Senior Staff AI Engineer - Healthcare Platform Lead

Qualified Health PBC; Palo Alto (CA); Hybrid; USD 250,000 - 310,000; 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 is seeking a Sr. Staff AI Engineer to set the technical direction for agentic AI systems across product lines.

You will define shared architecture, establish engineering standards, and collaborate with leadership on platform investments while staying hands-on with the toughest problems. You'll mentor senior engineers, shape the AI governance approach, and track frontier models to decide what to adopt.

Qualifications

• 9+ years building production software and ML engineering.
• 2+ years hands-on production LLM or agentic work.
• Strong ML fundamentals; experience with pipelines, deployment, and MLOps.
• Experience taking models from experimentation to production.
• Deep expertise in AI workflow automation at platform level.
• Ability to set technical direction across multiple product lines.
• Autonomy on ambiguous, high-stakes problems.
• Influence decisions with engineering leadership and stakeholders.

Responsibilities

• Define the architecture and roadmap for agentic workflow infra shared across product lines.
• Partner with leadership on build-vs-buy and platform investments.
• Set standards for LLM evaluation, safety, and monitoring across teams.
• Act as a technical escalation point for cross-product problems.
• Mentor Staff and Senior engineers and contribute to career ladders.
• Track frontier models and decide what to adopt at Qualified Health.

Skills

Python

LLM engineering

Software architecture

ML model deployment

MLOps

Autonomy in ambiguity

Education

Bachelor's degree in CS/Engineering

Master's degree in CS/Engineering

Tools

OpenAI

Anthropic

Mistral

Job description

Qualified Health is seeking a Sr. Staff AI Engineer to set the technical direction for agentic AI systems across product lines.

You will define shared architecture, establish engineering standards, and collaborate with leadership on platform investments while staying hands-on with the toughest problems. You'll mentor senior engineers, shape the AI governance approach, and track frontier models to decide what to adopt.