Senior Staff Applied AI Engineer

Qualified Health

. Define the technical architecture and roadmap for agentic workflow infrastructure shared across multiple product lines .

Posted 11/12/2026full-timePalo Alto • California • United StatesSenior💰 $250,000 - $310,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in software engineering and machine learning, with a strong focus on LLM evaluation, deployment, and AI governance. Proven ability to mentor engineers and influence technical decisions across product lines in high-stakes environments.

Highest-signal resume keywords

Python ProgrammingMachine Learning EngineeringLLM DevelopmentMLOpsAI Infrastructure Building

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringMachine Learning FundamentalsModel TrainingModel EvaluationWorkflow AutomationTechnical Direction SettingProduction DeploymentScaling ML ModelsMonitoring ML SystemsAI Governance

Soft Skills

MentoringInfluencing Technical DecisionsAutonomous Problem Solving

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Computer Science

Industry Keywords

Applied AIAgentic SystemsRegulated DomainHigh-Stakes EnvironmentStartup Experience

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Define the technical architecture and roadmap for agentic workflow infrastructure shared across multiple product lines
Partner with engineering leadership on build-vs-buy and platform investment decisions
Set engineering standards for LLM evaluation, deployment, safety, and monitoring across several teams
Help shape Qualified Health's AI governance approach
Act as a technical escalation point for high-ambiguity problems crossing product lines
Mentor and develop Staff and Senior engineers
Contribute to the applied AI career ladder
Track frontier AI companies and technologies, including OpenAI, Anthropic, and Mistral, and decide what to adopt at Qualified Health

Requirements

What you’ll need

Deep software engineering foundation; Python required
9+ years building production software and ML engineering
2+ years of hands-on production LLM or agentic work
Strong foundation in machine learning fundamentals
Hands-on experience developing, training, fine-tuning, and evaluating ML models
Experience taking ML models from experimentation through production deployment, scaling, monitoring, and ongoing optimization
Strong understanding of ML pipelines, model serving, and MLOps
Deep expertise in workflow automation for AI-driven systems at a platform level
Experience setting technical direction and standards across more than one product line
Ability to operate autonomously on ambiguous, high-stakes problems
Experience influencing technical decisions with engineering leadership and non-technical stakeholders
Bachelor's degree + 11 years OR Master's degree + 9 years in Computer Science, Engineering, or related field (or equivalent experience)
Recognized expertise in applied AI or agentic systems
Experience building AI infrastructure in a regulated or high-stakes domain
History of building or scaling a technical function in a startup
Experience mentoring Staff-level engineers
Legally authorized to work in the United States for any employer without requiring sponsorship now or in the future

Benefits

Comp & perks

Equity packages
Medical insurance
Dental insurance
Vision insurance
Flexible working hours
Hybrid work options
Inclusive environment that fosters creativity and innovation