Forward Deployed Engineer - Stockholm

OpenAI OpenAI · AI Frontier · Stockholm, Sweden · Model Deployment for Business

This role focuses on deploying OpenAI's frontier AI models into production systems for strategic customers, involving end-to-end ownership from discovery and design to rollout and adoption. The engineer will build full-stack systems, contribute code, and codify working patterns into reusable tools, with success measured by production adoption, workflow impact, and feedback that influences product and model roadmaps. The role requires strong engineering and deployment experience, particularly with LLMs or generative models, and the ability to manage complex projects in ambiguous environments.

What you'd actually do

  1. Own technical delivery across multiple deployments from first prototype to stable production
  2. Build full-stack systems that deliver customer value and sharpen how we learn
  3. Embed closely with customer teams, understand their needs, and guide adoption of what you build
  4. Scope work, sequence delivery, and remove blockers early
  5. Make trade-offs between scope, speed, and quality; adjust plans to protect delivery

Skills

Required

  • 5+ years of engineering or technical deployment experience
  • customer-facing work
  • scoped and delivered complex systems in fast-moving or ambiguous environments
  • production-grade code across frontend and backend using Python, JavaScript, or comparable stacks
  • built or deployed systems powered by LLMs or generative models
  • understand how model behaviour affects product experience
  • Simplify complexity and make fast, sound decisions under pressure
  • Communicate clearly with engineers, product teams, and customer stakeholders
  • Spot risks early and adjust without slowing down

Nice to have

  • Python
  • JavaScript

What the JD emphasized

  • production adoption
  • measurable workflow impact
  • eval-driven feedback
  • product and model roadmaps
  • customer delivery
  • production systems
  • frontier models
  • end-to-end deployments
  • system design
  • production rollout
  • built or deployed systems powered by LLMs or generative models

Other signals

  • customer delivery
  • production systems
  • frontier models
  • end-to-end deployments
  • system design
  • production rollout
  • measurable workflow impact
  • eval-driven feedback
  • product and model roadmaps