The Agentic AI Engineer, Expert will lead the architecture and design of PG&E’s AI ecosystem, setting technical standards and reference patterns for agentic capabilities, enterprise AI platforms, and knowledge enablement solutions. This hybrid role is based in Oakland, California.
Role Summary
In this position, you will serve as the principal architecture authority for AI platforms and emerging AI technologies across PG&E. You will define architecture standards, reference patterns, and strategic technical direction for Agentic AI platforms, AI Foundation services, MCP integrations, AI Gateways, retrieval platforms, knowledge systems, and related enterprise AI solutions.
Responsibilities
- Collaborate with AI Product Owners to define AI platform architecture, standards, reference architectures, and roadmaps.
- Establish enterprise AI foundational architecture and shared services technical strategy.
- Create reusable architecture patterns for AI applications and services.
- Align AI platform investments with business strategy and enterprise priorities.
- Prototype new Agentic patterns and explore open sourced solutions and frameworks.
- Architect multi-agent systems, autonomous workflows, and intelligent orchestration capabilities.
- Define Agent-to-Agent (A2A) communication and Human-in-the-Loop (HITL) design standards.
- Develop reusable Agentic AI architecture patterns and implementation frameworks, including guidance for enterprise adoption.
- 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.
- 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 and provide architectural leadership for AI-powered knowledge enablement solutions.
- Build evals for RAG and KnowledgeGraph systems and use them in production for drift detection.
- Partner with Cybersecurity teams to define AI security guardrails and platform architecture controls.
- Establish AI governance and Responsible AI architecture standards, and review solution architectures for security, privacy, compliance, and risk requirements.
- Design enterprise AI solutions that embed FinOps principles by default, covering model selection, infrastructure utilization, cost transparency, governance, and scalability to maximize business value while controlling operational spend.
- Lead enterprise AI architecture reviews and strategic design sessions, and 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.
Required Qualifications
- 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.
Relevant Technologies
- AWS
- AWS Associate Certification
- MCP
- Copilot Studio
- Azure AI Foundry
- AWS Bedrock
- RAG
- Semantic search
- Vector database
- Knowledge graph
- FinOps
- API-based platforms
- DevSecOps
- GenAIOps
- AI observability
- Human-in-the-Loop (HITL)
- Agent-to-Agent (A2A)
Department Context
The AI and Cloud Engineering Team defines PG&E’s enterprise AI and Cloud platform technical roadmap and strategic architecture standards, including 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 and builds scalable, secure, governed AI foundational capabilities aligned with business and technology objectives.
Work Location and Schedule
- Location: Oakland, CA (hybrid)
- Hybrid setup: working from the employee’s remote office and PG&E’s Oakland headquarters based on business need.
- Assigned work location will be within the PG&E Service Territory.
Salary and Pay Range
- Full salary/pay range is provided; actual pay is based on multiple factors including internal equity, specific skills, education, licenses or certifications, experience, market value, and geographic location.
- Expected range around the minimum and the midpoint: USD 140,000 - USD 189,000.
- Bay Area minimum: USD 140,000; Bay Area maximum: USD 238,000.
- Final decision will be made case-by-case based on the factors above.
Benefits
- Eligible to participate in PG&E’s discretionary incentive compensation programs.
