Forward Deployed Engineer (fde), Life Sciences - Nyc

OpenAI OpenAI · AI Frontier · New York, NY · Model Deployment for Business

Forward Deployed Engineer (FDE) for Life Sciences at OpenAI, focusing on end-to-end deployment of AI models in regulated environments. This role involves partnering with customers to translate workflow needs into production systems, defining launch criteria, and using evaluation results to improve models and product roadmaps. Requires strong software/ML/deployment engineering experience and customer-facing ownership in biotech/pharma.

What you'd actually do

  1. Own deployments from initial scoping through production adoption, including technical decisions, sequencing, and launch readiness.
  2. Partner with customers and internal teams to frame problems, define scope, and translate ambiguous workflow needs into system requirements and measurable endpoints.
  3. Define launch criteria for regulated contexts, including validation evidence, outcome metrics, and acceptance thresholds tied to production use.
  4. Enforce operating standards for auditability, traceability, and inspection readiness in the systems you ship.
  5. Design evals that measure model and system quality against workflow-specific scientific benchmarks and acceptance criteria.

Skills

Required

  • 6+ years of software, ML/AI, or deployment engineering experience
  • Customer-facing ownership in biotech, pharma, clinical research, scientific software, or adjacent technical domains
  • Operated as a senior engineer, tech lead, or deployment owner
  • Owned customer GenAI deployments end-to-end
  • Improved deployed systems through eval design, error analysis, and evidence generation
  • Delivered AI systems in workflows such as discovery, clinical development, regulatory writing, submissions, or scientific operations
  • Clear communication across scientific, clinical, model research, technical, and executive audiences
  • Systems thinking and engineering judgment

Nice to have

  • Experience with frontier models in regulated environments

What the JD emphasized

  • regulated environments
  • production adoption
  • evals
  • launch criteria
  • auditability
  • traceability
  • validation strategy
  • compliance constraints

Other signals

  • Deploying production AI systems
  • Working with customers in regulated environments
  • Defining repeatable system patterns and evals