Applied AI Engineer

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.

Job Summary:

We're hiring a Staff Applied AI Engineer to take technical ownership of how we build and scale agentic workflows across Qualified Health's product lines. This role goes beyond shipping individual workflows — you'll set the architectural patterns, reusable infrastructure, and engineering standards that let the rest of the team build faster and more reliably. You'll operate with significant autonomy, driving technical direction on ambiguous problems with minimal oversight, while still being hands-on in the code.

You'll partner closely with engineering leadership, product, and design to translate healthcare-specific AI challenges into scalable systems, and you'll be a technical anchor other engineers look to for guidance on agentic workflow design.

Key Responsibilities:

• Architect and build the core agentic workflow infrastructure supporting 100+ workflows across multiple product lines.

• Set technical standards and reusable patterns (eval pipelines, prompt frameworks, deployment patterns) for agentic workflow development team-wide.

• Lead design and code review for complex, cross-cutting integrations and production services.

• Drive evaluation and adoption decisions for state-of-the-art LLMs (OpenAI, Anthropic, Mistral, etc.) across use cases, including build-vs-buy tradeoffs.

• Mentor engineers on production-grade agentic system design, MLOps practices, and shipping fast without sacrificing reliability.

• Partner with product, engineering, and design leadership to shape the technical roadmap for AI-powered features.

• Identify and resolve systemic bottlenecks in the workflow infrastructure before they block the broader team.

Required Qualifications:

• Strong software engineering foundation (Python required; deep familiarity with production system design).