Qualified Health PBC is seeking a Staff Applied AI Engineer to take technical ownership of how it builds and scales agentic workflows across multiple product lines. This onsite role in Palo Alto, CA focuses on creating the infrastructure and engineering standards that help teams ship AI-powered features with reliability, speed, and consistency.
You will help shape the way the organization translates healthcare AI challenges into scalable systems by setting architectural patterns, building reusable infrastructure, and partnering closely with product and design to define the technical roadmap.
What you’ll build and improve
- Architect and build core agentic workflow infrastructure supporting 100+ workflows across multiple product lines.
- Define technical standards and reusable patterns for the team, including eval pipelines, prompt frameworks, and deployment patterns.
- Lead design and code review for complex, cross-cutting integrations and production services.
- Drive evaluation and adoption decisions for state-of-the-art LLMs such as OpenAI, Anthropic, and Mistral, including build-versus-buy tradeoffs for different use cases.
- Mentor engineers on production-grade agentic system design, MLOps practices, and how to ship quickly 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 slow broader execution.
Core requirements
- Strong software engineering foundation with Python required and deep familiarity with production system design.
- 5+ years building production software, including 2+ years building AI-powered applications with LLMs (ChatGPT, Claude, Anthropic, Mistral, etc.).
- Proven experience architecting REST APIs and services deployed at scale in cloud environments (GCP preferred).
- Strong grasp of MLOps, model deployment, and workflow automation, with experience setting standards or infrastructure other engineers build on.
- Track record of driving technical decisions with significant ambiguity and minimal oversight.
Helpful background
- Bachelor’s degree + 7 years OR Master’s degree + 5 years in Computer Science, Engineering, or a related field (or equivalent experience).
- Experience across both software engineering and ML/AI systems.
- Experience designing eval pipelines, prompt tuning frameworks, or automation infrastructure at a platform level.
- Startup experience with a bias toward shipping fast and iterating.
- Exposure to both startup agility and the engineering rigor of a mature, at-scale codebase.
- Experience mentoring engineers or setting technical direction for a team.
Compensation and benefits
Pay range: $200,000 to $260,000 per year, depending on skills, qualifications, experience, and location.
- Competitive salaries with equity packages
- Medical/dental/vision insurance
- Flexible working hours
- Hybrid work options
- Inclusive environment that fosters creativity and innovation
- Eligible for equity and benefits
Technologies: Python, OpenAI, Anthropic, Mistral, ChatGPT, Claude, REST APIs, GCP, LLMs
