Technical Lead Applied AI Engineer

Qualified Health PBC•Palo Alto, CA

1d•Hybrid

About The Position

Transform healthcare with us. At Qualified Health, we're redefining what's possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring—working alongside leading health systems to drive real change. This is more than just a job. It's an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you're ambitious, innovative, and ready to move fast, we'd love to have you on board. Join us in shaping the future of healthcare. We're hiring a Technical Lead Applied AI Engineer to set the technical vision for how Qualified Health builds agentic AI systems across the entire product portfolio. This is a company-level technical leadership role: you'll shape multi-year infrastructure strategy, represent engineering in decisions about AI direction at the leadership table, and set the bar for what "production-grade agentic AI in healthcare" means at QH. You'll still write code and dive into hard technical problems directly, but your primary impact will be through the systems, standards, and people you influence across teams.

Requirements

Deep software engineering foundation (Python required) with a track record of architecting systems used company-wide.
8+ years building production software, including 4+ years building and scaling AI-powered/LLM-driven applications in production.
Proven experience setting technical direction and standards adopted across multiple teams, not just a single product line.
Deep expertise in MLOps, model deployment, and workflow automation at an organizational/platform level.
Demonstrated ability to operate with full autonomy on ambiguous, high-stakes technical and strategic problems.
Strong track record influencing technical decisions at the leadership level, including with non-technical stakeholders.

Nice To Haves

Bachelor's degree + 10 years OR Master's degree + 8 years in Computer Science, Engineering, or related field (or equivalent experience).
Recognized expertise (internally or externally — talks, publications, open source, prior platform-level roles) in applied AI/agentic systems.
Experience building AI infrastructure in a regulated or high-stakes domain (healthcare, finance, etc.).
History of founding or scaling a technical function from the ground up in a startup environment.
Experience mentoring Staff-level engineers and shaping technical career ladders.

Responsibilities

Define the multi-year technical strategy and architecture for agentic workflow infrastructure supporting the full QH product portfolio (100+ workflows and growing).
Represent applied AI engineering in cross-functional and leadership-level decisions on product direction, build-vs-buy, and platform investment.
Set org-wide engineering standards for LLM evaluation, deployment, safety, and monitoring — informing QH's broader AI governance approach.
Act as a technical escalation point for the hardest, highest-ambiguity problems across product lines.
Mentor and develop Staff-level engineers; help shape the technical career ladder for applied AI roles.
Stay ahead of the frontier — evaluate emerging models, frameworks, and techniques (OpenAI, Anthropic, Mistral, etc.) and determine what's worth adopting at QH.
Partner with founders and engineering leadership on how AI infrastructure investment ties to company strategy.