• As a Customer Support Engineer at H2O.ai, you will play a critical role in ensuring our customers have a seamless experience deploying and managing machine learning models in production
• You will be the bridge between our engineering teams and customers, providing hands-on technical support, troubleshooting complex issues, and helping users optimize their MLOps workflows
• You will work closely with our developers, data scientists, and DevOps teams to ensure smooth deployments and high availability of models
• Additionally, you will have the opportunity to contribute to our platform’s evolution by providing valuable insights from customer interactions
• Lead Customer Escalation and Resolution: Serve as the final technical escalation point for complex, high-impact issues across H2O.ai’s Generative and Predictive AI product portfolio. Act as the primary bridge to Engineering to ensure rapid resolution and customer success in deploying and managing their AI applications
• Deep Technical Analysis and Root Cause: Conduct comprehensive root cause analysis, reproduce intricate customer issues in cloud-native environments, and provide necessary code fixes or patches to ensure system stability and high availability
• Infrastructure Expertise: Troubleshoot, maintain, and manage Infrastructure Code (Terraform and Helm charts) related to customer deployments, focusing on resolving configuration, stability, and security issues in production environments
• Mentorship and Quality Standards: Actively review technical solutions and troubleshooting approaches of junior team members. Champion and enforce best practices in documentation, operational efficiency, and code contribution within the support organization
• Strategic Influence: Translate persistent customer pain points and recurrent issues into actionable product feedback, helping to shape the platform’s long-term evolution and supportability

Benefits

• Remote-friendly culture
• Flexible working environment
• Career growth- This role is ideal for someone who enjoys problem-solving, has a deep understanding of Kubernetes-based architectures, and thrives in a customer-facing environment
• If you’re excited about working on cutting-edge cloud-native solutions, enabling real-time AI applications, and being part of a highly skilled team pushing the boundaries of MLOps, we’d love to hear from you!
• Proficiency in diagnosing, patching, or contributing to core software systems (3+ years of coding experience) using at least one of: GoLang, Python, C++, or Java, applied specifically to resolving support issues
• Bachelor’s or a higher education degree in Computer Science/Engineering or a related field
• Strong knowledge of Linux, Bash, File systems, Logging, Linux file permissions, Relational Databases (e.g. SQL), and Networking concepts (e.g., SSL, UDP/TCP, firewalls, and reverse proxies)
• Expertise in cloud platforms (AWS, Azure, or GCP) and infrastructure management tools (Terraform and Helm)
• Deep expertise in debugging and operating complex, distributed systems built on Kubernetes and Docker-based architectures
• Demonstrated experience in a senior or lead technical support role (e.g., 5+ years) where driving critical issue resolution and mentoring peers were primary responsibilities
• Exceptional communication skills and proven comfort in a high-impact, customer-facing role, capable of confidently navigating and influencing both technical and business stakeholders during critical incidents
• Proven ability to take ownership of cross-functional projects that enhance customer experience or support workflow efficiency
• Experience contributing to platform roadmaps or defining long-term technical strategy
• Demonstrated capability in hiring, onboarding, or training new team members
• Advanced knowledge of mainstream Machine Learning frameworks such as sklearn and pytorch, and data science libraries like numpy and pandas, relevant to H2O.ai’s offerings
• Experience with gRPC, Scala, Akka, or GoLang