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Forward Deployed Engineer, Life Sciences

Job in Berlin, Coos County, New Hampshire, 03570, USA
Listing for: Domino
Full Time position
Listed on 2026-10-05
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 150000 - 210000 USD Yearly USD 150000.00 210000.00 YEAR
Job Description & How to Apply Below
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  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 (Use the "Apply for this Job" box below)..ai

What

we are building

The Customer Engineering Solutions Team at Domino is the primary delivery engine that sits inside the walls of the world’s most regulated and demanding organizations, including Fortune 100 pharmaceutical and life sciences leaders.

A Forward Deployed Engineer is a software engineer with solutions instincts, embedded in a customer's environment, building AI workflows on Domino that the customer couldn't have built as fast, or as well, without you. We write production code, ship it inside the customer's environment, and stay until Domino is fundamentally part of how they work.

In the Life Sciences vertical, we build and deploy production-grade AI solutions that solve real, high-impact use cases, ranging from specialized AI inferencing workflows, custom cloud and data integrations, and interactive applications, to frontier solutions around Statistical Computing Environments (SCE), clinical CRM, etc. Our work provides the ultimate proof point that Domino is a comprehensive AI business solutions platform.

What your impact will be

In your first year, your impact will unfold across key milestones as you take ownership of strategic life sciences accounts:

  • Day 0-30 (Onboard & Shadow): You will be given the resources to master Domino platform mechanics and learn core user/admin functionalities. You will closely shadow the customer’s environment, pairing with a senior FDE to learn the client’s unique data, tooling stack, and commercial objectives.
  • By Month 6 (Full Ownership): You will step into full customer ownership across your engagements, executing independently against a prioritized backlog managed by your partner Engagement Manager (EM). You will build and deploy production-grade solutions across the entire MLOps lifecycle (development, deployment, and monitoring) while actively advising data science teams on Domino best practices.
  • By Year 1 (Strategic Scale & Leverage): You will lead and advise on key accounts, serving as a trusted advisor to technical and business stakeholders alike. You will author reusable playbooks, integration templates, and deployment guides for our shared knowledge base, measurably lifting the delivery speed of the entire FDE practice. Additionally, you will translate field intelligence into critical product feedback, routing platform signals to our SRE, Support, and Product teams to shape Domino’s roadmap.
What

we look for in this role
  • We are looking for a sharp, action-first engineer who possesses a unique blend of deep technical grit and customer empathy.
  • Core Technical Stack: Strong engineering roots with deep proficiency in Python (primary), alongside familiarity with SQL, R, and Bash.
  • Cloud & Infrastructure: Experience with Kubernetes and managed K8s solutions (such as EKS, AKS, or GKE), Docker, and…
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