Director, Customer Success Engineering

DataRobot

About The Position

DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business — today and in the future. As the Director of Customer Success Engineering, you will be a pivotal leadership figure reporting directly to the VP of Customer Success Engineering. You will operationalize the global customer success engineering strategy by leading a regional or segmented team of highly skilled Customer Success Engineers (CSEs). Your team is responsible for working hand-in-hand with customer AI Engineers and developers to maximize the value of DataRobot’s Agentic platform. You will ensure your CSEs are delivering measurable business outcomes, driving high application consumption, and securing long-term customer retention. This is a highly collaborative role requiring deep technical acumen in Generative/Predictive AI, proven people leadership, and a customer-obsessed mindset. You will partner cross-functionally with Account Management, Professional Services, Product, and Engineering to ensure a seamless customer experience that drives retention and growth. What You Will Achieve (30-60-90 Days) Day 30: Understand the DataRobot platform, shadow ongoing CSE customer engagements, learn our internal processes, and build relationships with your direct reports and cross-functional peers (Engineering, Product, Account Management). Day 60: Take full operational ownership of your team's book of business. Begin identifying opportunities to optimize CSE capacity, improve Time-to-Value (TTV) for new deployments, and standardize success planning. Day 90: Co-develop and execute strategic adoption plans for top-tier enterprise accounts. Establish a clear feedback loop with Product/Engineering to champion customer needs, and begin driving measurable improvements in team KPIs (health scores, platform consumption).

Requirements

10+ years of experience in post-sales technical, solution engineering, or professional services roles within the B2B enterprise SaaS, Cloud, or AI/Data space.
3–5+ years of direct people management experience, successfully leading technical customer-facing teams.
Proven track record of owning and achieving product adoption, retention, and commercial expansion targets.
Bachelor’s degree in a technical, business, or related field (Master’s degree or equivalent experience preferred).
Strong foundational knowledge of artificial intelligence, including predictive AI, Generative AI, LLMs, AI Agents, and modern SaaS delivery architectures (AWS, GCP, Azure).
Familiarity with data science concepts, programming languages (Python, R), and enterprise AI integration patterns.
Demonstrated ability to coach highly technical individual contributors (data scientists, CSEs, ML engineers) into trusted strategic business advisors.
Ability to translate highly complex technical concepts into ROI-driven business narratives for C-suite stakeholders.
Data-driven decision-maker with a strong grasp of customer success operations and financial KPIs.

Responsibilities

Team Leadership & Development Manage, mentor, and scale a high-performing team of Customer Success Engineers (CSEs).
Translate the overarching technical success strategy set by the VP of Customer Success Engineering into actionable team-level objectives.
Build a culture of accountability, continuous learning, and innovation.
Develop career progression pathways, conduct performance reviews, and recruit top-tier technical talent to keep pace with company growth.
Customer Outcomes & Value Realization Serve as the senior technical sponsor and executive escalation point for strategic enterprise accounts.
Ensure the successful execution of adoption plans, empowering customers to leverage DataRobot’s GenAI and predictive capabilities fully.
Own regional/segment performance metrics, specifically customer health scores, and platform consumption rates.
Proactively identify account risks and commercial expansion opportunities (upsell/cross-sell), guiding your CSEs to intervene and drive value realization alongside Account Management.
Operational Excellence & Tooling Drive day-to-day operational rigor across the team, ensuring adherence to success planning standards, CRM hygiene, and engagement methodologies.
Leverage CS platforms and CRM tools (e.g., Salesforce) to optimize team utilization, capacity planning, and productivity metrics.
Partner with the VP of Customer Success Engineering to evaluate telemetry data and analytics, continuously improving the customer journey.
Cross-Functional Collaboration Work closely with Account Management and Sales leadership to seamlessly align pre-sales expectations with post-sales technical delivery.
Act as a vital conduit between the field and the Product/Engineering teams, utilizing tools like Jira or Productboard to aggregate and translate customer feedback into roadmap influence.
Collaborate with Enablement teams to ensure your technical staff is thoroughly trained on the latest DataRobot features, AI agents, and market trends.