Sr. Staff Applied AI Engineer
Palo Alto, CA · HybridJob$250–310K/yrPosted 1 day agoStill listed today
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At a glance
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Job overview
Qualified Health is hiring a Sr. Staff AI Engineer to set technical direction for agentic AI systems across multiple product lines. The role defines shared architecture and engineering standards, informs platform investment, and remains hands-on with complex technical problems. It also establishes practices for LLM evaluation, deployment, safety, and monitoring, while mentoring engineers and shaping the company’s AI governance approach.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
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 Sr. Staff AI Engineer to set the technical direction for how Qualified Health builds agentic AI systems across multiple product lines. You’ll define shared architecture and engineering standards, work with engineering leadership on platform investment, and remain hands-on with the hardest technical problem
Key Responsibilities
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Define the technical architecture and roadmap for agentic workflow infrastructure shared across multiple product lines.
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Partner with engineering leadership on build-vs-buy and platform investment decisions.
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Set engineering standards for LLM evaluation, deployment, safety, and monitoring across several teams, and help shape QH’s AI governance approach.
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Act as a technical escalation point for high-ambiguity problems that cross product lines.
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Mentor and develop Staff and Senior engineers and contribute to the applied AI career ladder.
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Track the frontier (OpenAI, Anthropic, Mistral, etc.) and decide what is worth adopting at QH.
Required Qualifications
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Deep software engineering foundation (Python required) with a track record of architecting systems used across multiple teams.
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9+ years building production software and ML engineering, including 2+ years of hands-on production LLM or agentic work.
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Strong foundation in machine learning fundamentals, with hands-on experience developing, training, fine-tuning, and evaluating ML models. Experience may include traditional ML, deep learning, predictive modeling, NLP, or other applied ML disciplines.
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Proven experience taking machine learning models from experimentation and development through production deployment, scaling, monitoring, and ongoing optimization, including at the platform level. Strong understanding of ML pipelines, model serving, and MLOps.
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Deep expertise in workflow automation for AI-driven systems at a platform level.
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Proven experience setting technical direction and standards adopted across more than one product line.
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Demonstrated ability to operate with high autonomy on ambiguous, high-stakes problems.
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Track record influencing technical decisions with engineering leadership and non-technical stakeholders.
Desirable Skills
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Bachelor’s degree + 11 years OR Master’s degree + 9 years in Computer Science, Engineering, or related field (or equivalent experience).
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Recognized expertise (talks, publications, open source, prior platform-level roles) in applied AI or agentic systems.
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Experience building AI infrastructure in a regulated or high-stakes domain (healthcare, finance, etc.).
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History of building or scaling a technical function in a startup.
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Experience mentoring Staff-level engineers.
Why Join Qualified Health? This is an opportunity to join a fast-growing company and a world-class team, that is poised to change the healthcare industry. We are a passionate, mission-driven team that is building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers. Our employees are integral to achieving our goals so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options and an inclusive environment that fosters creativity and innovation.
Our Commitment to Diversity Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.
Pay & Benefits: The pay range for this role is between $250,000 and 310,000, depending on skills, qualifications, experience, and location. This role is also eligible for equity and benefits. Join our mission to revolutionize healthcare with AI. To apply, please send your resume through the application below.
How this job compares
Set against the 6,245 open Machine Learning Engineer jobs on Olive Jobs, counted November 13, 2026.
- Pay
- This posting$250–310K/yr
- California median$176–261K/yr1,406 salary ranges
- US median$145–244K/yr5,192 salary ranges
This range's midpoint, $280K, is 27% above the California median midpoint ($220K) — in the top quarter of Machine Learning Engineer salary ranges in California.
- Openings
- Olive Jobs lists 1,833 open Machine Learning Engineer jobs in California and 6,245 across the US. 7% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 11 years of experience — more than three in four Machine Learning Engineer postings that state a minimum ask for (median 5 years, across 5,158 postings).
- Education
- 2,123 of the 6,245 open Machine Learning Engineer jobs (34%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 13, 2026. Figures based on too few postings are left out.
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