Principal Applied AI Lead (AI)

TL;DR

Principal Applied AI Lead (AI): Developing and deploying AI agents and automation tools to optimize Talent Acquisition workflows with an accent on bridging the gap between AI capabilities and operational needs. Focus on building functional prototypes using LLM APIs and agent frameworks, establishing governance, and scaling AI adoption across the organization.

Location: San Diego, California or Mountain View, California

Company

hirify.global is a global financial technology platform powering prosperity through products like TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

• Identify high-value AI and automation opportunities within Talent Acquisition (TA) workflows.
• Design and build working AI prototypes using LLM APIs, agent frameworks, and automation tools.
• Run structured pilots and tool evaluations with defined success criteria and govern scaled deployment.
• Translate validated prototypes into clear technical requirements for engineering production.
• Develop governance frameworks, playbooks, and performance metrics for AI agents in production.
• Increase AI fluency across TA team members through hands-on sessions and clear frameworks.

Requirements

• 6+ years of experience in Talent Acquisition, TA operations, or HR combined with hands-on AI implementation.
• Proven track record of building solutions using LLM APIs, prompt engineering, and agent frameworks.
• Experience taking AI solutions from concept through to production deployment.
• Strong process design instincts with experience writing governance frameworks or SOPs.
• Ability to influence stakeholders without direct authority and translate complex AI concepts into plain language.
• Must be based in San Diego, California or Mountain View, California

Culture & Benefits

• Competitive compensation package with a strong pay-for-performance rewards approach.
• Eligibility for cash bonuses and equity rewards.
• Comprehensive benefits programs for full-time employees.
• Commitment to fair pay through regular ethnicity and gender comparisons.