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Engagement Manager, Life Sciences

AI Summary
Domino Data Lab is seeking an Engagement Manager to lead enterprise AI customer programs in the life sciences sector from contract signature through adoption, expansion, and renewal. The role combines program leadership, technical solutioning, stakeholder management, change management, and commercial awareness. The manager will direct delivery teams, translate executive priorities into executable plans, and connect customer feedback to internal product and commercial teams. Candidates need 4–8 years of experience in consulting, implementations, technical program management, or a similar enterprise-facing discipline, with life sciences experience strongly preferred. Strong fluency in software architecture, predictive modeling, AI governance, and regulated delivery environments is important.
Remote from
UK
Salary
Undisclosed
Employment
Full Time
Experience
Director
Published
Apply before
12 Dec 2026
Listing views
35
Application actions
2
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Opportunity details

About this role.

Who we are

At Domino, we build solutions that help the largest, highly regulated organizations adopt AI to accelerate mission-critical use cases. Our platform integrates a streamlined model and app development environment, advanced model, agent, and app hosting capabilities, and novel governance capabilities providing regulator-ready AI at scale. Our customers — like Johnson & Johnson, GSK, Bristol Myers, UBS, FINRA and the US Navy — are using our software to solve some of the most important challenges in the world, such as developing new medicines, securing our financial markets, or protecting our country. Backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake and other leading investors, we have been in business for over a decade but are still a small team operating with the spirit of a startup. In the world of AI today, we believe that the future is still being invented — and we want to be the ones building it. For more information, visit www.domino.ai

What we are building

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. Solutions Engineering earns technical credibility before the deal closes. Customer Engineering, where this role lives, owns everything after: adoption, implementation, expansion, and the kind of delivery that makes customers renew and grow. Global Support and SRE keeps it all running at the level enterprise customers depend on. Three functions, one relentless motion, and a team that earns its reputation on what it ships, not what it scopes.

What your impact will be

  • Own the customer program end-to-end: from contract signature through expansion. You’re accountable for outcomes, not activities, and every engagement you lead has a single owner (you), clear milestones, and a cadence that keeps everyone (internally and externally) moving as the program manager.
  • Partner with account team to ensure every engagement is scoped to be delivered with excellence, bridging what is sold with what can be executed.
  • Direct the delivery pod (our Forward Deployed Engineers and Integration & Architecture teams) for customer engagements. Put 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 the data scientists running models in production. You close the gap between strategic intent and day-to-day delivery.
  • Lead the room in solutioning conversations: connect how Domino builds, scales, and governs AI to the outcomes customer leadership actually cares about. You operate as a peer, not a vendor.
  • Make adoption real: drive 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.

What we look for in this role

  • 4–8 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.
  • Comfortable owning the what, not just the when: you can reshape a customer’s ask into the right solution, even when that means pushing back on the original scope
  • You move before the problem is fully formed: comfortable when the customer can’t yet articulate what’s wrong and treating ambiguity as the starting point.
  • You turn unstructured executive conversations into executable plans: connecting model development, deployment, and governance without losing what actually matters.
  • You 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 coordination. You hold an execution rhythm, hold a position when things get hard, and don’t create bureaucracy to do it.
  • 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. You escalate with a recommendation, not just a problem, and reach for AI to do all of it faster and better.

What we value

  • We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply
  • We value a growth mindset. High-performing creative individuals who dig into problems and see the opportunities for success
  • We believe in individuals who seek truth and speak the truth and can be their whole selves at work
  • We value all of you that believe improving is always possible. At Domino, everything is a work in progress – we can do better at everything
  • We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company

#LI-Remote

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a high-complexity, customer-facing leadership role spanning technical delivery, executive alignment, adoption, and expansion. It requires independent judgment in ambiguous, regulated enterprise AI engagements.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$125,000
US market range (per year)$105k–$150k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. The annual figures are estimated USD market compensation for a mid-level to senior enterprise engagement manager working with regulated AI and life sciences customers; the yearly period is inferred from the full-time professional role.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you take ownership of a customer engagement after contract signature?

I would begin by validating the intended business outcomes, scope, success metrics, stakeholders, technical dependencies, and risks. I would then establish a delivery plan with clear milestones, ownership, governance cadence, and an escalation path, while maintaining regular communication with both customer and internal teams.

Describe how you would handle a customer request that cannot be delivered within the original scope.

I would clarify the underlying business need and assess the technical, timeline, and capacity implications with the delivery team. I would present practical options, such as a phased approach, a scoped change request, or an alternative solution, with a clear recommendation rather than simply escalating the problem.

How do you drive adoption after an AI solution has been implemented?

I focus on adoption planning from the start by identifying user groups, workflow changes, enablement needs, and measurable usage outcomes. After launch, I would monitor adoption signals, gather feedback, address blockers quickly, and partner with customer sponsors to reinforce accountability for business value.

What is important when managing AI programs for life sciences customers?

Life sciences programs require strong attention to reproducibility, auditability, validation, governance, data controls, and compliance expectations. I would ensure that delivery decisions, model lifecycle practices, and stakeholder communications reflect those requirements while still maintaining momentum toward the customer’s scientific and operational goals.

How would you identify expansion opportunities within an existing account?

I would listen for unmet business needs, adjacent use cases, adoption barriers, and strategic initiatives during delivery and executive reviews. I would qualify each opportunity against customer value, technical feasibility, and stakeholder sponsorship, then work with customer success and sales to develop the appropriate next step.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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