Customer Success Engineer

Job Description:

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. 

The Customer Success Engineer is a post-sales technical expert responsible for driving adoption, consumption, and measurable outcomes from deployed GenAI applications. Customer Success Engineers serve as the technical bridge between developers and DataRobot’s platform, ensuring customers maximize value from using DataRobot. They work closely with Account Owner, Engagement Directors, and Professional Services teams to accelerate time-to-value, support expansion motions, and reduce churn risk through continuous enablement and use case optimization.

Key Responsibilities: 

• Accelerate Onboarding & Initial Application Adoption: Guide customers through first-use milestones by enabling key personas, resolving blockers, and ensuring consumption of initial apps deployed during onboarding.
• Drive Ongoing Consumption: Monitor usage, identify underutilized apps / stalled users, and engage with customers to increase activation and business impact.
• Customer Health Monitoring: Actively track product usage, satisfaction, and success milestones to surface risk early and coordinate mitigation plans.
• Technical Advocacy & Solution Feedback: Act as the voice of the customer to DataRobot product and engineering teams, channeling technical requirements, gaps, and enhancement requests.
• Accelerate Initial Group Learning Adoption: Facilitate onboarding workshops and training sessions for multiple user groups, enabling key personas to reach first-use milestones and overcome common blockers.
• Technical Enablement & Training: Deliver targeted, scalable enablement sessions and create reusable knowledge-sharing materials designed for diverse audiences across accounts.
• Use Case Value Realization: Collaborate with Engagement Directors to ensure learning initiatives align with business goals and capture feedback and outcomes for executive reviews.

Knowledge, Skills and Abilities:

• Familiarity with AI platforms, application lifecycle management, or data-centric solution delivery
• AI Engineering to include GenAI application development, prompt engineering, and knowledge of LLMs
• Strong presentation and communication skills, with the ability to engage both business users and technical stakeholders
• Proven ability to translate complex technical functionality into measurable business outcomes
• Experience in supporting product adoption, managing customer success plans, and driving technical consumption
• Extensive experience with the end-to-end machine learning lifecycle, including feature engineering, model training, evaluating accuracy and insights, and deploying models for inference
• Understanding of GenAI application architectures and LLM implementations
• Familiarity with cloud infrastructure (AWS/Azure/GCP) and deployment patterns
• Comfortable reading code/logs to diagnose technical issues

Requisite Education and Experience / Minimum Qualifications:

• 3-5+ years of experience in technical customer-facing roles (e.g., Solution Engineer, AI/ML Engineer, Technical CSM, App Developer) in SaaS or enterprise software
• Bachelor's degree in a technical, business, or related field (or equivalent practical experience); advanced degree a plus

The talent and dedication of our employees are at the core of DataRobot’s journey to be an iconic company. We strive to attract and retain the best talent by providing competitive pay and benefits with our employees’ well-being at the core. Here’s what your benefits package may include depending on your location and local legal requirements: Medical, Dental & Vision Insurance, Flexible Time Off Program, Paid Holidays, Paid Parental Leave, Global Employee Assistance Program (EAP) and more!

DataRobot Operating Principles:

• Wow Our Customers
• Set High Standards
• Be Better Than Yesterday
• Be Rigorous
• Assume Positive Intent
• Have the Tough Conversations
• Be Better Together
• Debate, Decide, Commit
• Deliver Results
• Overcommunicate

Research shows that many women only apply to jobs when they meet 100% of the qualifications while many men apply to jobs when they meet 60%. At DataRobot we encourage ALL candidates, especially women, people of color, LGBTQ+ identifying people, differently abled, and other people from marginalized groups to apply to our jobs, even if you do not check every box. We’d love to have a conversation with you and see if you might be a great fit. 

DataRobot is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. DataRobot is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. Please see the United States Department of Labor’s EEO poster and EEO poster supplement for additional information.

Use of Artificial Intelligence in Our Hiring Process

DataRobot uses approved AI-powered tools to support the hiring process in selected regions. These tools may assist in writing job descriptions, reviewing applications, assessing qualifications, and evaluating candidate materials. All decisions regarding applications are made by members of the DataRobot team.

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