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Jobs in Lake Forest, CA

Project Manager AI-agentic development and architecture experience Onsite at Lake Forest,CA

E-Solutions INC

  • Lake Forest, CA
  • 1 day ago

    Highlights

    Overall: This is a Scrum Master / Project Manager role with strong Agile delivery responsibilities plus emerging AI-agentic development governance and architecture experience. Supervise AI agents across microservices, legacy modernization, and large codebases/monorepos .

    Numbers & Facts

    LocationLake Forest, CA

    Description

    Overall: This is a Scrum Master / Project Manager role with strong Agile delivery responsibilities plus emerging AI-agentic development governance and architecture experience.
    Key Skills
    • Project Management & Scrum Master
    • Agile/Scrum, SAFe, Kanban
    • Stakeholder & Client Management
    • Requirement Gathering & User Stories
    • Jira & Confluence
    • SDLC, Governance & Compliance
    • Risk, Dependency & Release Management
    • UAT & Cross-functional Team Coordination
    Key Responsibilities
    • Lead Scrum ceremonies and drive Agile best practices.
    • Manage end-to-end project delivery-scope, timelines, risks, dependencies.
    • Gather requirements and convert them into user stories with acceptance criteria.
    • Manage product backlog, sprint progress, velocity, and delivery.
    • Remove impediments and drive continuous improvement.
    • Coordinate Dev, QA, Product, and business stakeholders.
    • Manage UAT, releases, reporting, and senior leadership communication.
    • Handle multiple projects/teams while ensuring SDLC and compliance standards.
    BizChat / AI-Agentic Skills
    • Experience with agentic IDEs and AI-assisted SDLC.
    • Define architecture and agent-executable tasks.
    • Establish AI guardrails, permissions, reviews, and governance.
    • Supervise AI agents across microservices, legacy modernization, and large codebases/monorepos.
    • Integrate agentic workflows with CI/CD pipelines.
    • Ensure security, compliance, auditability, and traceability of AI-generated code.
    • Establish quality/review practices for AI-assisted development.
    • Mentor teams on AI autonomy vs. correctness and maintainability.
    • Assess impact on SDLC, CI/CD, security posture, and technical debt.

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