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 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.
Consultative Mindset: Exceptional communication skills across both technical and business audiences. You are comfortable running structured discovery conversations, leading technical solutioning sessions, and translating messy customer requirements into buildable, tested solutions.
Execution Style: An "act fast, own it" mentality. You thrive in ambiguity, do not let blockers sit, and are comfortable making yourself productive inside an unfamiliar codebase quickly.
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
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