Senior Data & AI Engineer

Our Company The North American Electric Reliability Corporation (NERC) is a not-for-profit international regulatory authority whose mission is to assure the effective and efficient reduction of risks to the reliability and security of the grid. NERC develops and enforces Reliability Standards; annually assesses seasonal and long term reliability; monitors the bulk power system through system awareness; and educates, trains, and certifies industry personnel. NERC s area of responsibility spans the continental United States, Canada, and the northern portion of Baja California, Mexico. NERC is the Electric Reliability Organization (ERO) for North America, subject to oversight by the Federal Energy Regulatory Commission (FERC) and provincial authorities in Canada. NERC s jurisdiction includes users, owners, and operators of the bulk power system, which serves nearly 400 million people. Our Mission The vision for the ERO Enterprise, which is comprised of NERC and the six Regional Entities, is a highly reliable and secure North American bulk power system. Our mission is to assure the effective and efficient reduction of risks to the reliability and security of the grid. Your Impact The Senior Data & AI Engineer designs and builds the data architecture that makes NERC s data discoverable, trusted, and consumable by analytics and AI-and delivers production AI capabilities on top of it. This is a hands-on engineering role at the center of NERC s data modernization and AI adoption: the architecture work exists to make AI and advanced analytics possible, and the AI work proves the architecture. This role turns strategy into working systems. Partnering with both business and technical units, this engineer will implement governed, AI-ready data foundations and productionize AI solutions that advance NERC s reliability mission-responsibly, securely, and in compliance with regulatory obligations. Your Role This role creates and implements NERC s enterprise data architecture standards and delivers AI capabilities into production. This includes building the semantic and governed data layers that support analytics across the ERO Enterprise, implementing data quality, lineage, and classification controls appropriate to CEII and confidential information, and engineering AI solutions-from retrieval-augmented generation (RAG) pipelines to predictive models-on top of that foundation. This position reports to the Director, Data Architecture & AI. The Director sets architecture direction: AI solution designs are set in partnership with the Principal AI Architect and business units. Responsibilities Data Architecture & Engineering (approximately 60%) • Design and implement enterprise data models, modeling standards, and the semantic layer that powers certified analytics and reporting. • Working with business units, implement the data catalog, lineage, and data classification framework (including CEII and confidential information handling), with automated data quality testing built into pipelines. • Build and evolve data pipelines and integration patterns on NERC s cloud data platform in partnership with Data Engineers and DBAs. • Contribute to the API and data-sharing patterns enabling secure, governed exchange with Regional Entities, E-ISAC, FERC, and internal tools. AI Engineering (approximately 40%) • Build and productize AI solutions designed with the Principal AI Architect, including generative AI, RAG pipelines, LLM integrations, predictive analytics and classification algorithms. • Implement and operate MLOps/LLMOps practices: deployment environments, evaluation frameworks, monitoring, and cost management. • Stand up and maintain AI platform components such as vector stores, orchestration frameworks, and model serving infrastructure. • Prototype high-value AI use cases against governed data to validate architecture decisions and accelerate adoption. • Implement AI governance guardrails in code and configuration: data eligibility, usage constraints, and model documentation aligned with NIST AI RMF and NERC AI governance. Shared • Ensure solutions comply with regulatory frameworks, internal controls, and NERC requirements. • Communicate technical concepts clearly to technical and non-technical audiences, document architectures, standards, and operational runbooks. • Evaluate tools and vendors; make build-vs-buy recommendations. Qualifications The successful candidate will have at a minimum: • 7+ years of firsthand experience in data engineering, data architecture, or ML/AI engineering. • Expert-level SQL and Python. • Experience with cloud data platforms (Azure, AWS, or GCP) and modern warehouse/Lakehouse architectures; experience with transformation frameworks such as Azure Data Factory or equivalent. Preference is for Microsoft Fabric Dataflow. • Practical generative AI experience: RAG, embeddings, vector stores, prompt, and model evaluation-with at least one AI capability shipped to production....