Senior AI Architect Agentic AI Location: Noida, Hyderabad, Chennai, Bengaluru, Pune Experience: 12-16 Years AI Experience: Minimum 5 years in Generative AI / Agentic AI Employment Type: Full Time Job Summary We are looking for a Senior AI Architect to lead enterprise AI strategy and architecture for Generative AI and Agentic AI solutions. The candidate will define AI architecture standards, select suitable cloud and AI platforms, guide technical teams, and ensure AI solutions are secure, scalable, cost-effective and ready for production. The role requires strong enterprise architecture experience, hands-on knowledge of AI technologies, multi-cloud expertise, and the ability to lead senior customer discussions and complex AI programs. Key Responsibilities Lead AI architecture strategy from business requirement gathering through production deployment and scaling. Work with senior stakeholders to define AI vision, target architecture, technology roadmaps and investment priorities. Design enterprise architecture standards for Generative AI, Agentic AI, LLMs, RAG, multi-agent systems and AI applications. Make architecture decisions across GCP, Microsoft Azure, AWS, OpenAI and Anthropic Claude based on business needs, security, performance and cost. Design agent architectures, including orchestration, planning, tools, domain agents, memory, workflows and human approval processes. Define AI data and knowledge architecture covering data ingestion, search, vector databases, retrieval, access controls and evaluation. Establish model selection and routing strategies, fallback mechanisms, context management, caching and AI cost optimization. Define AI security, Responsible AI, privacy, governance, compliance, audit and risk management standards. Establish AI operations practices covering monitoring, tracing, logging, model evaluation, cost tracking and incident management. Create architecture roadmaps for MVPs, production deployment, scaling and long-term operations. Establish architecture reviews, technical standards, reference designs and governance processes. Review and approve solution architecture, integration designs, security designs and deployment plans. Evaluate complex customer requirements and decide which capabilities should be built, purchased, standardized or reused. Develop reusable architecture patterns and work with Product and Platform Engineering teams to improve AI platforms. Lead architecture escalations and resolve complex production and cross-platform technical issues. Support proposals, RFPs, solution estimations, technical assessments, POCs and strategic customer engagements. Mentor AI Architects, Senior Forward Deployment Engineers, FDEs and engineering leads. Participate in architecture review boards, customer governance meetings and strategic technology discussions. Required Technical Skills Strong software engineering and enterprise solution architecture experience. Extensive hands-on experience with Generative AI, LLMs, RAG, Agentic AI and multi-agent architectures . Experience designing enterprise AI applications and reusable agent frameworks. Knowledge of multiple AI and cloud platforms, including Azure, AWS, GCP, OpenAI or Anthropic Claude. Strong understanding of application, data, integration, cloud, security, networking and operations architecture. Experience with AI security, Responsible AI, privacy, compliance, governance and model risk management. Knowledge of AI observability, evaluation, AgentOps and production reliability. Experience with cloud-native architecture, Kubernetes, serverless platforms, CI/CD and Infrastructure as Code. Strong customer-facing communication and technical leadership skills. Ability to make architecture decisions and explain technical trade-offs to business and technical stakeholders. Preferred Skills Experience with two or more platforms among GCP, Azure, AWS, OpenAI and Anthropic Claude. Enterprise AI reference architectures, architecture governance and technology standards. MCP, A2A and enterprise agent interoperability. OpenTelemetry and AI monitoring/evaluation tools such as Azure Monitor, Application Insights, CloudWatch, LangSmith or Arize. Enterprise security architecture, Zero Trust, private connectivity and data residency. AI FinOps, model selection, vendor evaluation and total cost of ownership. Experience leading POCs, pilots, MVPs, production rollouts, RFPs and enterprise transformation programs. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, Information Technology or a related field. 1216 years of overall software engineering, cloud engineering, enterprise architecture or equivalent technical experience. Minimum 5 years of practical Generative AI / Agentic AI experience, including enterprise production delivery. Proven experience owning architecture for complex enterprise technology or AI programs. Experience leading senior customer engagements, architecture governance and cross-functional technical teams. Key Attributes Strong strategic thinking and enterprise architecture skills. Ability to balance long-term architecture with practical production requirements. Strong leadership and communication skills. Ability to resolve technical disagreements and drive decisions. Strong mentoring and stakeholder management capabilities. Interest in emerging AI technologies and their practical enterprise applications.