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DataRobot

Customer Success Engineer

DataRobot · Austin, TX

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  • On site
  • Full-time
  • $152,500 / year
  • Austin, TX

Job highlights

  • Drive GenAI adoption and value realization for customers.
  • Bridge technical gap between developers and AI platform.
  • Monitor customer health and proactively mitigate risks.
  • Provide technical advocacy and feedback to product teams.
  • Deliver technical enablement and training sessions.

About the role

About DataRobot

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.

Job Summary

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’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.

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 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

Minimum Qualifications

  • 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

Compensation and Benefits

The U.S. annual on-target earnings (OTE) range for this full-time position is between $125,000 and $180,000 USD/year. This range represents a combination of annual base pay and targeted commission. Actual offers may be higher or lower than this range based on various factors, including (but not limited to) the candidate’s work location, job-related skills, experience, and education.

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

All DataRobot hires are required to complete a background check prior to starting employment, which includes identity verification, criminal history check, employment verification and education verification. Additionally, all DataRobot employees must be available to attend in-person company trainings and meetings.

DataRobot encourages 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.

Key skills/competency

  • Customer Success Engineer
  • GenAI
  • AI Platforms
  • LLMs
  • Prompt Engineering
  • Technical Support
  • SaaS
  • Cloud Infrastructure
  • AI/ML
  • Customer Adoption

Skills & topics

  • Customer Success Engineer
  • GenAI
  • AI Engineering
  • LLMs
  • Prompt Engineering
  • Technical Customer Success
  • SaaS
  • Cloud
  • Machine Learning
  • AI Adoption

How to get hired

  • Tailor your resume: Highlight AI/ML, GenAI, and customer-facing experience, aligning with DataRobot's needs.
  • Showcase technical skills: Emphasize experience with AI platforms, LLMs, prompt engineering, and cloud infrastructure.
  • Demonstrate customer focus: Provide examples of driving adoption and delivering measurable business outcomes.
  • Prepare for technical interviews: Be ready to discuss AI concepts, customer challenges, and problem-solving approaches.
  • Understand DataRobot's values: Research operating principles like 'Wow Our Customers' and 'Deliver Results'.

Technical preparation

Master GenAI concepts and LLM architectures.,Practice prompt engineering techniques.,Familiarize with cloud platforms (AWS, Azure, GCP).,Review AI/ML deployment and inference processes.

Behavioral questions

Describe a time you drove customer adoption.,How do you translate technical features into business value?,How do you handle difficult customer conversations?,Share an example of technical problem-solving.

Frequently asked questions

What is the primary focus of a Customer Success Engineer at DataRobot?
The Customer Success Engineer at DataRobot is a post-sales technical expert focused on driving adoption, consumption, and measurable outcomes from deployed GenAI applications, acting as a technical bridge between developers and the DataRobot platform.
What are the key responsibilities for a Customer Success Engineer at DataRobot?
Key responsibilities include accelerating customer onboarding and adoption, driving ongoing consumption of AI applications, monitoring customer health, acting as a technical advocate, facilitating learning, and delivering technical enablement.
What technical skills are essential for a DataRobot Customer Success Engineer?
Essential technical skills include familiarity with AI platforms, GenAI development, prompt engineering, LLMs, AI/ML concepts, cloud infrastructure (AWS/Azure/GCP), and the ability to read code/logs for issue diagnosis.
What kind of experience is required for the Customer Success Engineer role at DataRobot?
The role requires at least 5 years of experience in technical customer-facing roles within SaaS or enterprise software, such as Solution Engineer, AI Engineer, Technical CSM, or App Developer.
What is the compensation range for a Customer Success Engineer at DataRobot in the U.S.?
The U.S. annual on-target earnings (OTE) range for this full-time position is between $125,000 and $180,000 USD/year, which includes base pay and targeted commission.
Does DataRobot encourage candidates from diverse backgrounds to apply for the Customer Success Engineer role?
Yes, DataRobot strongly encourages applications from all candidates, especially women, people of color, LGBTQ+ identifying individuals, and others from marginalized groups, even if they don't meet every qualification.
What kind of training or enablement will a Customer Success Engineer provide?
Customer Success Engineers will deliver targeted, scalable enablement sessions and create reusable knowledge-sharing materials for diverse audiences across customer accounts to facilitate learning and adoption.
How does DataRobot handle customer success and product feedback?
Customer Success Engineers act as the voice of the customer, channeling technical requirements, gaps, and enhancement requests to DataRobot's product and engineering teams.