Customer Success Engineer

DataRobot is a leading company in AI technology, focused on maximizing business impact while minimizing risk. The Customer Success Engineer serves as a post-sales technical expert, ensuring customers effectively adopt and utilize GenAI applications to achieve measurable outcomes.

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 ’s 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

Requirements:

• 5+ years of experience in technical customer-facing roles (e.g., Solution Engineer, AI 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
• 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 supporting product adoption, managing customer success plans, and driving technical consumption
• Working knowledge of AI/ML concepts (model deployment, inference, fine-tuning)
• 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