Forward Deployed Engineer, Life Sciences - Domino Data Lab

About Domino Data Lab

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 — use our software to solve some of the most important challenges in the world, such as developing new medicines, securing financial markets, and protecting our country.

Backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and other leading investors, we have been in business for over a decade while operating with the spirit of a startup.

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 (FDE) 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, and more.

What Your Impact Will Be

• Day 0–30 (Onboard & Shadow): Master Domino platform mechanics and learn core user/admin functionalities. Closely shadow customer environments, pairing with a senior FDE to learn the client’s unique data, tooling stack, and commercial objectives.
• By Month 6 (Full Ownership): Step into full customer ownership across your engagements, executing independently against a prioritized backlog managed by your partner Engagement Manager (EM). 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): Lead and advise on key accounts, serving as a trusted advisor to technical and business stakeholders. Author reusable playbooks, integration templates, and deployment guides for the shared knowledge base. Translate field intelligence into critical product feedback to shape Domino’s roadmap.

What We Look For

• 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). 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 with strict compliance rules, data security hurdles, and infrastructure limits.
• Consultative Mindset: Exceptional communication skills across both technical and business audiences. 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

• Growth mindset: High-performing creative individuals who dig into problems and see opportunities for success.
• Authenticity: Individuals who seek truth, speak truth, and can be their whole selves at work.
• Continuous improvement: Believing that improving is always possible.
• Continuous learning: An environment of teaching and learning to equip employees with tools for success.
• Diversity of all backgrounds, genders, ethnicities, abilities, and sexual orientations.

Visa Sponsorship

Visa sponsorship (including H-1B and other employment-based visa categories) may be available for this position depending on business considerations and role requirements. Sponsorship eligibility is assessed on an individual basis.