12087 AI Business Product Specialist

PSEG•Newark, NJ

18h•Hybrid

About The Position

The AI Business Product Manager (Technical) identifies, shapes, prioritizes, prototypes, and drives AI-enabled business capabilities that deliver measurable enterprise value. The role combines business architecture, product management, AI technology evaluation, and hands-on technical experimentation to connect business operations, enterprise architecture, and AI delivery teams. It translates enterprise priorities and operational challenges into scalable AI opportunities aligned with organizational strategy, governance standards, and technology capabilities. The position partners with business units, Enterprise Architecture, IT delivery, cybersecurity, data governance, and the AI Center of Excellence to support responsible, value-driven AI adoption. It is technically hands-on, supporting rapid experimentation, proof-of-concept development, platform evaluation, and technical feasibility assessments across emerging AI technologies and enterprise platforms. The position is hybrid, with at least three onsite days per week. PSEG does not offer visa sponsorship for this position. During emergency restoration efforts, employees may be required to perform functions outside their routine duties and work a schedule different from normal operations.

Requirements

Bachelor’s degree in Business, Information Systems, Engineering, Computer Science, or a related field.
8+ years of experience in product management, business architecture, digital transformation, technology delivery, or AI-related initiatives.
Experience with Artificial Intelligence (AI), Generative AI, Machine Learning, analytics, intelligent automation, or cloud AI platforms.
Experience working cross-functionally with business and technology organizations.
Strong understanding of enterprise business processes, operational transformation, and technology enablement.
Experience developing business cases, roadmaps, prioritization frameworks, and value realization metrics.
Hands-on experience prototyping AI solutions, AI workflows, copilots, automation solutions, or low-code/no-code AI applications.
Exposure to prompt engineering, AI agents, Retrieval-Augmented Generation (RAG), APIs, workflow orchestration, or AI integration concepts.
Strong communication, facilitation, stakeholder management, and executive presentation skills.
Ability to participate in technical discussions related to AI architecture, integrations, cloud platforms, APIs, and enterprise solution design.
Compliance with the Department of Energy’s regulation 10 CFR 810 is required.

Nice To Haves

MBA.
Familiarity with Azure OpenAI, AWS Bedrock, ServiceNow AI, SAP AI, Salesforce AI, or similar enterprise AI platforms.
Familiarity with Python, scripting, REST APIs, or cloud-native AI development concepts.
Experience within regulated industries such as utilities, energy, financial services, or healthcare.
Experience with Agile product management and iterative delivery methodologies.
Understanding of AI governance, cybersecurity, risk management, and regulatory considerations.

Responsibilities

Partner with business leaders to identify and evaluate AI opportunities across operational, customer, and corporate domains.
Analyze business capabilities, workflows, pain points, and value streams to identify AI enablement opportunities.
Translate business challenges into well-defined AI use cases and product opportunities.
Support development and execution of the enterprise AI roadmap and portfolio strategy.
Conduct discovery workshops and facilitate AI ideation sessions with business stakeholders.
Develop lightweight prototypes and proof-of-concept solutions to validate AI use cases, business value, and technical feasibility.
Experiment with AI agents, copilots, Generative AI workflows, automation capabilities, and emerging AI technologies.
Evaluate and compare enterprise AI technologies and platforms, including Azure OpenAI, AWS Bedrock, SAP, ServiceNow, Salesforce, and other AI-enabled enterprise platforms.
Participate in architectural discussions about AI solution design, integration, scalability, security, and operational readiness.
Assess technical approaches for business value, feasibility, governance, scalability, and operational considerations.
Collaborate with AI engineering and platform teams to transition validated prototypes into scalable enterprise solutions.
Evaluate business processes and target-state operating models to identify opportunities for AI-driven transformation.
Assess alignment between business objectives, enterprise architecture standards, and AI technology capabilities.
Collaborate with Enterprise Architecture and platform teams to align AI initiatives with enterprise technology strategy.
Identify opportunities to use native AI capabilities in enterprise platforms and third-party applications.
Manage AI use cases from ideation through implementation and value realization.
Develop business cases, value hypotheses, success metrics, and KPI frameworks for AI initiatives.
Support AI intake, prioritization, and portfolio management processes.
Evaluate AI opportunities based on business value, technical feasibility, risk, operational impact, and strategic alignment.
Maintain the AI initiative backlog and prioritization artifacts.
Track adoption, business outcomes, operational improvements, and ROI metrics.
Partner with AI engineering, platform, and IT delivery teams to define solution requirements and implementation approaches.
Collaborate with cybersecurity, legal, compliance, and governance stakeholders throughout AI intake and approval workflows.
Coordinate with enterprise platform owners to evaluate native AI capabilities and AI feature enablement opportunities.
Support stakeholder alignment, business readiness, and organizational change activities during AI implementation.
Ensure AI initiatives align with enterprise AI governance, cybersecurity, compliance, privacy, and responsible AI standards.