Sr. Associate, Data Engineering & AI

Known for being a great place to work and build a career, KPMG provides audit, tax and advisory services for organizations in today's most important industries. Our growth is driven by delivering real results for our clients. It's also enabled by our culture, which encourages individual development, embraces an inclusive environment, rewards innovative excellence and supports our communities. With qualities like those, it's no wonder we're consistently ranked among the best companies to work for by Fortune Magazine, Consulting Magazine, Seramount, Fair360 and others. If you're as passionate about your future as we are, join our team. KPMG is currently seeking a Sr Associate, Data Engineering & AI to join our Digital Nexus technology team. Responsibilities: Design, build, and manage the full lifecycle of scalable data pipelines and orchestration processes ingesting data into Azure Data LakeDesign and deploy enterprise GenAI applications, intelligent automation systems, and agentic workflows to drive delivery transformationBuild advanced LLM-based systems leveraging Retrieval-Augmented Generation (RAG), fine-tuning, and vector search for context-aware reasoningDevelop high-performance AI pipelines across Databricks, Azure AI Foundry, and Google Vertex AI using Python and PySpark to integrate structured and unstructured dataArchitect dynamic, multi-agent systems (using LangChain/LangGraph) and build reusable Python frameworks for complex multi-step reasoning and tool usageEstablish best practices for AI system evaluation, monitoring, governance, and continuous improvement using feedback loops and human-in-the-loop validation Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment Qualifications: Minimum three years of full systems development lifecycle (SDLC) experience in so ftware engineering, data engineering, or AI/ML rolesBachelor's degree from an accredited college or university is preferred; High School diploma or GED requiredStrong proficiency in Python, SQL, and Azure technologies (ADF, ADB, Key Vault), with deep knowledge of Databricks, PySpark, and enterprise data managementProven experience with modern LLM tooling (LangChain, LangGraph, vector databases) and deploying stateful/agentic workflows on cloud AI platforms (Azure AI Foundry, Vertex AI)Excellent analytical, communication, and Agile project management skills, with the ability to foster high-performance teams and collaborate across all organizational levels KPMG LLP and its subsidiaries (“KPMG”) complies with all local/state regulations regarding displaying salary ranges. If required, the ranges displayed below or via the URL below are specifically for those potential hires who will work in the location(s) listed. Any offered salary is determined based on relevant factors such as applicant's skills, job responsibilities, prior relevant experience, certain degrees and certifications and market considerations. In addition, KPMG is proud to offer a comprehensive, competitive benefits package, with options designed to help you make the best decisions for yourself, your family, and your lifestyle. Available benefits are based on eligibility. Our Total Rewards package includes a variety of medical and dental plans, vision coverage, disability and life insurance, 401(k) plans, and a robust suite of personal well-being benefits to support your mental health. Depending on job classification, standard work hours, and years of service, KPMG provides Personal Time Off per fiscal year. Additionally, each year KPMG publishes a calendar of holidays to be observed during the year and provides eligible employees two breaks each year where employees will not be required to use Personal Time Off; one is at year end and the other is around the July 4th holiday. Additional details about our benefits can be found towards the bottom of our KPMG US Careers site at Benefits & How We Work. Follow this link to obtain salary ranges by city outside of CA: https://kpmg.com/us/en/how-we-work/pay-transparency.