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. Its 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, Singtel, Chipotle, Workday, Progressive Insurance, and NIH.

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

About This Opportunity

We are seeking a Senior Sales Engineer specializing in Machine Learning and Artificial Intelligence to bridge the gap between complex AI/ML technologies and business value. This role requires a unique combination of deep technical expertise and exceptional communication skills to support enterprise sales cycles, conduct technical demonstrations, and architect AI solutions that align with client business objectives.

This position is based in NYC, New York, and in the greater NYC area.

What You Will Do
Technical Sales Support

• Lead technical discovery sessions with enterprise clients to understand data needs and AI/ML requirements
• Deliver compelling technical presentations and architecture walkthroughs to both technical and C-level stakeholders
• Support sales cycles through proof-of-concept development, client workshops, and technical solution demonstrations
• Create and maintain demo environments showcasing AI/ML capabilities across various use cases
• Conduct hands-on training and product onboarding workshops for client data teams

• Design end-to-end machine learning solutions aligned with enterprise cloud architectures
• Create reference architectures and technical documentation for AI/ML implementations
• Architect feature stores and ML Ops pipelines using industry-standard tools
• Develop visual technical documentation and deployment diagrams for architecture reviews
• Collaborate with product teams to shape roadmaps based on client feedback and market
• needs

• Manage client escalations by diagnosing architecture mismatches and deployment challenges
• Partner with cross-functional teams to introduce responsible AI controls and compliance frameworks
• Support partner organizations in implementing data science platforms across hybrid cloud environments
• Evangelize scalable AI adoption across diverse industries and use cases

• Bachelor's degree in Computer Science, Engineering, or related technical field
• Master's degree in Computer Science or equivalent advanced technical education preferred
• 10+ years of software engineering experience with focus on AI/ML systems
• 5+ years of experience in technical sales, solutions engineering, or client-facing technical roles

• Expert-level proficiency in Python, with strong knowledge ofR, Java, and SQL
• Deep experience with ML/AI frameworks: TensorFlow, Scikit-learn, MLflow, Hugging Face
• Hands-on experience with enterprise ML platforms (H2O.ai, Driverless AI, or similar
• Proficiency in LLM development and deployment, including open-source models

• Strong experience with major cloud platforms: AWS, GCP, Azure
• Expertise in containerization and orchestration: Docker, Kubernetes, Helm
• Knowledge of cloud services: S3, EC2, Lambda, IAM, GKE, AKS
• Experience with Infrastructure as Code: Terraform

• Hands-on experience with CI/CD pipelines, GitLab CI, Jenkins
• Knowledge of monitoring and observability tools: Prometheus, Grafana
• Experience with ML Ops best practices: Model Registry, ML Pipelines, Feature Stores
• Understanding of streaming data processing and real-time scoring systems

• Experience with REST APIs, OAuth, and data ingestion pipelines
• Knowledge of various data storage solutions and integration patterns
• Understanding of enterprise data governance and security requirements

• Proven track record of supporting enterprise sales cycles and achieving revenue targets
• Exceptional presentation skills with ability to communicate complex technical concepts to diverse audiences
• Experience creating compelling technical demonstrations and proof-of-concepts
• Strong collaborative skills for working with sales teams, product managers, and engineering teams
• Ability to translate business requirements into technical solutions and vice versa

• Deep understanding of AI/ML industry trends, tools, and best practices
• Knowledge of responsible AI principles, bias detection, and compliance frameworks
• Experience across multiple industries and AI/ML use cases
• Understanding of enterprise software procurement and implementation processes

• Deep background in financial services, including banking, insurance, capital markets, or fintech
• Experience with healthcare and life sciences AI applications, including regulatory compliance
• Knowledge of retail and e-commerce AI use cases, particularly recommendation systems and demand forecasting
• Background in manufacturing and supply chain optimization using predictive analytics
• Experience in media and entertainment, including content recommendation and audience targeting
• Understanding of telecommunications and network optimization applications
• Familiarity with energy and utilities sector, including grid optimization and predictive maintenance

• Experience with generative AI agents and LL
• M-based applications
• Experience with image recognition, NLP, or other specialized AI domains
• Knowledge of Agile methodologies and project management tools (Jira)

• Experience with advanced visualization tools and dashboard creation
• Knowledge of streaming data architectures and real-time processing
• Background in model explainability and AI observability
• Experience with hybrid cloud deployments and multi-cloud strategies

• Achievement of quarterly and annual sales targets through technical support
• Client satisfaction scores for technical demonstrations and workshops
• Successful proof-of-concept completion rates and conversion to sales
• Quality and effectiveness of technical documentation and reference architectures
• Contribution to product roadmap through client feedback and market insights

• Up to 30% travel for client meetings, conferences, and on-site implementations
• Flexibility for remote client workshops and technical sessions

• Market leader in total rewards
• Remote-friendly culture
• Flexible working environment
• Be part of a world-class team
• Career growth
• Salary range: $175,000-$245,000

H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis.

H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We’ve made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence.

H2O.ai employs the world’s top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company’s purpose.

Please visit www.H2O.ai to learn more.
 

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