OpenAI

Technical Deployment Lead, Forward Deployed Engineering - Zurich

OpenAI2 weeks ago
Location

Zurich, Switzerland

Type

Full Time

Salary

USD 250,000 – 350,000

Level

Lead

Role

Lead

Posted

Jul 10, 2026

Full TimeLead

The role

Summary

OpenAI seeks a Technical Deployment Lead to own end-to-end delivery of complex AI systems to enterprise customers in the Forward Deployed Engineering team. This high-autonomy, technical leadership role requires 7+ years of customer-facing delivery experience, deep expertise in AI/LLM systems, and the ability to translate business objectives into executable technical plans while managing cross-functional teams and driving measurable customer impact.

What you'll do

Own End-to-End Technical Delivery Planning: Define and manage comprehensive technical delivery roadmaps across multiple interdependent workstreams. Translate business objectives and customer outcomes into structured technical plans with clearly defined milestones, dependencies, acceptance criteria, and sequencing strategies. Work collaboratively with Forward Deployed Engineers, Researchers, and customer teams to establish realistic timelines and resource allocation.
Drive Day-to-Day Engineering Execution: Run daily execution tracking and coordination across OpenAI FDE teams and customer engineering teams. Monitor progress against delivery milestones, identify and unblock impediments, make real-time trade-off decisions on scope and priority to protect critical path delivery. Maintain clarity on dependencies and sequencing to ensure smooth handoffs between teams and components.
Embed with Customer Teams for Production Deployment: Work embedded with customer organizations to map existing workflows, identify integration points, and understand operational constraints. Design and shape tools, integrations, and solution architectures that align with customer processes. Lead comprehensive onboarding programs, change management initiatives, and adoption strategies to ensure successful production deployment and sustained usage.
Partner with Product and Research Functions: Serve as the voice of customer needs and field signals to Product and Research teams. Ensure platform components and research initiatives align with deployment timelines and customer requirements. Provide regular feedback on product roadmap priorities, architectural decisions, and research directions based on real-world deployment learnings and customer outcomes.
Codify Solution Patterns and Evaluation Frameworks: Extract reusable patterns, best practices, and architectural templates from successful deployments. Document integration approaches, configuration strategies, and operational playbooks to accelerate future customer engagements. Package field signals, customer success metrics, and lessons learned into actionable insights that improve product offerings and model capabilities.
Establish Value Cases and Measure ROI: Define impact hypotheses, baseline metrics, and key performance indicators aligned with customer business objectives before deployment. Execute pre-deployment and post-deployment measurement programs to validate outcomes and quantify business value. Present ROI findings and adoption metrics to executive sponsors and internal stakeholders to demonstrate deployment success and drive continued investment.

What we look for

Technical

Strong Technical Fluency Across System ArchitectureAbility to understand and discuss system-level architecture, cloud infrastructure patterns, distributed systems design, and integration strategies. Comfortable pressure-testing technical approaches, evaluating trade-offs between performance, scalability, maintainability, and cost. Strong fundamentals in software engineering principles and system design.
API Integration and Data Pipeline DesignDeep understanding of REST APIs, SDK integration patterns, data pipeline construction, and enterprise integration architecture. Experience designing and implementing customer-specific integrations with third-party systems, databases, and legacy infrastructure. Knowledge of ETL processes and data governance considerations.
Cloud Platforms and InfrastructureWorking knowledge of major cloud platforms (AWS, Azure, Google Cloud) and their services. Understanding of containerization (Docker/Kubernetes), serverless architectures, observability stacks, and infrastructure-as-code principles. Ability to evaluate deployment options and infrastructure trade-offs.
Production Operations and MonitoringFamiliarity with production deployment strategies, infrastructure monitoring, logging, alerting systems, and incident response procedures. Understanding of SLAs, uptime requirements, and operational best practices for mission-critical systems. Experience with observability tools and operational runbooks.

Education

Bachelor's Degree in Computer Science or Related FieldFormal education in computer science, software engineering, mathematics, or related technical discipline. Foundation in computer science principles, algorithms, and system design fundamentals essential for technical credibility and architectural discussions with engineering teams.

