Principal AI Platforms Solution Architect at PG&E Corporation

Job description

Requisition ID # 174929 Job Category: Engineering / Science Job Level: Manager/Principal Business Unit: Technology & Security Work Type: Hybrid Job Location: Oakland Department Summary The AI and Cloud Engineering Team is responsible for engineering, integrating, and operationalizing enterprise AI and Cloud platform capabilities that enable PG&E teams to securely adopt and scale AI solutions. The team builds and supports foundational capabilities such as Agentic AI services, MCP integrations, AI Gateway services, knowledge platforms, and AI Foundation components. Working within enterprise architecture, security, and governance direction, the team translates approved strategies and patterns into reusable, production-ready platform capabilities that accelerate high-impact business use cases while improving security, scalability, reliability, and operational consistency. Position Summary The AI Platforms Solution Architect (Principal) is responsible for leading the solution architecture and technical design of PG&E’s AI platform capabilities. This role translates enterprise architecture, security, and governance direction into scalable, production-ready designs and reusable implementation patterns for Agentic AI platforms, AI Foundation services, MCP integrations, AI Gateways, retrieval platforms, knowledge systems, and enterprise AI solutions. The position provides deep technical architecture leadership, partners with Enterprise Architecture and other technology stakeholders, and guides engineering teams in implementing secure, governed, reliable, and reusable AI platform capabilities. This position is hybrid, working from the employee’s remote office and our Oakland headquarters, based on business need. Key Responsibilities Enterprise AI Platform Architecture & Strategy • Work closely with AI Product Owners to define AI platform architecture, standards, reference architectures, and roadmaps. • Establish enterprise AI foundational architecture and shared services technical strategy. • Develop reusable architecture patterns for AI applications and services. • Align AI platform investments with business strategy and enterprise priorities. • Build prototypes for new Agentic patterns and explore open sourced solutions and frameworks Agentic AI & Autonomous Systems Architecture • Architect multi-agent systems, autonomous workflows, and intelligent orchestration capabilities. • Establish Agent-to-Agent (A2A) communication and Human-in-the-Loop (HITL) design standards. • Design reusable Agentic AI architecture patterns and implementation frameworks. • Guide enterprise adoption of Agentic AI solutions AI Gateway, MCP & Integration Architecture • Establish architecture standards for AI Gateways and enterprise AI traffic management. • Define MCP architecture and enterprise connectivity patterns. • Architect secure integrations between AI platforms and enterprise systems. • Develop reusable AI integration frameworks and reference solutions. AI Foundation Services, Knowledge Platforms & RAG • Architect enterprise RAG, semantic search, vector database, and knowledge graph platforms. • Define enterprise context management and retrieval architecture patterns. • Est ablish reference architectures for enterprise knowledge services. • Provide architectural leadership for AI-powered knowledge enablement solutions. • Build evals for RAG and KnowledgeGraph systems and use in production for drift detection AI Governance, Security & Responsible AI Architecture • Work closely with Cybersecurity teams to define AI security guardrails and platform architecture controls. • Establish AI governance and Responsible AI architecture standards. • Review solution architectures for security, privacy, compliance, and risk requirements. • Partner with Cybersecurity and Enterprise Architecture teams to govern enterprise AI platforms. • Design enterprise AI solutions that embed FinOps principles by default, optimizing model selection, infrastructure utilization, cost transparency, governance, and scalability to maximize business value while controlling operational spend. Technology Leadership & Enterprise Consulting • Lead enterprise AI architecture reviews and strategic design sessions. • Advise business and technology leaders on enabling AI use cases. • Evaluate emerging AI technologies and platform capabilities. • Mentor architects and engineering teams across the organization. Background Qualifications Minimum • Bachelor's degree in Computer Science, Engineering, Information Technology, Artificial Intelligence, or equivalent work experience in computer science, information technology, business administration, engineering, or other relevant field required • 10 years of experience in Solution Architecture, Platform Architecture, Cloud Architecture, Enterprise Architecture or relevant IT experience. • 7 years of architecture or software development experience • 3 years of experience architecting AI, ML, Generative AI, Agentic AI solutions or Cloud. • AWS Certified Solutions Architect - Associate or equivalent cloud certification • Experience architecting cloud-native platforms within AWS and Azure environments. • Experience designing enterprise integration architectures and API-based platforms. • Experience leading architecture and design review processes. • Strong executive communication and stakeholder management skills. • Experience working in an agile/scrum environment Desired • Experience with Agentic AI platforms, AI Gateways, MCP, Copilot Studio, Azure AI Foundry, AWS Bedrock, and enterprise AI services. • Experience designing RAG, semantic search, vector database, and knowledge graph solutions. • Experience defining enterprise AI operating models, governance frameworks, and Responsible AI controls. • Experience with developer platforms, DevSecOps, AI observability, and GenAIOps. • Experience in utility, critical infrastructure, or highly regulated environments. • Experience developing enterprise-wide AI platform roadmaps and transformation strategies. Compensation PG&E provides the salary range that the company in good faith believes it might pay for this position at the time of the job posting. This compensation range is specific to the locality of the job. The actual salary paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, and internal equity. Although we estimate the successful candidate hired into this role will be placed between the entry point and the middle of the range, the decision will be made on a case-by-case basis related to these factors. This job is also eligible to participate in PG&E’s discretionary incentive compensation programs. A reasonable salary range is: • Bay Area Minimum: $155,000 • Bay Area Midpoint: $210,000 • Bay Area Maximum: $265,000

Requirements

Must-haves

Requisition ID # 174929
Job Category: Engineering / Science
Job Level: Manager/Principal
Business Unit: Technology & Security
Work Type: Hybrid
Job Location: Oakland
Department Summary
Enterprise AI Platform Architecture & Strategy
Work closely with AI Product Owners to define AI platform architecture, standards, reference architectures, and roadmaps.
Establish enterprise AI foundational architecture and shared services technical strategy.
Develop reusable architecture patterns for AI applications and services.
Align AI platform investments with business strategy and enterprise priorities.
Build prototypes for new Agentic patterns and explore open sourced solutions and frameworks
Agentic AI & Autonomous Systems Architecture
Architect multi-agent systems, autonomous workflows, and intelligent orchestration capabilities.
Establish Agent-to-Agent (A2A) communication and Human-in-the-Loop (HITL) design standards.
Design reusable Agentic AI architecture patterns and implementation frameworks.
Guide enterprise adoption of Agentic AI solutions

Nice-to-haves

Experience with Agentic AI platforms, AI Gateways, MCP, Copilot Studio, Azure AI Foundry, AWS Bedrock, and enterprise AI services.
Experience designing RAG, semantic search, vector database, and knowledge graph solutions.
Experience defining enterprise AI operating models, governance frameworks, and Responsible AI controls.
Experience with developer platforms, DevSecOps, AI observability, and GenAIOps.
Experience in utility, critical infrastructure, or highly regulated environments.
Experience developing enterprise-wide AI platform roadmaps and transformation strategies.

Application prep

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