Principal Applied AI Engineer – Healthcare Infrastructure

Qualified Health; Palo Alto (CA); On-site; USD 230,000 - 350,000; Full time

Benefits offered by this job

Equity packages

Medical/dental/vision insurance

Flexible working hours

Hybrid work options

Inclusive environment

Job summary

Qualified Health in Palo Alto is hiring a Principal Applied AI Engineer to set the technical vision for agentic AI across the product portfolio. You will shape multi-year infrastructure strategy, influence leadership decisions, and write production-grade code while guiding the systems and standards across teams.

You’ll mentor staff engineers, evaluate new models, and partner with founders to tie AI investments to company strategy.

Qualifications

• 8+ years building production software with a track record of scale.
• 4+ years building and scaling AI-powered/LLM-driven apps in production.
• Ability to set technical direction and standards across multiple teams.
• Deep expertise in MLOps, model deployment, and workflow automation.

Responsibilities

• Define the multi-year technical strategy and architecture for agentic workflow infrastructure.
• Represent applied AI engineering in leadership decisions on product direction and platform investments.
• Set org-wide standards for LLM evaluation, deployment, safety, and monitoring.
• Act as a technical escalation point for high-ambiguity problems across product lines.
• Mentor Staff-level engineers and shape the technical career ladder.
• Evaluate emerging models/frameworks to determine what to adopt at QH.
• Partner with founders on how AI infra investments tie to company strategy.

Skills

Python

Production software

MLOps

AI strategy

Leadership influence

Staff mentoring

Education

Bachelor’s degree + 10 years OR Master’s degree + 8 years in Computer Science, Engineering, or related field

Job description

Qualified Health in Palo Alto is hiring a Principal Applied AI Engineer to set the technical vision for agentic AI across the product portfolio. You will shape multi-year infrastructure strategy, influence leadership decisions, and write production-grade code while guiding the systems and standards across teams.

You’ll mentor staff engineers, evaluate new models, and partner with founders to tie AI investments to company strategy.