This team operate like an innovative startup within Workday: fast-moving, highly collaborative, and deeply technical, while still benefiting from Workdays scale and stability. Youll partner closely with product, engineering, data labeling, design, and go-to-market teams to ship consumer-grade, AI-first experiences that help recruiters and hiring teams spend more time with people and less time with software.
As an AI Product Manager on the Paradox team, you will own the product lifecycle for core LLM-powered capabilities across candidate and recruiter experiences.
Youll drive product discovery, define requirements, and partner with engineering and data science from design through launch, iteration, and ongoing optimization.
One key part of this role is hands-on AI evaluation. You will regularly review LLM outputs and AI conversation logs, perform data labeling, and dig into traces to identify gaps, edge cases, and failure modes. Youll translate these insights into concrete changes to prompts, data, workflows, and system logic that measurably improve quality, reliability, and user experience.
You will:
Own AI-driven features, including candidate and recruiter-facing experiences.
Define product vision, goals, and roadmaps for your areas, balancing user value, technical feasibility, and business impact.
Lead rigorous evaluation of LLM behavior: review outputs, label data, and partner with data science to refine prompts, metrics, and evaluation strategies.
Collaborate closely with engineering to design scalable, robust solutions and iterate quickly on experiments.
Synthesize input from customers, internal stakeholders, and the market into clear, prioritized product requirements.
Communicate progress, tradeoffs, and learnings across a global, cross-functional set of partners, guiding teams toward high-impact outcomes.
Basic Qualifications:
4+ years of experience as a Product Manager (or technical role with clear PM trajectory).
Proven experience delivering LLM-based products into production (handling latency, costs, guardrails, and real-user edge cases).
Hands-on experience with GenAI architectures & evaluations: Strong grasp of RAG, prompt engineering, and core LLM evaluation frameworks (e.g., benchmark datasets, output validation).
Strong cross-functional collaboration skills, bridging technical teams (DS/Eng) and non-technical stakeholders (CSM, Business).
Proven ability to turn ambiguous problems into clear product decisions and priorities.
Other Qualifications:
Experience building agentic workflows or complex multi-agent systems (e.g., tool use, function calling, autonomous execution).
Prior experience in HR Tech or Talent Acquisition workflows.
Hands-on experience building/optimizing fine-tuning or RLHF pipelines.
Track record in a fast-paced 0→1 / early-stage product environment.
