Agentic AI Engineer, Expert

Pacific Gas and Electric Company; Oakland (CA); Hybrid; USD 140,000 - 238,000; Full time

Job summary

Pacific Gas and Electric Company is seeking an Expert Agentic AI Engineer to lead architecture for PG&E's AI ecosystem. You will define standards, reference patterns, and strategic direction for AI foundation services, MCP integrations, AI Gateways, and knowledge platforms.

This role serves as the principal architecture authority across AI technologies at PG&E. The position is hybrid, with work from Oakland headquarters and remote options based on business needs; Bay Area compensation ranges are

Qualifications

• Bachelor's degree or equivalent in a technical field.
• 5+ years in Cloud/Enterprise Architecture roles.
• AWS Associate Certification or equivalent cloud cert.
• Experience with Agentic AI platforms and enterprise AI services.

Responsibilities

• Define AI platform architecture standards and roadmaps.
• Architect multi-agent and autonomous workflow systems.
• Establish AI gateways, MCP connectivity and integrations.
• Lead governance, security, and responsible AI controls.
• Mentor engineers and drive strategic AI platform initiatives.
• Partner with product owners to align architecture with business goals.

Skills

Cloud Architecture

Solution Architecture

Platform Architecture

Enterprise Architecture

Agentic AI

Generative AI

AWS/Azure

DevSecOps AI

API-based platforms

Education

Bachelor's degree or equivalent

AWS Associate Certification

Tools

Copilot Studio

Azure AI Foundry

AWS Bedrock

MCP

Job description

Requisition ID# 174444

Job Category: Engineering / Science

Job Level: Individual Contributor

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 Agentic AI Engineer, Expertis 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.

PG&Eis providingthe full salary/pay range for this position. The actual amount paid to an individual will be based on multiple factors, including, but not limited to, internal equity,specific skills, education, licenses or certifications, experience, market value, and geographic location.The range toreasonably expectwill be around the minimum and themidpoint$140,000 - $189,000. Thefinal decision will be made on a case-by-case basis related to thefactorsabove.This job is also eligible toparticipatein PG&E’s discretionary incentive compensation programs.

Bay Area Minimum: $ 140,000

Bay Area Maximum: $ 238,000

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.

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 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.

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
• 5 years of experience in Cloud Architecture, Solution Architecture, Platform Architecture, or Enterprise Architecture
• AWS Associate Certification, or equivalent Cloud platform certification

Desired:

• Experience with Agentic AI platforms, AI Gateways, MCP, Copilot Studio, Azure AI Foundry, AWS Bedrock, and enterprise AI services
• 5+ years of software development experience
• 3+ years of experience architecting AI, ML, Generative AI, or Agentic AI solutions
• Experience architecting cloud-native platforms within AWS and Azure environments
• Experience designing enterprise integration architectures and API-based platformsExperience leading architecture and design review processes
• Strong executive communication and stakeholder management skills
• 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