Enterprise AI Engineer: Agentic & LLM Systems Lead

h2o.ai; San Francisco, Northern (CA, KY); Hybrid; USD 175,000 - 200,000; Full time

Benefits offered by this job

Remote-friendly culture

Flexible working environment

World-class team

Career growth

Market leader in total rewards

Job summary

H2O.ai is seeking a Principal AI Engineer in San Francisco to design and ship end-to-end AI solutions for enterprise problems, including agentic AI systems and LLM apps. This hands-on role sits with a field team and collaborates with top ML talent to move from demos to production.

You will own the full lifecycle from framing to deployment, build scalable services, and ensure governance and guardrails for enterprise deployments.

Qualifications

• 8+ years hands-on AI/ML engineering experience with end-to-end model development and production deployment.
• Experience leading technical delivery across complex, multi-stakeholder enterprise engagements.
• Proven ability to build LLM-powered applications (RAG, fine-tuning, agentic workflows).
• Strong Python engineering skills with ML frameworks and LLM tooling.
• Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes).

Responsibilities

• Lead end-to-end customer engagements, ownership of delivery quality and outcomes.
• Design and build agentic AI systems and multi-agent frameworks.
• Own full development lifecycle from problem framing to production deployment.
• Mentor junior ML engineers and coordinate cross-functional teams.

Skills

Python

ML engineering

Leadership

Cross-functional coordination

LLM concepts

Cloud deployment

REST APIs

Tools

LangChain

LlamaIndex

Docker

Kubernetes

PyTorch

TensorFlow

scikit-learn

Job description

H2O.ai is seeking a Principal AI Engineer in San Francisco to design and ship end-to-end AI solutions for enterprise problems, including agentic AI systems and LLM apps. This hands-on role sits with a field team and collaborates with top ML talent to move from demos to production.

You will own the full lifecycle from framing to deployment, build scalable services, and ensure governance and guardrails for enterprise deployments.