Forward Deployed Engineer

Collate’s Forward Deployed Engineering team partners with Fortune 100 life sciences organizations to deploy production AI systems across their most critical document and regulatory workflows.

We operate at the boundary of customer deployment and core platform development — using early engagements to define repeatable solution patterns, evaluation standards, and agentic architectures that scale across the industry.

You’ll join as one of the first members of this team and operate with the autonomy of a founder.

Your job is to go deep on the hardest problems at our most strategic customers — medical writers, regulatory affairs teams, clinical operations, and development engineers — identify what’s structurally broken, and build production AI systems that solve it.

What you build shapes the Collate platform for every customer that comes after you.

Collate’s Forward Deployed Engineering team partners with Fortune 100 life sciences organizations to deploy production AI systems across their most critical document and regulatory workflows.

We operate at the boundary of customer deployment and core platform development — using early engagements to define repeatable solution patterns, evaluation standards, and agentic architectures that scale across the industry.

You’ll join as one of the first members of this team and operate with the autonomy of a founder.

Your job is to go deep on the hardest problems at our most strategic customers — medical writers, regulatory affairs teams, clinical operations, and development engineers — identify what’s structurally broken, and build production AI systems that solve it.

What you build shapes the Collate platform for every customer that comes after you.

• Lead end-to-end deployments of Collate’s AI systems inside life sciences organizations — owning scoping, build, and production rollout from first conversation to measurable workflow impact.
• Go deep before you write a line of code. Embed with customer teams — medical writers, regulatory affairs, clinical ops — to understand what’s structurally broken, where the highest concentration of unsolved value lives, and what’s actually buildable.
• Design and ship production AI systems — document generation agents, agentic workflows, data pipelines — that integrate with customers’ existing infrastructure and regulatory environments.
• Define and run eval loops that measure system quality against workflow-specific benchmarks — acceptance criteria, output accuracy, reviewer expectations — and use that signal to improve deployed systems over time.