Senior Ta Operations Specialist

GitLab GitLab · Enterprise · United States · Talent Acquisition

Senior TA Operations Specialist responsible for owning and architecting the Talent Acquisition technology infrastructure, including ATS configuration, integrations, and the design, build, and deployment of AI agents and automation workflows. The role involves managing AI governance, bias auditing, and compliance, as well as leading the TA systems roadmap and vendor relationships.

What you'd actually do

  1. Own the end-to-end configuration of the TA tech stack — including ATS stages, fields, picklists, scorecards, user access, and permissions
  2. Design, build, and deploy end-to-end AI agents and automation workflows for recruiter-facing and enterprise TA use cases
  3. Lead the TA systems roadmap — owning evaluation, RFPs, and tech stack planning for the TA team
  4. Own AI governance framework and policy for the TA function — including bias auditing and fairness reviews for all AI tools and agents
  5. Contribute AI agent performance data to TA dashboards and own AI performance reporting

Skills

Required

  • Demonstrated experience owning and configuring enterprise ATS platforms and HR/TA tech stacks including stages, fields, integrations, and user access management
  • Hands-on experience building and deploying AI agents or automation workflows in an enterprise environment
  • Strong understanding of prompt engineering, LLM behavior, and model performance monitoring
  • Experience managing integrations across platforms — including diagnosing and resolving integration failures
  • Familiarity with AI governance, bias auditing, and compliance frameworks
  • Experience in recruiting operations, HR tech, or a related domain required

Nice to have

  • A genuine curiosity about emerging recruiting technology — you bring ideas before you're asked

What the JD emphasized

  • AI agent development
  • automation workflows
  • AI governance framework
  • bias auditing
  • fairness reviews

Other signals

  • AI agent development
  • automation workflows
  • prompt engineering
  • LLM behavior
  • AI governance