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Salary: USD 230,000 - 280,000 / annual
Qualified Health is hiring a Technical Lead Applied AI Engineer to set the technical vision for building agentic AI systems across the entire product portfolio. This is a company-level technical leadership role where you'll shape multi-year infrastructure strategy, represent engineering in AI direction decisions at the leadership table, and define what "production-grade agentic AI in healthcare" means at the organization. You'll still write code and tackle hard technical problems directly, but your primary impact will be through systems, standards, and people you influence across teams.
Key responsibilities include:
- Define multi-year technical strategy and architecture for agentic workflow infrastructure supporting 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 that inform QH's AI governance approach
- Serve as technical escalation point for the hardest, highest-ambiguity problems across product lines
- Mentor and develop Staff-level engineers; shape the technical career ladder for applied AI roles
- Evaluate emerging models, frameworks, and techniques (OpenAI, Anthropic, Mistral, etc.) and determine adoption strategy
- Partner with founders and engineering leadership on how AI infrastructure investment ties to company strategy
Qualified Health is a seed-stage company redefining what's possible with Generative AI in healthcare. The infrastructure provides guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring, working alongside leading health systems to drive real change.
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 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 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 regulated or high-stakes domain (healthcare, finance, etc.)
- History of founding or scaling a technical function from the ground up in startup environment
- Experience mentoring Staff-level engineers and shaping technical career ladders
