between approaches, assess technical feasibility, and make informed decisions balancing multiple constraints (performance, cost, risk, timeline, compliance).
Execution Leadership and Problem-SolvingDrive to own outcomes end-to-end, exceptional judgment under pressure, ability to simplify complex problems, make binding decisions quickly, and maintain forward momentum despite obstacles and ambiguity.
Executive CommunicationAbility to translate technical complexity into clear business language, present recommendations to executive stakeholders with confidence, and communicate trade-offs and constraints in ways that drive business decision-making.

Nice to have

OpenAI API and Platform ExperienceHands-on experience building with OpenAI models (GPT-4, GPT-4o), fine-tuning APIs, embeddings, or other OpenAI platform services. Understanding of platform capabilities, limitations, and common integration patterns is advantageous.
Enterprise AI DeploymentExperience deploying AI/ML systems at enterprise scale, managing model governance, handling data security and compliance requirements, or navigating AI-specific deployment challenges in production environments.
Solutions Architecture or ConsultingBackground in solutions architecture, management consulting, or professional services with experience designing solutions to complex customer problems, presenting to executive teams, and managing solution delivery timelines.
Full-Stack Technical FluencyComfortable reading and discussing code, understanding backend/frontend tradeoffs, and engaging in technical depth across the software stack. Not required to be a practicing engineer, but deep technical credibility is valued.
International Business and Cross-Cultural CommunicationExperience working across geographies, time zones, and cultural contexts. Comfort with international business practices and ability to communicate effectively with diverse customer teams across regions.
Product Thinking and Strategic InfluenceAbility to think strategically about patterns across multiple customer engagements, synthesize insights into product recommendations, and influence executive-level roadmap decisions with compelling field evidence.

Compensation & benefits

Salary

EUR 180,000 – 260,000 (annual)

Stock options

Available

Benefits

Hybrid Work Arrangement

Flexible hybrid work model requiring 3 days in-office per week in Paris with flexibility for remote work. On-site presence provides collaboration benefits while maintaining work-life balance.

Relocation Assistance

Comprehensive support for relocating to Paris including moving expenses, housing assistance, visa sponsorship, and resources for international transition to help integrate smoothly.

Travel Budget and Support

Fully supported travel program with up to 50% travel anticipated (sometimes higher) to customer sites globally. Company covers all travel expenses and provides support for extended customer engagements.

Professional Development

Access to continuous learning resources, technical training, industry conferences, and opportunities to develop expertise in cutting-edge AI/LLM technologies and customer success methodologies.

Equity Compensation

Participation in OpenAI's equity program providing stock options or equity grants, aligning employee success with company growth and long-term value creation.

Comprehensive Health and Wellness

Health insurance coverage including medical, dental, and vision benefits. Wellness programs, mental health support, and fitness resources to support employee wellbeing.

Generous Time Off

Competitive vacation policies with flexibility, paid holidays, parental leave, and sabbatical options enabling work-life integration and long-term career sustainability.

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
PythonSQL
Frameworks
LangChainFastAPI / Django
Databases
Vector Databases (Pinecone, Weaviate, Milvus)PostgreSQL / Enterprise SQL
Tools
Git / Version ControlDocker / Container OrchestrationCloud Platforms (AWS / Azure / GCP)Monitoring and Observability Tools
Other
OpenAI API and GPT ModelsAI Safety and GuardrailingPrompt Engineering and Evaluation

Interview Guides

5 guides available for OpenAI

Apply Now

On this page