Note: The job is a remote job and is open to candidates in USA. The North American Electric Reliability Corporation (NERC) is a not-for-profit international regulatory authority responsible for reducing risks to the reliability and security of the North American bulk power system. The Senior Data & AI Engineer will design and implement governed, AI-ready enterprise data foundations and production AI capabilities, including semantic data layers, data pipelines, RAG solutions, predictive models, and AI governance controls. The role partners with business and technical teams to support secure, compliant data modernization and AI adoption.
Responsibilities
- 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
- 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
- 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
Skills
- 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
- Working knowledge of MLOps/LLMOps practices and tooling
- Experience with data governance, metadata management, and data quality tooling
- Effective communication and interpersonal skills, including active listening and clear articulation
- Demonstrated ability to work through ambiguity and drive results
- Experience in regulated industries, energy, utilities, or reliability organizations
- Familiarity with NIST AI RMF, or similar risk/governance frameworks
- Experience with platforms such as Microsoft Fabric, Databricks, or Snowflake, and with BI semantic models (e.g., Power BI)
- Experience with master data management (MDM) and API-based data sharing
Benefits
- The position may be based remotely.
- Reimbursement of travel expenses will be in accordance with the company’s travel and expense reimbursement policies.
- Provide a safe, inclusive, and collaborative work environment.
- Opportunities for growth and development.
- We value well-being, prioritizing collaboration, engagement, and connection among our team.
Company Overview