Forward Deployed Engineer

About Manifold

Manifold is the AI platform for life sciences, accelerating life-changing medicines to patients. Our products speed up workflows in areas from target identification and clinical development to market access and precision medicine in the clinic, while maintaining the governance life sciences requires. Global companies and premier research institutions use Manifold to operate faster and more effectively. Backed by leading investors including Reach Capital, TQ Ventures, Calibrate Ventures, SilverArc Capital, and Industry Ventures, Manifold serves tens of thousands of users across hundreds of organizations globally.

About the role

Manifold is hiring Forward Deployed Engineers (FDEs) to work at the intersection of AI, data infrastructure, and life sciences. Our customers are working on life changing medicines that affect real patients, and the faster their data becomes usable, the faster the science moves. In this high-impact role, you will work directly with scientists and clinicians across biopharma, academic research, and health systems to put Manifold's platform to work with their data, from scoping through to production.

As an FDE, you'll be the primary technical and scientific contact for your accounts. An Implementation Manager owns the customer relationship, and you own the technical and scientific work inside it. You'll work as one team for our customers alongside Implementation, Product, and Account Management. You'll field questions about the whole platform, including parts you didn't build, and you'll often be the only Manifold person on the call. We expect our FDEs to operate autonomously, thrive under ambiguity, and represent Manifold at the highest level in customer environments, which means earning our customer’s trust in the first conversation and owning the path to a successful outcome.

What You'll Do

• Scope and architect end-to-end solutions on Manifold's platform, and recommend whether a problem needs configuration, a custom build, or a self-service path
• Configure and implement the platform for each customer, and build what it needs alongside: data pipelines, agent configuration, process automation, and domain-specific tooling
• Own delivery from onboarding and pilot through to production, working in the customer's environment with their data, and quickly drive the engagement from ambiguous problem to working in production
• Run discovery sessions, demos, and end-user training, and support adoption after go-live
• Troubleshoot complex issues across infrastructure, data, and application layers
• Identify repeatable patterns, playbooks, and tooling that accelerate future deployments, and help set the standard for what a great deployment looks like