Lead Internal Audit Developer (Innovation Team)

TIAA•Frisco, TX

4d•$111,000 - $153,000

About The Position

Internal Audit Developer The Internal Audit Developer job reviews complex analytics on confidential and time sensitive internal audit and investigations projects. With guidance from senior management, this job manages projects and develops solutions that help identify potential internal controls issues through analytics and automation. As a subject matter expert in internal audit data analytics, this job helps define data analytic standards for the Internal Audit Services function. Key Responsibilities and Duties Design and develop Internal Audit’s Artificial Intelligence solution and other innovation tools as required. This includes backend and front-end development work, database & data engineering and server & infrastructure management. Build AI workflows that can call tools/APIs, reason over intermediate results, and complete complex tasks. Design context and memory management and implement strategies for managing context and memory across interactions to allow AI models to work over large and evolving information. Design and build front end code using React JS for user-facing AI solutions. Ensure secure connectivity with backend services. Keep up to date with latest technologies and frameworks in AI to identify and integrate the latest models, RAG techniques, and agentic frameworks to solve unique business challenges. Partner closely with audit teams to understand their needs, challenges, and priorities, ensuring innovation initiatives deliver practical value to day-to-day audit work. Establish and maintain close, ongoing interaction and feedback loops with audit teams to ensure innovation solutions are grounded in real audit needs and effectively address operational challenges. Drive AI capability development and deployment that advance audit effectiveness and efficiency through continuous collaboration with audit practitioners. Support governance and control initiatives associated with development and deployment of Internal Audits AI solution. Lead knowledge sharing initiatives and foster a community of practice around data analytics and AI within IAS, emphasizing accessible communication and practical application of technical concepts.

Requirements

3+ years of software development, data engineering, data analytics, data management and/or AI/ML development experience
Data analytics experience including the concepts of data management, ETL, stored procedures and building complex queries using SQL and developing reports and BI dashboards using power BI/Tableau
Strong proficiency in Python for AI/ML development and backend engineering.
Proficiency in React JS or similar modern JavaScript frameworks for frontend development.
Experience building AI workflows, integrating APIs, and implementing RAG techniques and agentic frameworks.
Knowledge of AI/ML frameworks (e.g., LangChain, LangGraph, TensorFlow, PyTorch) and context/memory management in AI systems.
Experience with database design, data engineering, and SQL development.
Proven experience with cloud infrastructure and server management (AWS, Azure, or GCP).
Proficiency with version control systems (Git) and CI/CD pipelines

Nice To Haves

5+ years of software development, data engineering, data analytics, data management and/or AI/ML development experience

Responsibilities

Design and develop Internal Audit’s Artificial Intelligence solution and other innovation tools as required.
Build AI workflows that can call tools/APIs, reason over intermediate results, and complete complex tasks.
Design context and memory management and implement strategies for managing context and memory across interactions to allow AI models to work over large and evolving information.
Design and build front end code using React JS for user-facing AI solutions.
Ensure secure connectivity with backend services.
Keep up to date with latest technologies and frameworks in AI to identify and integrate the latest models, RAG techniques, and agentic frameworks to solve unique business challenges.
Partner closely with audit teams to understand their needs, challenges, and priorities, ensuring innovation initiatives deliver practical value to day-to-day audit work.
Establish and maintain close, ongoing interaction and feedback loops with audit teams to ensure innovation solutions are grounded in real audit needs and effectively address operational challenges.
Drive AI capability development and deployment that advance audit effectiveness and efficiency through continuous collaboration with audit practitioners.
Support governance and control initiatives associated with development and deployment of Internal Audits AI solution.
Lead knowledge sharing initiatives and foster a community of practice around data analytics and AI within IAS, emphasizing accessible communication and practical application of technical concepts.