Senior Sales Engineer, H2O.ai

• 5+ years in pre-sales, sales engineering, or solution architecture roles for enterprise AI/ML platforms
• Hands-on expertise in Generative AI and ML: LLM fine-tuning, evaluation, pipelines, predictive ML algorithms
• Proven experience with cloud-native deployments (AWS, Azure, GCP), Kubernetes, and enterprise integration
• Master the art of technical storytelling, the ability to whiteboard a complex Kubernetes deployment for an IT Director, then pivot to explaining the risk-mitigation benefits of 'Guardrails' to a Chief Risk Officer
• Excellent presentation and communication skills: confident in front of C-level executives and technical teams
• Experience with H2O.ai products or similar enterprise AI/ML platforms is a plus
• Willingness to travel up to 50% to support strategic accounts

Desirable

• We are looking for a Senior Sales Engineer - AI to join our team
• In this role, you’ll combine deep technical expertise in Machine Learning and Generative AI with strong pre-sales solutioning skills to help enterprise customers design, adopt, and scale AI using the H2O.ai platform
• You’ll work hand-in-hand with Sales, Product, and Customers - leading technical discovery, designing architectures, running demos and pilots, and guiding customers through their end-to-end AI journey
• Partner with Sales to drive pre-sales success: lead discovery sessions, identify customer needs, design technical solutions, and build winning proposals
• Execute high-impact proof of value that moves beyond technical feasibility to demonstrate ROI, such as cost per token or measurable accuracy gains in production using H2O AI Enterprise Platform: Predictive, Generative, and Agentic AI
• Build and present custom AI/ML/GenAI solutions tailored to industry verticals (banking, finance, insurance, healthcare, manufacturing, retail, public sector)
• Showcase hands-on expertise with LLMs: fine-tuning, evaluations, RAG, and Agentic pipelines
• Design and build sophisticated Agentic Workflows, beyond simple RAG to multi-agent systems that can reason, use tools, and execute complex business logic autonomously
• Design reference architectures and deployment strategies for enterprise customers across cloud (AWS, Azure, GCP), hybrid, and on-prem
• Architect integrated solutions that leverage the full H2O stack: using Driverless AI for predictive features, h2oGPTE for unstructured data synthesis
• Guide customers on MLOps, Kubernetes deployments, CI/CD integration, monitoring, and governance to ensure their applications are production-ready
• Work closely with Product Management to influence the product roadmap based on customer and field insights
• Contribute to thought leadership by creating solution blueprints, best practices, and reusable assets; represent H2O.ai at events, roundtables, webinars, and conferences