Experience

7+ Years of Customer-Facing Technical LeadershipDemonstrate extensive experience leading large-scale, complex technical engagements with enterprise customers. Track record of managing high-stakes deployments where customer outcomes directly depend on tight technical coordination, rapid decision-making, and flawless execution. Experience coordinating across cross-functional teams including engineers, product managers, and customer teams.
Proven AI/LLM Systems DeliveryHands-on experience shipping production AI and Large Language Model systems. Deep familiarity with AI solution patterns, LLM integration approaches, common production pitfalls, and architectural best practices. Understanding of RAG (Retrieval-Augmented Generation), prompt engineering, fine-tuning strategies, and model deployment considerations in enterprise environments.
Enterprise Sales Engineering or Customer Success LeadershipBackground in technical delivery leadership roles within enterprise software, cloud services, or consulting firms. Experience building strong customer relationships, translating technical capabilities into business value, and leading implementations that require coordination between sales, engineering, and customer teams.
Domain Expertise in Major SectorsDemonstrated 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, and operational constraints that inform solution architecture and deployment strategies.

Skills

Required skills

Technical Project ManagementExpert-level ability to plan, coordinate, and execute complex technical projects across multiple teams. Skilled at breaking down ambiguous problems into well-scoped work items, managing dependencies, and making sequencing decisions that optimize delivery. Comfortable using project management methodologies and tracking tools to maintain clarity and accountability.
Customer Problem SolvingAbility to deeply understand customer workflows, pain points, and business objectives. Translate vague customer needs into concrete technical requirements and solution architectures. Comfort working embedded with customer teams to rapidly prototype solutions and iterate based on feedback.
Cross-Functional Leadership and InfluenceProven ability to lead without direct authority, influencing engineers, researchers, customer leaders, and executives. Strong communication skills for translating between technical and business languages. Comfortable building trust quickly and earning credibility with diverse stakeholder groups.
System Design and ArchitectureStrong ability to design end-to-end system architectures that meet customer requirements while accounting for scalability, reliability, and operational constraints. Comfortable making architectural trade-offs and justifying decisions to technical teams.
Executive Communication and PresenceAbility to synthesize complex technical information into clear, compelling narratives for executive audiences. Strong presentation skills and comfort communicating with C-level stakeholders. Ability to convert strategy into digestible day-to-day technical execution plans.
Ambiguity Navigation and Problem SimplificationThrive in high-ambiguity environments with incomplete information and competing priorities. Strong ability to identify signal amid noise, break down complex problems into manageable components, and drive rapid iteration toward solutions. Comfortable making decisions with imperfect information.

Nice to have

Consulting BackgroundExperience in management consulting or technical consulting firms where you managed complex engagements, coordinated across multiple client and internal teams, and drove measurable business outcomes. Familiarity with consulting methodologies and client management practices.
AI/Generative AI Product LeadershipBackground in AI product management, AI product marketing, or AI solution architecture. Familiarity with LLM capabilities, limitations, and realistic use cases. Understanding of AI adoption challenges and change management considerations unique to AI deployments.
Enterprise Software Sales EngineeringExperience in technical sales engineering, solution architecture, or sales enablement roles for enterprise software companies. Demonstrated ability to work with sales teams, understand customer buying processes, and articulate technical value to decision-makers.
Change Management and Organizational AdoptionFormal training or demonstrated expertise in change management methodologies, organizational adoption strategies, and user training program design. Experience leading large organizational transformations or technology rollouts.
Metrics Design and Data AnalysisAbility to design meaningful KPIs, establish baseline measurements, and conduct rigorous pre/post deployment analysis. Comfort with data analysis, statistical significance testing, and communicating results to executives.
DevOps and Infrastructure AutomationWorking knowledge of DevOps practices, infrastructure-as-code, CI/CD pipelines, and automation frameworks. Understanding of containerization, orchestration, and deployment automation tools.

Compensation & benefits

Salary

USD 250,000 – 350,000 (annual)

Stock options

Available

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
PythonTypeScript/JavaScriptSQL
Frameworks
LangChain / LlamaIndexFastAPI / FlaskReact / Vue.js
Databases
PostgreSQLVector Databases (Pinecone, Weaviate, Milvus)Redis
Tools
OpenAI API / GPT ModelsGit / GitHubDocker / KubernetesAWS / Google Cloud Platform / AzureMonitoring and Observability Tools (Datadog, New Relic, Prometheus)Jira / Asana / Linear
Other
LLM Deployment PatternsEnterprise Architecture and IntegrationCI/CD and Deployment AutomationInformation Security and Compliance

Interview Guides

5 guides available for OpenAI

Apply Now

On this page