Title : - AI/ML Engineer Location : - Reston, VA (Hybrid) Duration : - 12 Months of Contract Description Top Skills' Details • 7-10 years of experience working as python/ML Engineer with strong Python, SQL, and AWS • LLM's - RAG, AWS Bedrock, standard AWS services Job Description Models are being audited in Fannie Mae , this team will do the audit testing with different models to see if the model is doing what it is supposed to do, any gaps. These are all the models Fannie Mae uses across the enterprise that are being audited. This is a combination of a data analysts with experience in prompt engineering. Prompt engineering, writing code, data analysis - write queries Looking for someone with strong Python, SQL, AWS - ability to understand financial models Any experience with LLMs - they are using Anthropic and AWS Bedrock Experience 8+ years overall in Software Engineering disciplines, preferably in the financial services industry 2-3 years of experience in AI/ML engineering roles Strong programming skills in Python, SQL and experience with AWS. Key Responsibilities Design, test, and refine prompts for large language models (LLMs) to support financial reporting, summarization, and client communication tools. Analyze structured and unstructured financial data using Python and SQL, delivering insights through dashboards and reports. Develop and maintain data pipelines and ETL workflows to support GenAI model training and evaluation. Use AWS SageMaker to build, train, and deploy machine learning and GenAI models. Collaborate with data scientists, analysts, and business stakeholders to align AI solutions with financial objectives. Monitor model performance, iterate on prompt, and model design to improve accuracy and relevance. Document workflows, models, and prompt strategies for internal knowledge sharing and compliance. Required Qualifications 2 3 years of experience in data analysis or machine learning roles. Proficiency in Python and SQL for data manipulation and analysis. Hands-on experience with major AWS services, particularly SageMaker, S3, Redshift, and Lambda. Experience working with LLMs (Anthropic Claude, Sonnet) and prompt engineering techniques. Strong understanding of financial data, KPIs, and reporting standards. Excellent communication and collaboration skills. Preferred Qualifications Experience in the finance or fintech industry. Familiarity with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG). Exposure to data visualization tools (e.g., Power BI, Tableau). Understanding of MLOps practices and model lifecycle management. Education Bachelor's degree in Computer Science, Data Science, Finance, or a related field. Additional Skills & Qualifications: Need someone with strong analytical skills