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.

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

Customer Success Engineer

Key skills