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AI Governance and Compliance Specialist - Global Security Organization

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: TikTok
Full Time position
Listed on 2026-08-08
Job specializations:
  • IT/Tech
    Information Security & Data Protection, Cybersecurity, Data Scientist, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 111600 - 162000 USD Yearly USD 111600.00 162000.00 YEAR
Job Description & How to Apply Below

Discover a career that energizes and excites you every day.

@2026 Tik Tok

Security

AI Governance and Compliance Specialist - Global Security Organization

Location:

San Jose

Employment Type:

Regular

Job Code:

A02882A

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Responsibilities
  • Regulatory Readiness & Operational Controls
    - Regulatory Mapping:
    Interpret global AI and platform safety laws (e.g., EU DSA, EU AI Act, US state laws like CA SB 1047 / Colorado AI Act) and translate requirements into actionable technical guardrails for recommendation and Algorithmic systems.
  • Recommender Compliance:
    Execute compliance strategy for Recommender specific mandates, including options for non-profiling recommendation feeds, ad/content parameter disclosures, and systemic risk mitigation for content curation.
  • Model Risk Tiering & Auditability:
    Evaluate recommendation architectures, input data, and optimization objectives to assign appropriate regulatory risk classifications. Build automated tracking systems that log model lineage, training parameters, and evaluation results to ensure end-to-end traceability for compliance audits.
  • Technical Assurance and Model Auditing
    - Systemic Risk Mitigation Pipelines:
    Design operational guardrails to prevent feed algorithms from amplifying illegal content, severe disinformation, hate speech, or content linked to mental health harms and minor safety.
  • Algorithmic Bias & Fairness Testing:
    Conduct quantitative pre-release and post-release audits evaluating candidate generation (retrieval) and ranking stages for popularity bias, demographic disparity, and filter-bubble formation.
  • ML-SDLC Governance Gates:
    Ensure compliance sign-off gates into the Machine Learning Software Development Lifecycle (ML-SDLC), ensuring no high-risk recommendation model ships to production without documented clearance.
  • Third-Party Audit Package Preparation:
    Assemble end-to-end evidence packages, data samples, and code/architecture explanations for external statutory auditors and regulatory bodies.
  • Audit Readiness & External Engagement
    - Regulatory Liaison:
    Act as the primary technical point of contact during independent third-party audits, regulatory inquiries, or statutory compliance filings.
  • Auditing Rigor:
    Exceptional attention to detail in constructing audit trails, technical documentation, and regulatory evidence packages.
  • Engineering & Legal Bridge:
    Serve as the translator between Machine Learning Engineers/Data Scientists and Legal/Policy teams to align model architecture choices with legal defensibility.
  • Global Process Enablement:
    Establish standardized playbooks and repeatable compliance protocols for recommendation engine risk assessments, ensuring consistent regulatory adherence across diverse geographic markets and product verticals.
Qualifications

Minimum Qualifications
  • Proven track record in successfully developing, implementing, and managing comprehensive compliance programs at scale with experience engaging directly with regulators, external auditors, or supervisory bodies on algorithmic or AI compliance matters.
  • Deep understanding of recommendation systems, ranking algorithms, recommendation architectures, and content distribution pipelines at scale.
  • Proficiency in Python, SQL, and data analysis; experience with ML frameworks (e.g., PyTorch, Tensor Flow) and experimentation platforms.
  • Exceptional analytical, critical thinking, and problem-solving skills, coupled with the ability to translate complex legal and technical concepts into clear, actionable advice for diverse technical and non-technical audiences.
  • Demonstrated ability to work independently, effectively manage multiple competing priorities, and thrive in a fast-paced, dynamic, and often ambiguous environment.
Preferred Qualifications
  • Bachelor’s degree in Computer Science, Data Science, Information Policy, Law & Technology, or a related quantitative/policy discipline.
  • 4+ years of professional experience in AI/ML governance, tech compliance, algorithmic auditing, or responsible AI engineering.
  • Solid understanding and practical experience in Global regulations (e.g., DSA, OSA, GDPR, AI Governance Act), including practical experience in their application.
  • Strong foundational…
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