Senior Life Sciences AI Solutions Engineer

h2o.ai; Washington, Northern (District of Columbia, KY); Hybrid; USD 200,000 - 320,000; Full time

Benefits offered by this job

Remote-friendly culture

Flexible working environment

Career growth

Job summary

H2O.ai is seeking a Senior Sales Engineer - AI in Washington, DC to blend deep ML expertise with pre‑sales acumen. You will lead technical discovery, design architectures, run demos and pilots, and guide customers from initial concept to production deployment.

You will partner with Sales and Product, showcase Generative AI capabilities, and craft multi‑cloud reference architectures spanning AWS, Azure, GCP, and on‑prem environments. Travel up to 50% is expected.

Qualifications

• 5+ years in pre-sales, sales engineering, or solution architecture for enterprise AI/ML platforms.
• Hands-on Generative AI and ML: LLM fine-tuning, evaluation, pipelines.
• Proven cloud-native deployments experience (AWS, Azure, GCP) and Kubernetes.
• Master the art of technical storytelling for executive audiences.
• Willingness to travel up to 50% and security clearance advantageous.

Responsibilities

• Partner with Sales to drive pre-sales success: lead discovery, design solutions, build proposals.
• Execute high-impact proofs of value showing ROI and measurable gains.
• Design and present AI/ML/GenAI solutions for industry verticals.
• Showcase hands-on expertise with LLMs, RAG, and Agentic pipelines.
• Architect reference architectures for multi-cloud, hybrid, and on-prem deployments.
• Guide customers on MLOps, CI/CD, monitoring, and governance for production-ready apps.

Skills

Pre-sales experience

Generative AI / ML

Cloud deployments

Kubernetes

Executive storytelling

H2O.ai products

Tools

AWS

Azure

GCP

Kubernetes

Job description

H2O.ai is seeking a Senior Sales Engineer - AI in Washington, DC to blend deep ML expertise with pre‑sales acumen. You will lead technical discovery, design architectures, run demos and pilots, and guide customers from initial concept to production deployment.

You will partner with Sales and Product, showcase Generative AI capabilities, and craft multi‑cloud reference architectures spanning AWS, Azure, GCP, and on‑prem environments. Travel up to 50% is expected.