Senior AI Sales Engineer, H2O.ai

• Are you a data scientist or machine learning engineer who enjoys solving real-world problems by applying cutting-edge Gen AI/ML algorithms?
• Are you passionate about working with customers to solve their business challenges?
• Can you explain complex machine learning concepts in simple business terms?
• 5+ years in pre-sales, sales engineering, or solution architecture roles for enterprise AI/ML platforms
• Strong 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
• Ability to design and explain AI/ML solution architectures to both technical and executive stakeholders
• Strong programming skills in Python (preferred), with familiarity in R or Java
• 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 AI Solutions Engineer to join our customer-facing 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
• Deliver compelling demos, workshops, and proof-of-concepts (POCs) across the H2O.ai platform (Driverless AI, Feature Store, EnterpriseGPT, Wave, h2oGPT, LLM Studio, ML Ops, and open-source tools)
• 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, evaluation, RAG pipelines, guardrails, and LLMOps best practices
• Design reference architectures and deployment strategies for enterprise customers across cloud (AWS, Azure, GCP), hybrid, and on-prem
• Guide customers on MLOps, Kubernetes deployments, CI/CD integration, monitoring, and governance to ensure production readiness
• Work closely with Product Management to influence 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