University 2026 Talent Acquisition AI Product Engineering Intern
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Overview
Job Description
Company Overview
ID.me is the next-generation digital identity wallet that simplifies how individuals securely prove their identity online. Consumers can verify their identity with ID.me once and seamlessly login across websites without having to create a new login and verify their identity again. Over 152 million users experience streamlined login and identity verification with ID.me at 20 federal agencies, 45 state government agencies, and 70+ healthcare organizations. More than 600+ consumer brands use ID.me to verify communities and user segments to honor service and build more authentic relationships. ID.me’s technology meets the federal standards for consumer authentication set by the Commerce Department and is approved as a NIST 800-63-3 IAL2 / AAL2 credential service provider by the Kantara Initiative. ID.me is committed to “No Identity Left Behind” to enable all people to have a secure digital identity. To learn more, visit https://network.id.me/.
Role Overview
ID.me is seeking an AI Product Engineering Intern to embed within our Talent Acquisition organization and design intelligent systems that operate on top of our production HR infrastructure. This is not a traditional HR internship — it is an applied AI systems role focused on building agentic workflow automation that increases hiring velocity, operational rigor, and executive visibility.
As an intern, you will architect and ship decision-support agents that integrate with systems such as Greenhouse, Ashby, Slack, and sourcing platforms to transform recruiting from reactive process management into a live, orchestrated operating system. You will work at the intersection of AI, automation, behavioral design, and production-grade workflow infrastructure, partnering closely with Talent leadership and engineering stakeholders. Your work will directly impact hiring outcomes, recruiter productivity, and organizational scale readiness.
This role is based in our Mountain View office and requires full-time in-office attendance.
What You’ll Build
You will design and deploy agentic systems that operate strictly as human-in-the-loop decision support tools, with clear governance guardrails and compliance-aware architecture.
Offer Close Autopilot (“Hiring Deal Desk Agent”)
Design an intelligent closing support system that monitors late-stage candidate engagement signals — stage velocity, response timing, calendar friction, reschedule patterns, and market competitiveness indicators — to surface real-time risk insights. The system will generate personalized sell narratives, suggest compensation positioning within approved bands, and recommend executive intervention when appropriate. The agent will never make autonomous hiring or compensation decisions; instead, it will provide structured visibility and close-probability insights to support human judgment. This system introduces executive-level leverage to offer closing without automating selection decisions.
Recruiting Chief of Staff Bot (“Pipeline Autopilot”)
Build an orchestration agent using ATS webhooks that detects stalled candidates, missing feedback, interviewer scoring variance, and requisitions outside SLA. The system will generate contextual Slack nudges to hiring managers, draft recruiter updates, and recommend process optimizations such as batching interviews or consolidating loops. It will focus exclusively on workflow efficiency and behavioral nudging — not candidate evaluation or ranking — improving consistency and velocity across the hiring lifecycle.
Talent Radar (“Agentic Sourcing Swarm”)
Develop a sourcing intelligence engine for high-priority roles that translates hiring intake into structured competency maps, identifies market adjacency clusters, generates longlists, and groups prospects into skill archetypes. The system will produce transparent rationales for each recommendation, confidence indicators, and hyper-personalized outreach drafts. All outreach requires human approval prior to execution, ensuring compliance and ethical guardrails. This platform shifts sourcing from Boolean search to pattern-based intelligence while maintaining full human oversight.
Responsibilities
- Architect and deploy AI-driven workflow agents operating on top of live HR systems
- Design human-in-the-loop decision-support frameworks with transparent logic and rationale
- Integrate with ATS platforms, communication tools, and sourcing systems via APIs and webhooks
- Implement governance-aware design that avoids automated candidate selection or compensation determination
- Build dashboards, monitoring tools, and feedback loops to measure system impact
- Partner with Talent leadership to prioritize high-leverage automation opportunities
- Document systems for scale, audit readiness, and operational continuity
Minimum Qualifications
- Currently pursuing an MBA or a Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or a related technical field.
- Strong programming experience (Python preferred) and comfort working with APIs and production systems
- Experience building automation workflows or AI-enabled applications
- Familiarity with LLM prompting, agent frameworks, or orchestration systems
- Strong systems thinking and ability to design for reliability and governance
Preferred Qualifications
- Experience with workflow automation tools, webhooks, or event-driven architecture
- Exposure to data modeling, clustering, or pattern-recognition systems
- Experience building human-in-the-loop AI systems
- Interest in organizational design, operations, or behavioral systems
- Ability to translate ambiguous operational challenges into structured technical solutions
Why This Role Is Unique
Most HR organizations use dashboards. Very few operate intelligent agents that actively orchestrate workflow in real time. This internship provides the opportunity to design and ship production-grade AI systems that directly influence hiring velocity, executive visibility, and organizational scale. If you are an engineering student who wants to apply AI beyond prototypes — and instead build systems that meaningfully reshape how a company hires — this role offers outsized impact.
ID.me is a full-time, in-office culture. Unless a specific job description explicitly states otherwise, all roles are on-site five days per week at one of our offices in McLean, VA; Mountain View, CA; New York City, NY; or Tampa, FL. Certain roles — such as field-based sales or other remote-by-design positions — may have different work arrangements as noted in their individual postings.
ID.me maintains a work environment free from discrimination, where employees are treated with dignity and respect. All ID.me employees share in the responsibility for fulfilling our commitment to equal employment opportunity. ID.me does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. ID.me adheres to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, ID.me's policy is to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works. Upon request we will provide you with more information about such accommodations.
Please review our Privacy Policy, including our CCPA policy, at id.me/privacy. If you provide ID.me with any personally identifiable information you confirm that you have read and agree to be bound by the terms and conditions set out in our Privacy Policy.
ID.me participates in E-Verify.
Automate your job search with Sonara.
Submit 10x as many applications with less effort than one manual application.
