Build and implement Generative AI and Agentic AI capabilities that enhance internal business processes and customer experiences. Develop and govern AI agents and copilots, including experience with Microsoft Copilot Studio and enterprise agent development patterns. Design and develop Agentic AI solutions leveraging Model Context Protocol (MCP), Google Agent Development Kit (ADK), Lang. Graph / Lang. Chain, and Agent Engine on Google Cloud Platform (GCP). Ensure AI and Gen. AI solutions are architecturally aligned with enterprise technology strategy, and meet scalability, security, resiliency, and compliance requirements. Drive enterprise adoption of Gen. AI and Agentic AI frameworks, establishing reusable patterns, reference architectures, and best practices. Lead and execute proofs of concept (POCs) to evaluate emerging AI technologies, tools, and frameworks, and transition successful POCs into production-ready solutions. Collaborate closely with Enterprise Architects, Platform Engineering, Security, and Data teams to ensure AI solutions align with approved reference architectures and governance standards. Stay current with industry trends in Generative AI, agent frameworks, and AI platforms, proactively recommending innovative and practical solutions for enterprise use cases. Familiarity with security and privacy controls for AI/ ML workloads to protect against exploitation of data or models during training, validation and inference. Managing security policy and drift detection at scale across the enterprise. Cloud Security (AWS & GCP)Architect and implement secure cloud solutions leveraging native services and third-party tools. Define and enforce cloud security posture management (CSPM), identity and access management (IAM), secrets, key management and encryption strategies. Collaborate with DevOps and cloud engineering teams to embed security into foundational networking components, CI/ CD pipelines and infrastructure-as-code. Datacenter & Hybrid Security. Ensure secure integration between cloud platforms and on-prem datacenters, including network segmentation, VP - Ns, and secure data flows. Oversee security controls for legacy systems and their modernization paths. Gen. AI Security Enablement. Define security and governance frameworks for Gen. AI platforms and use cases. Ensure responsible AI practices including data privacy, model integrity, explainability and ethical AI usage. Collaborate with AI/ ML teams to secure model training, inference, and deployment pipelines. Governance & Collaboration. Serve as a key member of the Enterprise Technology & Solution Governance. Partner with business, IT, and risk stakeholders to align security architecture with enterprise goals. Provide technical guidance and mentorship to junior engineers and architects on AI development practices. Required Qualifications:Experience: 10-12 years in Engineering / Architecture disciplines, with at least 2 years in Gen. AI and Agentic AI development. Project Delivery: Must have at least one Gen. AI or Agentic AI project end-to-end delivery experience. Technical Expertise:Strong proficiency in Google ADK, Lang. Graph/ Langchain, Agent Engine, RAG, and Vertex AI. Hands-on experience with GCP services: Cloud Run, ECS, Vertex AI Search Engine, IAM, and networking. Experience developing Ia. C and application pipelines using modern automation and DevOps tooling (e.g., Terraform, GitHub Actions)Solid understanding of Gen. AI patterns, LLM fine-tuning, and prompt engineering. Programming Skills: Python, Java, or similar languages for AI development. Cloud Certifications: GCP Professional Machine Learning Engineer or GCP Professional Cloud Architect preferred. Education: Bachelor’s or Master’s degree in Computer Science, AI/ ML, or related field. Soft Skills: Strong problem-solving, communication, and collaboration skills. Key Competencies:Strategic and analytical thinking. Successfully integrated AI agents into business or technical workflows for automation and enhanced decision-making. Improved operational efficiency and customer experience through AI-driven innovation. Established reusable AI patterns and best practices for enterprise adoption. Strong communication and stakeholder engagement. Proactive and solution-oriented mindset. Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position. Compensation.