Principal Applied AI Engineer

Qualified Health

. Define the multi-year technical strategy and architecture for agentic workflow infrastructure supporting the full product portfolio .

Posted 10/7/2026full-timePalo Alto • California • United StatesLead💰 $230,000 - $280,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in Python programming, MLOps, and architecting AI-powered applications, with a strong ability to influence technical decisions and mentor engineering teams. Proven experience in defining technical strategy and standards for AI infrastructure in high-stakes environments.

Highest-signal resume keywords

Python ProgrammingMLOps ExpertiseAI Infrastructure DevelopmentTechnical Strategy DefinitionMentoring Staff-Level Engineers

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Production Software DevelopmentAI-Powered Application ScalingModel DeploymentWorkflow AutomationSystem Architecture

Soft Skills

Influencing Technical DecisionsCross-Functional CollaborationAutonomous Problem Solving

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Engineering

Industry Keywords

Applied AIAgentic SystemsRegulated Domain ExperienceStartup Environment

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Define the multi-year technical strategy and architecture for agentic workflow infrastructure supporting the full product portfolio
Represent applied AI engineering in cross-functional and leadership-level decisions on product direction, build-vs-buy, and platform investment
Set organization-wide engineering standards for LLM evaluation, deployment, safety, and monitoring
Act as a technical escalation point for the hardest, highest-ambiguity problems across product lines
Mentor and develop Staff-level engineers
Help shape the technical career ladder for applied AI roles
Evaluate emerging models, frameworks, and techniques and determine what to adopt
Partner with founders and engineering leadership on how AI infrastructure investment ties to company strategy
Write code and directly address complex technical problems

Requirements

What you’ll need

Python required
8+ years building production software
4+ years building and scaling AI-powered/LLM-driven applications in production
Track record of architecting systems used company-wide
Experience setting technical direction and standards adopted across multiple teams
Deep expertise in MLOps, model deployment, and workflow automation at an organizational/platform level
Ability to operate with full autonomy on ambiguous, high-stakes technical and strategic problems
Strong track record influencing technical decisions at the leadership level, including with non-technical stakeholders
Bachelor's degree + 10 years OR Master's degree + 8 years in Computer Science, Engineering, or related field, or equivalent experience
Recognized expertise in applied AI/agentic systems
Experience building AI infrastructure in a regulated or high-stakes domain
History of founding or scaling a technical function from the ground up in a startup environment
Experience mentoring Staff-level engineers and shaping technical career ladders

Benefits

Comp & perks

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