Implementation Manager

Drug development is one of the most data-intensive endeavors in history, yet scientists spend more time finding and cleaning data than using it. Bioprocess data is high-frequency, multi-source, and scattered across systems that rarely talk to each other. We make it usable, and our AI agent lets scientists query their full experimental history, catch deviations in real time, and inform million-dollar manufacturing decisions.

This is a place for builders - people who want to own hard problems, ship fast, and work with others who hold themselves to a high bar.

The role

You’ll be Invert’s first Implementation Manager and a founding member of the CX team. You own customer rollouts end-to-end: requirements and solution design, configuration and integrations, testing, UAT, and user onboarding. Our customers’ environments are complex, and you’re the person translating their workflows into a working Invert deployment.

Once customers are live, you stay with them - driving adoption, surfacing expansion, advocating internally, and making sure they keep realizing value.

What you’ll do

• Own implementations from kickoff to go-live: scope, timeline, quality, across customer and Invert teams
• Lead requirements and design workshops with scientists and IT; translate bioprocess workflows into Invert deployments
• Partner with Engineering on integrations; prototype and oversee delivery where needed
• Run UAT, train users, and act as trusted advisor through go-live and beyond
• Own live accounts: usage health, adoption, renewal posture. Use usage data to find patterns, risks, and expansion
• Run business reviews that tie Invert usage to the customer’s process development and manufacturing goals
• Be the voice of the customer to Product and Engineering

• 5-7 years in implementation, customer success, or account management at a B2B SaaS company
• Scientific or regulated-industry SaaS background - bioprocess, LIMS, lab informatics, manufacturing data, or similar. Bioprocess fluency is a plus; willingness to go deep on it fast is required.
• Comfort with the technical layer: APIs, data schemas, historians, bioreactor data systems, cloud data infrastructure
• Track record running multi-stakeholder implementations end-to-end
• B.S. in a STEM field