Engagement Manager, Life Sciences

About the role

Domino's Solutions team is the customer-facing engine behind how leading enterprises build, scale, and govern AI-powered applications—solving real business challenges, not just deploying technology. This role sits within Customer Engineering, which owns everything after the deal closes: adoption, implementation, expansion, and the kind of delivery that makes customers renew and grow.

Responsibilities

• Own the customer program end-to-end: from contract signature through expansion. You're accountable for outcomes, not activities, with clear milestones and a cadence that keeps everyone moving as the program manager.
• Partner with the account team to ensure every engagement is scoped for excellence, bridging what is sold with what can be executed.
• Direct the delivery pod (Forward Deployed Engineers and Integration & Architecture teams) for customer engagements. Allocate capacity where it creates the most value and keep programs on track across milestones, stakeholder communication, and account health.
• Earn trust at every level: from C-suite sponsors to data scientists running models in production. Close the gap between strategic intent and day-to-day delivery.
• Lead solutioning conversations: connect how Domino builds, scales, and governs AI to the outcomes customer leadership cares about. Operate as a peer, not a vendor.
• Drive adoption: rollout, enablement, and change management so what your team ships gets used, not shelved.
• Turn customer engagements into growth in partnership with customer success and sales—proactively uncovering new use cases and expansion opportunities, qualifying them, and routing them back to internal teams to fuel pipeline.
• Be the customer's voice inside Domino: convert field intelligence into product feedback, escalations, and commercial signals that make the broader team smarter.

Requirements

• 3–5 years in an enterprise customer-facing discipline: implementations, consulting, technical program management, or product. Caliber and complexity matter more than the title.
• Background in life sciences where reproducibility, auditability, and compliance are non-negotiable is a meaningful advantage.
• Move before the problem is fully formed: comfortable when the customer can't yet articulate what's wrong and treat ambiguity as the starting point.
• Turn unstructured executive conversations into executable plans: connecting model development, deployment, and governance without losing what actually matters.
• Know enough about how enterprise data science teams build, scale, and govern models to ask the right questions before the customer knows they need to answer them.
• Real delivery ownership across full cycles, not just coordination. Hold an execution rhythm, hold a position when things get hard, and avoid creating bureaucracy.
• Technically fluent across software architecture, predictive modeling, and agentic systems: able to get hands-on when it matters and learn new domains fast.
• Solutions-oriented by default. Escalate with a recommendation, not just a problem, and leverage AI to do all of it faster and better.

Benefits

• Equity
• Company bonus or sales commissions/bonuses
• 401(k) plan
• Medical, dental, and vision benefits
• Wellness stipends

Pay

Total Compensation Range: $180,000—$245,000 USD (On Target Earnings for sales roles, including base salary and commissions/bonuses). This range will be narrowed during the interview process based on experience, qualifications, and location.