Principal AI Engineer

Principal AI Engineer — Velsera

AI Platform & Enablement · Reports to the CTO · Senior individual contributor

About the role

Velsera builds software and infrastructure for precision medicine — research platforms, clinical and diagnostic applications, and the systems that keep them running in regulated environments. We are adding AI capability across that portfolio and inside our own operations: governed model access, self-hosted and managed LLM serving, evaluation and audit, and integration into the products and business processes people already depend on.

This is a deliberately broad role. You will be deployed where the highest-value AI work is at the time — a customer-facing product capability in one quarter, an internal enterprise workflow in the next, a strategic account or funded program after that. The mandate stays the same wherever you land: design and ship production AI systems that hold up under real compliance requirements, work across AWS, Azure, and GCP, and leave behind reusable patterns rather than one-off builds.

You will set technical direction for what is expected to grow into an AI platform and enablement team.

What you'll work on

• Build a governed model access layer — self-hosted open-weight models, cloud-managed models (Bedrock, Vertex AI, Azure OpenAI), and customer- or partner-supplied models — designed to be consumed by more than one product or business function.
• Integrate AI capabilities into product experiences and enterprise workflows across batch, interactive, and agentic patterns.
• Establish the patterns everyone else reuses: evaluation, versioning, approvals, audit trails, cost control, guardrails, and safe rollout and rollback.
• Partner with product, engineering, security, QARA/compliance, IT, and scientific and commercial teams to introduce AI-native architectures that people can actually adopt.
• Move between assignments as business priorities shift, and make what you build in one