Forward Deployed Engineer, Life Sciences

• Design and ship production systems around models, owning integrations, data provenance, reliability, and on-call readiness across research, clinical, and operational workflows
• Lead discovery and scoping from pre-sales through post-sales, translating ambiguous workflow needs into hypothesis-driven problem framing, system requirements, and an execution plan with measurable endpoints
• Define and enforce launch criteria for regulated contexts, including validation evidence, audit readiness, outcome metrics, and drive delivery until we demonstrate sustained production impact
• Build in sensitive scientific data environments where auditability, validation, and access controls shape architecture, operating procedures, and failure handling
• Run evaluation loops that measure model and system quality against workflow-specific scientific benchmarks and use results to drive model and product changes
• Distill deployment learnings into hardened primitives, reference architectures, validation templates, and benchmark harnesses that scale across regulated life sciences environments

• 5+ years of software/ML engineering or technical deployment experience with customer-facing ownership in biotech, pharma, clinical research, or scientific software
• PhD, MS, or equivalent applied experience in a life sciences relevant field encouraged
• Have owned customer GenAI deployments end-to-end from scoping through production adoption, and improved them through evaluation design, error analysis, and iterative evidence generation
• Have delivered AI systems in trial design, regulatory writing, or scientific operations where validation strategy, auditability, compliance constraints, and reviewer expectations shaped system design and rollout
• Communicate clearly across scientific, clinical, model research, technical, and executive audiences
• Apply systems thinking with high execution standards

relocation assistance