Principal Applied AI Lead, Talent

Intuit
Bay Area California / Southern California

About the job

We are at an inflection point in how Talent Acquisition operates. AI agents and automation are no longer experiments — they are becoming core to how we attract, assess, and hire at scale. This role exists to make sure we get that transition right. The Principal Applied AI Lead is the person who bridges the gap between what's possible with today's AI tools and what our TA teams actually need. You'll partner directly with recruiting, sourcing, ops, and coordination teams to understand their workflows, identify the highest-value opportunities for AI, and then build working solutions — not decks, not recommendations, actual tools that change how the work gets done. You'll also own the governance layer: how agents are deployed, supervised, measured, and improved over time. This is not a traditional PM role or a pure engineering role. This is someone with genuine TA domain knowledge and real AI fluency who can move fast, exercise high judgment about what's worth building, and own solutions from prototype through production.

Responsibilities

Partner with TA teams across the org to identify the highest-value AI and automation opportunities — distinguishing genuine leverage from novelty

Develop a deep understanding of TA's workflow pain points, data landscape, and strategic priorities to inform where AI creates durable impact

Design and build working AI prototypes and automations — from scoping the problem to putting a functional solution in front of stakeholders for validation

Use LLM APIs, agent frameworks, AI-native platforms, and workflow automation tools to iterate quickly without requiring dedicated engineering resources for every build

Run structured pilots and tool evaluations with defined success criteria — test in controlled environments, measure outcomes, and govern the path to scaled deployment

Translate validated prototypes into clear requirements and partner with engineering to move from proof-of-concept to production

Author and maintain job descriptions for all TA AI agents, defining their responsibilities, decision rights, authorities, and escalation paths

Establish and track performance metrics for each agent — accuracy, timeliness, reliability, process outcomes — and run regular review cycles to drive improvement

Serve as the human supervisor for AI agents in production, maintaining clear accountability for how they're trained, integrated, and escalated

Build the playbooks, workflow blueprints, and governance frameworks that make AI adoption scalable and repeatable across TA

Develop TA team members' AI fluency through hands-on sessions, shared examples, and clear frameworks for when and how to use AI effectively

Collaborate with HR, Legal, and Compliance to ensure all deployments meet regulatory and accountability requirements from the start, not at the end

Stay current on the AI tooling landscape and bring informed, tested recommendations on what the org should adopt, integrate, or build custom

Qualifications

Minimum

6+ years of experience spanning Talent Acquisition, TA operations, or HR — and hands-on AI implementation; you need both, not one or the other

A genuine track record of building things with AI: you have used LLM APIs, prompt engineering, agent frameworks, and automation platforms to create working solutions without heavy engineering support

Experience taking solutions from concept through production deployment, including navigating the technical, organizational, and process realities that come with it

Strong process design instincts — you've written governance frameworks, performance standards, or SOPs and know how to make them usable by real teams

Demonstrated ability to influence without authority — your credibility comes from insight and delivered work, not title

Strong communicator who can translate complex AI capabilities into plain language for TA leaders, and translate fuzzy operational problems into specific, buildable solutions

Preferred

No preferred qualifications listed.