Customer Success Engineer

This is a fully remote position, open to applicants in Japan.

📋 Description

• Accelerate the onboarding process and initial application usage by guiding customers through key milestones, addressing obstacles, and ensuring the effective use of apps deployed during the onboarding phase.

• Promote ongoing application usage by monitoring activities, identifying underutilized applications and inactive users, and engaging with customers to boost activation and overall business impact.

• Monitor customer health by actively tracking product usage, satisfaction levels, and success milestones to identify risks early and coordinate appropriate mitigation strategies.

• Serve as the customer advocate to the DataRobot product and engineering teams, relaying technical requirements, identifying gaps, and submitting enhancement requests.

• Facilitate onboarding workshops and training sessions for various user groups to help key personas achieve first-use milestones and navigate common challenges.

• Provide targeted technical enablement and training by delivering scalable sessions and creating reusable knowledge-sharing resources tailored for diverse audiences across accounts.

• Collaborate with Engagement Directors to ensure that learning initiatives align with business objectives and gather feedback and outcomes for executive reviews.

⛳️ Requirements

• A minimum of 5 years of experience in technical customer-facing roles (e.g., Solution Engineer, AI/ML Engineer, Technical CSM, App Developer) within SaaS or enterprise software environments.

• A bachelor's degree in a technical, business, or related field (or equivalent practical experience); an advanced degree is a plus.

• Familiarity with AI platforms, application lifecycle management, or data-centric solution delivery.

• Experience in AI Engineering, including GenAI application development, prompt engineering, and knowledge of large language models (LLMs).

• Excellent presentation and communication abilities, capable of engaging both business users and technical stakeholders.

• Demonstrated capability to convert complex technical functionalities into quantifiable business results.

• Background in supporting product adoption, managing customer success plans, and enhancing technical consumption.

• Extensive knowledge of the end-to-end machine learning lifecycle, including feature engineering, model training, accuracy evaluation, and model deployment for inference.

• Understanding of GenAI application architectures and LLM implementations.

• Familiarity with cloud infrastructure (AWS/Azure/GCP) and deployment methodologies.

• Proficient in reading code and logs to troubleshoot technical issues.

• Professional proficiency in both Japanese and English, with strong written and verbal communication skills.

🏝️ Benefits

• Medical, Dental & Vision Insurance

• Flexible Time Off Program

• Paid Holidays

• Paid Parental Leave

• Global Employee Assistance Program (EAP) and more!