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Principal AI Platforms Solution Architect

Remote / Online - Candidates ideally in
Oakland, Alameda County, California, 94616, USA
Listing for: Pacific Gas and Electric Company
Remote/Work from Home position
Listed on 2026-10-05
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 155000 - 265000 USD Yearly USD 155000.00 265000.00 YEAR
Job Description & How to Apply Below

Job Category:
Engineering / Science

Job Level: Manager/Principal

Business Unit:
Technology & Security

Work Type:
Hybrid

Job Location:

Oakland

Department Summary

AI and Cloud Engineering Team is responsible for defining PG&E's enterprise AI and Cloud platform technical roadmap and strategic architecture standards, Agentic AI patterns, MCP integrations, AI Gateway services, knowledge platforms, and AI Foundation capabilities. The team provides design and engineering leadership for enterprise AI adoption. Builds AI foundational capabilities to support PG&E high impact use cases. Ensure AI solutions are scalable, secure, governed, and aligned with business and technology objectives.

Position Summary

The AI Platforms Solution Architect (Principal) is responsible for leading the architecture and design of PG&E's AI ecosystem. This role defines architecture standards, reference patterns, and strategic technical direction for Agentic AI platforms, AI Foundation services, MCP integrations, AI Gateways, retrieval platforms, knowledge systems, and enterprise AI solutions. The position serves as the principal architecture authority for AI platforms and emerging AI technologies across PG&E.

This position is hybrid, working from the employee’s remote office and our Oakland headquarters, based on business need. The assigned work location will be within the PG&E Service Territory.

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.
  • Establish reference architectures for enterprise knowledge services.
  • Provide architectural leadership for AI-powered knowledge enablement solutions.
  • Build evals for RAG and Knowledge Graph 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 Fin Ops 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…
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