Senior Technical Support Engineer

Location: Fort MacKay

Founded in 2012, H2O.ai is on a mission to democratize AI. As the world’s leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose‑built GenAI applications on their private data. With a focus on Sovereign AI—secure, compliant, and infrastructure‑flexible deployments—H2O.ai delivers solutions that align with the highest standards of data privacy and control.

Our open‑source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500.

H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH.

H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO.

H2O.ai’s AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation.

With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co‑create valuable AI applications for all users.

H2O.ai has raised $256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life.

This position is based in Canada.

About This Opportunity

As a Customer Support Engineer , 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.

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. You will work closely with our developers, data scientists, and Dev Ops 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.

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!

What You Will Do

• 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.

What We Are Looking For

• 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.
• Deep expertise in debugging and operating complex, distributed systems built on Kubernetes and Docker‑based architectures.
• Proficiency…