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Salary: USD 230,000 - 280,000 / annual
Qualified Health is building generative AI infrastructure for healthcare, providing guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring. You will join as Principal Applied AI Engineer, a company-level technical leadership role responsible for setting the technical vision for agentic AI systems across the entire product portfolio.
You will define multi-year technical strategy and architecture for agentic workflow infrastructure supporting 100+ workflows and growing. You'll represent applied AI engineering in cross-functional and leadership-level decisions on product direction, build-vs-buy, and platform investment. You'll set organization-wide engineering standards for LLM evaluation, deployment, safety, and monitoring, informing QH's broader AI governance approach.
You will act as a technical escalation point for the hardest, highest-ambiguity problems across product lines. You'll mentor and develop Staff-level engineers and help shape the technical career ladder for applied AI roles. You'll stay ahead of the frontier by evaluating emerging models, frameworks, and techniques from OpenAI, Anthropic, Mistral, and others, determining what's worth adopting at QH. You'll partner with founders and engineering leadership on how AI infrastructure investment ties to company strategy.
While this is a leadership role, you'll still write code and dive into hard technical problems directly. Your primary impact will be through the systems, standards, and people you influence across teams.
Qualified Health is a seed-stage, venture-backed company backed by premier investors. The team is mission-driven and focused on building a category-defining product that will change the healthcare industry.
REQUIREMENTS:
- Deep software engineering foundation with Python required; 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
DESIRABLE:
- 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
