Manager, AI Audit Innovation

PayPal PayPal · Fintech · Austin, TX +4 · Data Science

Manager role focused on designing, developing, and deploying AI-powered solutions and automation frameworks for the Global Internal Audit team. This involves translating audit objectives into technical solutions, managing AI initiatives end-to-end, ensuring secure and responsible integration with enterprise governance and regulatory standards, and evaluating emerging AI/ML/LLM technologies. The role requires hands-on AI engineering experience, building AI agents and automation frameworks, and integrating AI tools with enterprise systems.

What you'd actually do

  1. Partner with audit teams to define and build high impact AI use cases, translating audit objectives into scalable technical solutions.
  2. Lead the end-to-end design and deployment of AI-powered applications and automation frameworks across audit workflows, partnering with cross functional teams to ensure solutions comply with enterprise AI governance standards and regulatory requirements
  3. Establish performance metrics and continuously optimize solutions to drive measurable improvements in audit efficiency and effectiveness.
  4. Produce and maintain comprehensive technical documentation, including model artifacts, system architecture diagrams, validation protocols, and data lineage documentation to ensure transparency and auditability.
  5. Drive adoption of AI solutions within Internal Audit by designing user-centric implementations, communicating technical concepts in accessible terms, and providing training and hands-on support to ensure audit teams successfully integrate AI into their daily workflows.

Skills

Required

  • 6 years of experience in data science, AI/ML, analytics, or advanced engineering roles
  • Bachelor’s degree in Computer Science, Engineering, Statistics, or related field
  • Hands on experience designing and deploying AI/ML solutions in production
  • Experience with enterprise LLM tools (e.g., Claude, ChatGPT, Perplexity)
  • Experience building or managing AI agents and automation frameworks
  • Advanced proficiency in Python and SQL
  • Experience implementing CI/CD, containerization, or MLOps practices.
  • Experience with Jupyter Notebooks and large-scale data platforms (e.g., BigQuery)
  • Experience with cloud platforms (AWS, Azure, GCP) and related AI services
  • Understanding of model governance, validation, and responsible AI practices

Nice to have

  • Experience in Internal Audit, Risk, Compliance, or Financial Services
  • Experience integrating AI tools with enterprise systems
  • Familiarity with audit management systems or GRC platforms
  • Advanced degree (MS or PhD) in Machine Learning, Statistics, or Computer Science

What the JD emphasized

  • AI Audit Innovation
  • AI and automation solutions
  • AI-powered solutions
  • AI engineering
  • AI initiatives
  • AI capabilities
  • AI use cases
  • AI-powered applications
  • AI governance standards
  • AI solutions
  • AI, machine learning, and LLM technologies
  • enterprise AI platforms
  • LLM tools
  • AI tools
  • AI solutions
  • AI tools
  • AI/ML
  • AI/ML solutions
  • LLM tools
  • AI agents
  • AI/ML
  • responsible AI practices
  • AI tools
  • AI tools
  • regulatory requirements
  • model governance
  • responsible AI practices

Other signals

  • AI Audit Innovation
  • AI and automation solutions
  • AI-powered solutions
  • AI engineering
  • AI initiatives
  • AI capabilities
  • AI use cases
  • AI-powered applications
  • AI governance standards
  • AI solutions
  • AI, machine learning, and LLM technologies
  • enterprise AI platforms
  • LLM tools
  • AI tools
  • AI solutions
  • AI tools
  • AI/ML
  • AI/ML solutions
  • LLM tools
  • AI agents
  • AI/ML
  • responsible AI practices
  • AI tools
  • AI tools