Lead Qualcomm's GenAI transformation for embedded and software engineering, building reusable AI agents, agentic workflows, and developer productivity tools that scale across teams. Partner with platform and engineering teams to establish secure AI practices, governance models, and metrics while serving as a technical thought leader who shapes the organization's transition to AI-native engineering workflows.… Requires Principal-level technical leadership with deep expertise in generative AI, LLM-based systems, and hands-on experience deploying GenAI solutions in complex engineering environments. Collaborate on code generation, code review, test automation, and release readiness use cases while driving measurable productivity and quality improvements.
ai-governance jobs in San Diego
Senior Infrastructure & Security Engineer responsible for administering and securing Microsoft 365, Azure, and Entra ID environments, including identity controls, conditional access, and MFA enforcement. The role encompasses data protection through DLP policies and Microsoft Purview, endpoint security via CrowdStrike, Windows Server and Active Directory infrastructure, virtualization (VMware, Azure), backup/disaster recovery, and establishing governance standards for AI platforms.… Requires 7+ years of progressive IT infrastructure and security experience with strong expertise in Microsoft cloud services, identity management, and enterprise networking.
Zensar is seeking an experienced AI Architect to design, develop, and deploy enterprise-scale AI and Generative AI solutions. The role requires deep expertise in Large Language Models (Claude, Gemini, OpenAI), multi-cloud platforms (Azure, AWS), and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years designing AI/ML solutions.… Responsibilities include defining AI strategy and architecture standards, designing end-to-end GenAI systems (RAG, agentic AI, multi-agent systems), architecting secure infrastructure across Azure and AWS, establishing governance and responsible AI frameworks, and leading adoption programs. The ideal candidate will mentor teams, evaluate emerging technologies, and translate business requirements into scalable, production-grade AI systems.