Senior Manager - AI Process Design

Iberdrola•Orange, CT

About The Position

The Senior Manager - AI Process Design role is responsible for leading the process design development, optimization, operationalize and scaling of the AI-driven business processes to drive measurable outcomes and reduce AI risk across the utility enterprise; act as the primary translator between business stakeholders (operations, OT, customer teams), Data/AI, and Enterprise Architecture to prioritize capability-led AI initiatives, ensure AI ready data and governance, and enable adoption at scale.

Requirements

Bachelor’s degree in Computer Science, Data Science or a related field or a related field and a minimum of ten (10) years of relevant experience. An equivalent combination of education and experience may be considered.
Relevant experience in power & utilities or adjacent heavy asset industries with exposure to OT/SCADA/ADMS environments and asset management programs.
Proven track record delivering cross functional digital/AI initiatives or productized data products in enterprise environments.
Business & domain acumen: Deep understanding of utility business capabilities (asset management, grid operations, customer experience, DERs) and operational constraints (safety, regulatory context).
Stakeholder facilitation & change leadership: Proven ability to run cross functional workshops, co-design processes with OT/operations, HR and legal, and drive adoption through human centric change plans.
Governance, ethics & compliance: Ability to operationalize XAI, fairness audits, privacy by design and vendor contractual requirements for transparency and lifecycle accountability.
Measurement & value realization skills: Capability to define role appropriate metrics across business outcomes, strategic and operational levers, establish baselines and perform ROI/impact tracking.
Practical program execution: Experience supporting pilot to production transitions, quality gates, testing regimes and production monitoring for automation/AI deployments.
Ability to translate among the languages used by executive, business, IT, and quant stakeholders.

Nice To Haves

Master’s degree in Computer Science, Data Science or a related field or a related field

Responsibilities

Map technology and AI opportunities to business capabilities; prioritize high‑impact capabilities (e.g., Optimize Asset Life Cycle, Manage Customer Experience) for digital/AI enablement and value realization.
Translate operational problems into measurable AI use cases (predictive maintenance, outage prediction, demand forecasting, conversational self‑service), define success metrics and ROI, and validate vendor performance claims and benchmarks.
Lead cross‑functional workshops and co‑design sessions with business, OT, legal/compliance, HR and IT to secure alignment, co‑create implementation roadmaps and manage adoption risks.
Coordinate with data scientists, domain stewards and D&A architects to ensure AI‑ready data, observability, lineage and model orchestration across IT/OT/ET systems; validate model robustness and integration with SCADA/ADMS/GIS where relevant.
Embed AI governance and risk controls into project lifecycles (explainability, fairness, privacy, security), require vendor documentation and lifecycle support, and support enterprise AI governance boards.
Define and track KPIs tied to business outcomes (operational efficiency, reliability, customer satisfaction, cost‑to‑serve), operational diagnostics (cycle time, SLA adherence), AI agent effectiveness (performance, reliability) and adoption metrics; report progress to executives.
Evaluate vendor pricing, licensing, SLAs and exit terms; collaborate with platform providers and procurement to ensure transparency, data returns and lifecycle support.
Support pilot‑to‑production transitions, ensure testing and production monitoring, and coordinate ongoing model validation, drift detection and lifecycle maintenance.