<p><strong>Who we are</strong></p> <p>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 &amp; 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</p> <p><strong>What we are building</strong></p> <p>Our Sales Engineering team is at the heart of transforming curiosity into confidence. We help prospects envision the full potential of our platform, guiding them from discovery to realization. Working closely with Enterprise Account Executives, our Sales Engineers craft compelling product demonstrations, design and execute impactful proof-of-concepts, and shape technical strategies that drive successful customer implementations.</p> <p>As a growing company, our Sales Engineers play a pivotal role beyond just sales—collaborating across Marketing, Product Management, and Engineering to bridge the gap between market needs and product innovation. If you thrive in an environment where your technical expertise fuels real business impact, and where your insights help shape the future of our platform, you’ll feel right at home here.</p> <p><strong>What your impact will be</strong></p> <ul> <li>Lead technical evaluations and demonstrations of the Domino platform for customers across the Department of Defense, civilian agencies, federally funded research and development centers (FFRDCs), and major defense contractors.</li> <li>Design and execute proof-of-concept deployments tailored to each customer’s environment and mission needs, showcasing Domino’s integration with their data science workflows and infrastructure.</li> <li>Collaborate with account executives to craft solution architectures that meet federal security and compliance standards (e.g., FedRAMP, IL5).</li> <li>Develop and maintain reusable demonstration environments and technical assets that accelerate future sales cycles.</li> <li>Drive post-POC adoption readiness by partnering with Customer Success and Solutions Architects to ensure a smooth handoff into deployment.</li> <li>Success will be evident through higher technical win rates, reduced time to close, and increased adoption within key government accounts.</li> </ul> <p><strong>What we look for in this role</strong></p> <ul> <li><strong>Security Clearance: </strong>This position requires an active U.S. Secret Security Clearance (US Citizenship required), with the ability to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) Security Clearance and program access (post start). A U.S. Security Clearance that has been active in the past 24 months is considered active.</li> <li> Proven success in pre-sales or solutions engineering, ideally supporting enterprise software or AI/ML platforms. This does not necessarily need to be at a software vendor, equivalent solution engineering tasks internally or as a consultant developer could work.</li> <li>Experience with U.S. public sector customers, especially within federal agencies, defense, or national labs — understanding their procurement processes, compliance constraints, and security environments.</li> <li>Track record of leading successful technical evaluations or pilots that resulted in multimillion-dollar enterprise or government software deals.</li> <li>Experience working in complex, highly regulated IT environments, including hybrid or air-gapped systems.</li> <li>Proficiency in Python, R, and modern data science / machine learning tools.</li> <li>Familiarity with containerization (Docker, Kubernetes), cloud platforms (AWS GovCloud, Azure Government, GCP), and networking concepts.</li> <li>Understanding of the end-to-end AI lifecycle, from experimentation to production.</li> </ul> <p><strong>What we value</strong></p> <ul> <li>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</li> <li>We value a growth mindset. High-performing creative individuals who dig into problems and see the opportunities for success</li> <li>We believe in individuals who seek truth and speak the truth and can be their whole selves at work</li> <li>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</li> <li>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> </ul> <hr /> <p>#LI-Remote</p><div><div><div><p><em>The annual US base salary range for this role is listed below. For sales roles, the range provided is the roles 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 candidates 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.</em></p></div><div>Total Compensation Range</div><div><span>$200,000</span><span>—</span><span>$250,000 USD</span></div></div></div>

Domino Data Lab

Sales Engineer, Public Sector

Domino Data Lab

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