12127 Sr Mgr AI Engineering & Platform Delivery

PSEG•Newark, NJ

4d•Hybrid

About The Position

The IT Leader focuses on the delivery and refinement of digital products. This role involves strategic product planning, feature execution, and managing technology systems for business operations. Responsibilities extend to coordinating with IT groups for troubleshooting and system enhancements, leading system installations, upgrades, and maintaining system operations. The leader is also responsible for guiding the technology teams, fostering innovation, and driving automation to enhance support for end users. This position emphasizes a strong commitment to developing team capabilities and promoting an agile work environment to optimize business outcomes. The AI Manager – Engineering & Platform Delivery is responsible for leading the engineering, product execution, platform enablement, and delivery functions of the Enterprise AI Center of Excellence (AI CoE). The AI Manager provides day-to-day leadership for AI delivery activities, including business discovery, technical evaluation, proof-of-concept development, engineering, platform enablement, and production deployment. The role ensures close collaboration between business stakeholders and engineering teams while maintaining alignment with enterprise architecture, cybersecurity, and Responsible AI standards. This position is expected to remain technically engaged, providing architectural guidance, mentoring engineers, participating in technology evaluations, and supporting complex solution design while building a high-performing enterprise AI delivery organization.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Information Systems, Engineering, or related field
10+ years of experience in software engineering, enterprise application development, AI/ML, cloud engineering, or solution delivery
5+ years of technical leadership or engineering management experience
Experience leading multidisciplinary teams including product, engineering, or solution delivery functions
Hands-on experience developing cloud-native, API-driven, and AI-enabled applications
Strong understanding of enterprise architecture, cloud platforms, distributed systems, APIs, DevOps, and modern software engineering practices
Experience delivering enterprise technology solutions from concept through production
Strong communication, leadership, stakeholder management, and coaching skills

Nice To Haves

Experience with Azure OpenAI, Azure AI Services, AWS Bedrock, Microsoft Copilot technologies, ServiceNow AI, Salesforce AI, SAP AI, or comparable enterprise AI platforms
Experience building AI agents, copilots, Retrieval-Augmented Generation (RAG) solutions, intelligent automation, or Generative AI applications
Experience with Python, .NET, JavaScript/TypeScript, REST APIs, cloud-native application development, and full-stack engineering
Familiarity with containerization, Kubernetes, DevOps, CI/CD, GitHub, Azure DevOps, and MLOps practices
Experience within regulated industries such as utilities, energy, financial services, or healthcare
Understanding of cybersecurity, Responsible AI principles, and enterprise technology governance

Responsibilities

Lead end-to-end delivery of enterprise AI initiatives from approved use case through production.
Manage delivery priorities, engineering capacity, quality, and commitments.
Establish effective AI engineering and Agile delivery practices and continuously improve team performance.
Lead and coach AI Business Product Managers supporting business domains.
Ensure AI opportunities are defined, prioritized, technically evaluated, and validated through rapid prototyping.
Guide build, buy, and configure decisions and transition validated opportunities into engineering delivery.
Lead delivery of AI applications, agents, copilots, workflows, APIs, and reusable enterprise AI services.
Evaluate and enable appropriate enterprise AI platforms and emerging technologies.
Ensure solutions are secure, scalable, reusable, maintainable, and production-ready.
Provide technical leadership for AI architecture, integrations, engineering standards, and solution design.
Oversee AI platform engineering, MLOps/LLMOps, deployment automation, monitoring, observability, and lifecycle management.
Partner with Enterprise Architecture, Cloud, Infrastructure, and Platform teams to ensure reliable and cost-effective solutions.
Lead implementation of AI engineering platforms, development environments, deployment automation, and operational tooling.
Oversee emerging MLOps capabilities including deployment automation, monitoring, observability, lifecycle management, and operational support.
Partner with infrastructure, cloud, and platform teams to optimize AI platform performance, scalability, reliability, and cost.
Support production readiness, operational support, and continuous improvement of AI solutions
Partner with business, IT, Enterprise Architecture, Cybersecurity, and platform teams to execute AI delivery priorities.
Coordinate with the Responsible AI & Governance team to meet governance, security, privacy, and compliance requirements.
Foster collaboration across business and technology teams to accelerate responsible enterprise AI adoption.