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Supports customers by troubleshooting technical issues, reproducing bugs, identifying root causes, and delivering fixes. Designs features, writes production code and unit tests, reviews code, and contributes to automated testing. Develops infrastructure with Terraform and Helm while working extensively with Kubernetes, Docker, cloud platforms, Linux, microservices, and MLOps systems for deploying and monitoring machine learning models.

Troubleshoot customer issues, analyze and reproduce bugs, identify root causes, implement fixes, design features, write code and unit tests, and contribute to automated testing. Review developer designs and code, improve engineering practices, and manage infrastructure changes using Terraform and Helm. The role requires strong software engineering, Kubernetes, Docker, Linux, cloud, networking, and customer communication skills.

Support customers by troubleshooting technical issues, analyzing and reproducing bugs, identifying root causes, and delivering fixes. Design features, write production code and unit tests, contribute to automated testing, review code, and improve engineering practices. Develop infrastructure using Terraform and Helm, while working extensively with Kubernetes, Docker, Linux, cloud platforms, microservices, databases, and networking technologies. The role requires strong communication and customer-facing skills.

Leads customer-facing AI and machine learning engineering activities, including solution architecture, demonstrations, proof-of-concept delivery, and deployment of end-to-end ML workflows. Serves as a trusted technical advisor during sales engagements, translates business needs into scalable cloud-native solutions, manages customer technical relationships, and supports successful project delivery. Manages, mentors, and develops a team of AI and machine learning engineers.

Leads pre-sales technical discovery, solution architecture, demonstrations, proof-of-value projects, and enterprise AI deployments. Designs predictive, generative, and agentic AI solutions across cloud, hybrid, and on-premises environments. Advises customers on LLM fine-tuning, RAG, agentic workflows, MLOps, Kubernetes, governance, monitoring, and integrations. Partners with Sales and Product, develops reusable solution assets, influences the roadmap, and represents H2O.ai at industry events. Travel up to 50% is required.

As a Senior Sales Engineer at H2O.ai, you'll lead pre-sales efforts by leveraging technical expertise in AI to design solutions for enterprise customers, drive ROI demonstrations, and guide AI adoption. You'll collaborate with multiple teams and influence product roadmaps while showcasing hands-on skill with LLMs and cloud-based deployments.

Support accounts payable, travel and expense processing, cash management, bank reconciliations, prepaids, accruals, journal entries, and month-end close. Maintain vendor records, assist with 1099 reporting, audits, compliance, cash forecasting, internal controls, and accounting automation. Partner cross-functionally to ensure accurate expense classification and invoice processing while improving ERP and finance operations.

Supports accounts payable, travel and expense processing, cash management, bank reconciliations, month-end close, journal entries, vendor records, 1099 reporting, and audit activities. The role partners cross-functionally to ensure accurate expense classification, contributes to cash forecasting and internal controls, and helps automate and improve accounting systems. This is a temporary position with potential full-time conversion.

The AI Engineer will develop and deploy AI applications, collaborate on the end-to-end pipeline, create backend services, and develop frontend interfaces.

Design, build, and deploy a Kubernetes-based cloud platform managing AI engine lifecycles. Develop operators, APIs (gRPC/REST), microservices, and CI/CD deployments (Helm/GitOps), ensure container hardening and production reliability, and mentor teammates through design-to-delivery ownership.