Applied AI Engineer
$180k - $250kQualified Health
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 an Applied AI Engineer to focus on building and scaling real-world AI workflows. This role is designed for engineers who are hands-on with deploying generative AI applications. You'll spend the majority of your time developing agentic workflows and production-grade integrations across multiple of our product lines. You'll work closely with product and engineering teammates to design, deploy, and scale AI-powered applications that solve real problems in healthcare. Key Responsibilities:
- Develop and deploy agentic workflows and automation pipelines (approx. 60% of role).
- Build and maintain production-ready services, REST APIs, and integrations (approx. 30%).
- Ship production solutions in days, not months emphasizing scrappiness and speed.
- Collaborate across product, engineering, and design to deliver end-to-end AI-powered features.
- Evaluate and integrate state-of-the-art LLMs (OpenAI, Anthropic, Mistral, etc.) into production use cases.
- Contribute to building a scalable workflow infrastructure that will support 100+ workflows
- Strong software engineering foundation (Python required; solid coding practices).
- Experience building AI-powered applications in the past 1-2 years using ChatGPT, Claude, Anthropic, or Mistral.
- Hands-on experience with REST API development and deploying services into cloud environments (GCP preferred).
- Clear understanding of MLOps, model deployment, or workflow automation in production systems.
- Bachelor's degree + 4 years OR Master's degree + 2 years in Computer Science, Engineering, or related field.
- Background in software engineering → ML path .
- Experience with agentic workflows or adjacent skills such as prompt tuning, eval pipelines, or automation frameworks.
- Startup experience: demonstrated scrappiness, speed, and bias toward shipping.
- Exposure to both startup agility and big tech engineering rigor is ideal.
- Strong communication skills and ability to collaborate in fast-paced, ambiguous environments.
Vacancy posted 4 days ago
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