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Forward Deployed Engineer, Life Sciences

Domino Data Lab

Remote · United States$15,417–18,333 gross/mofull-timeDomino Data Lab Careers

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.

Responsibilities

  • 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…
  • 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…
  • 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 cloud architecture (AWS, Azure, or GCP). You should be capable of troubleshooting networking, compute, and platform issues.
  • AI & MLOps Experience: A proven track record of delivering machine learning workflows, model deployment/monitoring, GPU workloads, and generative AI or agent frameworks.
  • Regulated Environment Navigation: Experience operating within, or consulting for, highly regulated or constrained environments. You can expertly navigate multi-factor constraints like strict compliance rules, data security hurdles, and infrastructure limits.

Languages

    Work format
    Remote
    Seniority
    Mid
    Posted
    2 Jul 2026
    Last verified
    In the last 5 days

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