Solutions Engineer, Life Sciences

Who we are At Domino, we build software that helps the largest, AI-driven organizations build and operate advanced data science and AI solutions at scale. Our platform integrates a streamlined model development environment, MLOps capabilities, and novel features for collaboration, reuse, and reproducibility — all of which make data science teams more productive, reduce time to value, and ensure compliance. Our 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 a decade but are still a small team operating with the spirit of a startup. Especially 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 www.domino.ai What we are building We help F100 Life Sciences organizations envision the full potential of our platform, guiding them from discovery to realization. Our Solutions Engineers craft compelling product demonstrations, design and execute impactful proof-of-concepts, and shape technical strategies that drive successful customer deployments. What your impact will be Engage deeply with the technical problems customers are trying to solve — taking the time to genuinely understand their workflows, constraints, and frustrations before proposing anything. The goal is always to find the best solution for the customer, not to fit them to a predetermined answer. Design and run hands-on proof-of-concept projects tailored to each customer's environment: model development for drug discovery, clinical analytics pipelines, regulatory submission workflows, omics data processing, and similar use cases. Work with account executives to design architectures that address life sciences-specific requirements around data governance, reproducibility, and validation (e.g., 21 CFR Part 11, GxP environments). Proactively identify novel use cases within life sciences customers where Domino could create meaningful value — drawing on industry knowledge to surface opportunities that customers may not have considered and that go beyond the initial scope of an engagement. Build and maintain reusable technical environments and assets that make future customer engagements faster and more substantive. Partner with Customer Success and Solutions Architects to make sure customers who complete a POC are set up to succeed in production. Build custom prototypes and applications on top of Domino for customers — using AI-assisted coding tools to move quickly — to demonstrate value in ways that go beyond standard demos. This reflects our directional shift toward Forward Deploy Engineering as a growing part of field work over the next 12 months. Success is most visible when customers come away from technical engagements with a clear understanding of how Domino solves their problems — and when those engagements convert to production deployments. What we look for in this role A technical background — from life sciences or from a general tech/solutions environment . You've either worked inside a pharma, biotech, CRO, genomics, or medical device organization doing code-first analytical or scientific work, or you've built and supported technical solutions at a general technology or software company. Either way, you understand what it actually feels like to build and run real systems for real users, and you can translate that experience credibly in front of technical and scientific stakeholders alike. Working knowledge of at least one life sciences domain — drug discovery, clinical development, computational biology, manufacturing/QC, or regulatory data management. Credible in front of scientific stakeholders without needing to be a domain expert. Platform or tooling ownership experience — ideally you’ve built, operated, or meaningfully contributed to an internal platform or shared scientific computing environment. You’ve influenced or helped shape how that platform served its users, even without a formal product owner title. Experience in a solutions engineering, pre-sales, or customer-facing technical role — or equivalent internal/consulting work where the job was diagnosing technical problems and helping others solve them, not just executing defined tasks. You’ve led or contributed to technical evaluations, pilots, or proof-of-concepts — whether at a vendor, internally, or as a consultant — that drove meaningful adoption or investment decisions. Demonstrated ability to build: you’ve written production or near-production code to solve a real scientific or operational problem. Experience creating internal tools, pipelines, or applications for scientific teams is a strong signal. Proficiency in Python and/or R; hands-on experience with the data science and ML tools used in life sciences technical work. Familiarity with how models get built, validated, and moved toward production in a regulated context is a plus. 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 #LI-Remote For sales roles, the range provided is the role's On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range will be narrowed during the interview process based on a number of factors, including the candidate's experience, qualifications, and location. Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends. Total Compensation Range $160,000 — $230,000 USD