Senior Sales Engineer, H2O.ai
$175-245k
More information about location
Open-source AI cloud platform
Be an early applicant
Open-source AI cloud platform
201-500 employees
Be an early applicant
$175-245k
More information about location
201-500 employees
Company mission
To democratize AI for everyone.
Role
Who you are
- 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
- 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
- Experience with healthcare and life sciences AI applications, including regulatory compliance
- Understanding of telecommunications and network optimization applications
- M-based applications
- Experience with advanced visualization tools and dashboard creation
- Background in model explainability and AI observability
Desirable
- Deep background in financial services, including banking, insurance, capital markets, or fintech
- 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
- Familiarity with energy and utilities sector, including grid optimization and predictive maintenance
- Experience with generative AI agents and LL
- Experience with image recognition, NLP, or other specialized AI domains
- Knowledge of Agile methodologies and project management tools (Jira)
- Knowledge of streaming data architectures and real-time processing
- Experience with hybrid cloud deployments and multi-cloud strategies
What the job involves
- 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
- 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
- Flexibility for remote client workshops and technical sessions
- Success Metrics:
- 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
Our take
Dedicated to making the world of AI more accessible to everyone, H2O.ai provides a platform that supports the making and operating of AI for businesses. The platform boasts a range of capabilities; from automated machine learning and no-code deep learning, to AI-powered data labelling and extraction; as well as its most recently added "h2oGPT" that supplies enterprise generative AI.
With productivity, organisation and data analysis among the core parts to any business' success, AI and machine learning getting more and more popular - as they are able to outpace humans' ability to absorb, interpret, and make complex decisions quickly. It is no surprise then that H2O.ai has a grand roster of clients including GlaxoSmithKline, Capital One, and Paypal. It is also well-funded, and with such a comprehensive set of offerings it is in a great place to secure further success.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 8 rounds)
Nov 2021
$100m
SERIES E
Aug 2019
$72.5m
SERIES D
Total funding: $251.1m
Company benefits
- Remote-friendly culture
- Flexible working environment
- Career growth
Company HQ
Mountain View, CA
Leadership
Sri Satish Ambati
(Co-Founder & CEO)11 years experience in the Software and Engineering field prior to H2O.ai. Worked as Director of Engineering and Principal Engineer of DataStax.
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