IT Internal Auditor - Advisor

Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. Here, your expertise can help fuel purpose-driven innovation that expands access to home ownership and affordable rental housing across the country. Join Fannie Mae to grow your career and help people find a place to call home.

Job Description Our team of trusted audit professionals evaluates every aspect of Fannie Mae’s IT environment. From on-premises environments to cutting edge cloud services, our audits cover the broad range of exciting technologies Fannie Mae uses, providing a challenging environment with tremendous opportunities for personal growth.

Within IT Audit, the infrastructure team focuses on evaluating Fannie Mae’s complex environment of IT processes, systems, and services. We conduct audits focused on highly visible topics, such as cyber security, IT Governance, resiliency, and the management of the various operating systems and platforms used by Fannie  this position, you will push us forward in our journey to increase the use of advanced data analytics, modeling, and AI to more effectively assess the IT environment.

THE IMPACT YOU WILL MAKEThe IT Internal Auditor - Advisor role will offer you the flexibility to make each day your own, while helping to improve the governance, risk, and control environment related to important risks such as cyber security and resiliency. You will act as a key driver of developing and deploying generative Artificial Intelligence (AI), advanced analytics, and continuous analytics while supporting our IT audits by:

Identify, review, and acquire data from primary or secondary data sources. Establish associated data interfaces and ingestion processing frameworks.

Implement new statistical modeling capabilities that help identify risks and control gaps in the IT environment.

Apply and build new advanced analytic capabilities to support the integration of data and statistical models or algorithms into day-to-day IT audit work. Apply industry practices in research and testing to product development, deployment, and maintenance.

Create new modeling/statistical applications to support risk measurement and automated control testing.

Design and implement data visualizations, technical documentation, and non-technical presentation materials to communicate complex ideas and findings to audit teams and clients.

Develop Retrieval-Augmented Generation (RAG) and Agentic AI workflows.

Integrate LLMs (Gemini, Claude, GPT-4o) into the audit process, both for audit data and audit evidence.

Act as a source of knowledge related to AI and data analytics.

Build and maintain relationships with business partners.

THE EXPERIENCE YOU BRING TO THE TEAM Minimum Required Experience6+ years of experience in programming in data analytics related languages, such as Python, R, or JavaScript.
3+ years in ML engineering, including 3+ years hands-on with Generative AI/LLMs and 2+ years with knowledge graph technologies.

Curiosity and adaptability learning and responsibly applying new techniques, including artificial intelligence, to reimagine how we work.

Desired Experience Master’s degree in Computer Science, Statistics, Mathematics, or related area of study

Ability to apply statistical or computational methods to real-world data and tailoring analysis to answer complex questions or problems

Strong coding skills and experience with data analytics related languages, such as Python (including Sci Py, Num Py, and/or PySpark) and/or Scala.

Visualization:

Strong skills in identifying, designing, and implementing visualizations of various data sets

Experience with visualization tools (e.g., Power Bi, Tableau, Plotly, Seaborn)
Generative AI:

Proven experience building AI solutions using advanced prompt engineering (Chain of Thought, Tree of Thought) and designing and deploying RAG pipelines

Experience with validation of LLM outputs and reduction of hallucinations

Knowledge of Agentic AI architecture, and knowledge graph integration with LLMs (e.g., Graph

RAG, ontology-driven prompt engineering, hybrid reasoning systems).Hands-on work with vector databases (Pinecone, Chromadb) and frameworks like Lang Chain/Llama Index…