Engagement Manager, Life Sciences

🕒 October 14

🇬🇧 United Kingdom – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👔 Manager

🇬🇧 UK Skilled Worker Visa Sponsor

This company has sponsored UK Skilled Worker visas in the past.

👻 Ghost score 11%

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Domino Data Lab

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2013

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

💰 Series F on 2022-06

Artificial Intelligence • Enterprise • SaaS

Domino Data Lab is a company that empowers AI-driven enterprises to build and manage AI at scale through its Enterprise AI Platform. The platform provides an integrated experience for model development, MLOps, collaboration, and governance, enabling global enterprises to innovate across various sectors. Domino supports better medicinal development, productive agriculture, and competitive product creation. Established in 2013 and backed by notable investors like Sequoia Capital and NVIDIA, Domino enables companies to optimize AI deployment effectively.

📋 Description

• Own customer programs end-to-end from contract signature through expansion • Act as program manager with clear ownership, milestones, and operating cadence • Partner with account teams to scope engagements for excellent delivery • Direct Forward Deployed Engineers and Integration & Architecture teams for customer engagements • Allocate delivery capacity and keep programs on track across milestones, stakeholder communication, and account health • Build trust with C-suite sponsors and data scientists • Lead solutioning conversations connecting Domino’s AI capabilities to customer leadership outcomes • Drive rollout, enablement, and change management to ensure adoption • Identify, qualify, and route new use cases and expansion opportunities with customer success and sales • Convert customer field intelligence into product feedback, escalations, and commercial signals

🎯 Requirements

• 4–8 years in an enterprise customer-facing discipline such as implementations, consulting, technical program management, or product • Background in life sciences is a meaningful advantage • Ability to reshape customer requests into appropriate solutions and push back on original scope when necessary • Comfort working with ambiguity and problems that are not fully formed • Ability to turn unstructured executive conversations into executable plans • Knowledge of how enterprise data science teams build, scale, and govern models • Real delivery ownership across full cycles, not merely coordination • Technical fluency across software architecture, predictive modeling, and agentic systems • Ability to get hands-on technically and learn new domains quickly • Solutions-oriented approach, escalating with recommendations • Ability to use AI to work faster and better

🏖️ Benefits

• Encouragement of applications from people of all backgrounds, genders, ethnicities, abilities, and sexual orientations • Environment of teaching and learning with tools needed for success

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