Senior Agentic AI Engineer & Enterprise Delivery Lead

h2o.ai; San Francisco (CA); On-site; USD 175,000 - 200,000; Full time

Benefits offered by this job

Remote-friendly culture

Competitive base salary

Hybrid work options

Job summary

H2O.ai in San Francisco seeks a Principal AI Engineer to design and ship end-to-end AI solutions for enterprise problems—agentic AI, LLM apps, and production ML pipelines. You’ll work hands-on in a customer-facing field role alongside Kaggle Grandmasters and ML experts to deliver production-grade AI with measurable business impact.

You will collaborate with engineering and product teams to drive architecture, governance, and deployment across cloud, on-prem, and hybrid environments, building

Qualifications

• 8+ years AI/ML engineering with production deployments.
• Experience delivering complex enterprise engagements.
• Experience building LLM-powered apps: RAG, agentic workflows, fine-tuning.
• Strong Python skills with ML frameworks and LLM tooling.
• Experience deploying AI services in cloud or on-prem environments.

Responsibilities

• Lead end-to-end customer engagements, ensuring delivery quality and outcomes.
• Architect and ship agentic AI systems and multi-agent workflows.
• Build scalable backend services and APIs for AI capabilities.
• Mentor junior ML engineers and collaborate with product teams.
• Drive pre-sales proof-of-concept engagements and customer workshops.

Skills

Python

LLM tooling

Leadership

Customer engagement

Cross-functional collaboration

Cloud deployment

Tools

LangChain

LlamaIndex

Docker/Kubernetes

PyTorch

AWS/Azure/GCP

Job description

H2O.ai in San Francisco seeks a Principal AI Engineer to design and ship end-to-end AI solutions for enterprise problems—agentic AI, LLM apps, and production ML pipelines. You’ll work hands-on in a customer-facing field role alongside Kaggle Grandmasters and ML experts to deliver production-grade AI with measurable business impact.

You will collaborate with engineering and product teams to drive architecture, governance, and deployment across cloud, on-prem, and hybrid environments, building