Sr Manager - Data & AI Governance
Listed on 2026-07-19
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IT/Tech
Data Security, AI Business & Operations, Cybersecurity, Information Security
Senior Manager – Data & AI Governance
The base salary range for this position is dependent upon experience and location, ranging from $163,360 to $204,200.
What We Offer:
- Competitive benefits and growth opportunities
- Generous performance-based bonuses
- 12% 401(k) match
- Comprehensive health, dental, and vision insurance
- Tuition reimbursement
- Professional development and clear career advancement pathways
Job Summary
The Senior Manager – Data & AI Governance role is responsible for establishing, operating, and continuously evolving Avangrid's enterprise Data and Artificial Intelligence governance framework. This role ensures that data, analytics, and AI solutions are designed, deployed, and operated in compliance with ethical standards, regulatory obligations, cybersecurity requirements, and enterprise policies while enabling scalable business value realization across regulated utility operations.
The role serves as the enterprise authority for Data & AI governance, translating regulatory, risk, and responsible AI principles into practical operating controls embedded across the full AI and data lifecycle. The Senior Manager partners closely with Data & AI teams, Enterprise Architecture, IT, Cybersecurity, Legal, Compliance, Risk, and business leaders to balance innovation, speed, and risk management in a highly regulated environment.
Key Responsibilities
Enterprise Data & AI Governance Framework
- Define, implement, and maintain enterprise-wide Data and AI governance frameworks, standards, and operating models covering data management, analytics, machine learning, and AI solutions.
- Establish governance structures, decision rights, escalation paths, and accountability models across the Data & AI lifecycle.
- Operationalize governance controls across architecture, development, deployment, monitoring, and retirement of AI systems.
Responsible AI, Risk, and Compliance
- Embed Responsible AI principles (fairness, transparency, explainability, accountability, privacy, and security) into AI design and delivery processes.
- Ensure compliance with applicable regulations and frameworks, including data privacy laws, emerging AI regulations (e.g., US NIST Guidelines, EU AI Act where applicable), cybersecurity standards, and internal policies.
- Lead AI and data risk assessments, model assurance reviews, and governance checkpoints for priority use cases.
- Act as a primary liaison to global, legal, compliance, enterprise risk, audit, and external regulators as required.
Lifecycle Oversight & Controls
- Define and enforce AI and data lifecycle management standards, including data sourcing, training data governance, model validation, monitoring, drift detection, explainability, and decommissioning.
- Ensure governance alignment across IT, cloud, OT, and analytics platforms, including vendor-managed and third-party AI solutions.
- Require and validate vendor documentation, transparency, and lifecycle commitments for AI-enabled products and services.
Operating Model & Enablement
- Partner with Data & AI teams to integrate governance seamlessly into IT delivery workflows (Agile, product, platform, and portfolio processes).
- Develop governance tooling, templates, playbooks, and artifacts to enable efficient adoption across teams.
- Provide training, guidance, and advisory support to business, IT, and Data & AI teams on governance requirements and best practices.
Monitoring, Reporting & Continuous Improvement
- Define KPIs and metrics for governance effectiveness, compliance posture, model risk, and adoption.
- Maintain governance documentation for audits, regulatory requests, and internal reporting.
- Monitor evolving regulatory, industry, and technology trends and continuously update standards and controls accordingly.
Required Qualifications
- Bachelor's in Computer Science, Data Science, Engineering, Information Systems, Law, Ethics, or a related field of study and a minimum of ten (10) years of relevant experience. An equivalent combination of education and experience may be considered.
- Relevant experience in data governance, AI governance, risk management, compliance, cybersecurity, or advanced analytics environments.
- Proven experience defining and operating governance…
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