Agentic AI Technical Architect

Key Responsibilities - Lead the development and implementation of enterprise-wide ML and Gen AI/Agentic architectures, ensuring they are scalable, secure, and aligned with business goal. - Proven experience in developing solution across IFAO/IPO/ICO/ISCO Business Services - Lead the end-to-end development & deployment of Gen AI/Agentic initiatives, from ideation and PoC to deployment and scaling. - Identify opportunities for innovation and lead the creation of reusable Gen AI/Agentic assets, accelerators, and frameworks. - Oversee the seamless deployment of Gen AI/Agentic models across platforms, ensuring operational efficiency and compliance. - Develop and implement strategies for continuous integration and delivery of AI solutions, optimizing for performance and maintainability. - Establish and enforce governance policies, standards, and best practices for AI architecture and deployment, ensuring adherence to data privacy and ethical guidelines. - Mentor and lead a technical team and architects fostering a culture of innovation and excellence. - Collaborate with business stakeholders to translate requirements into scalable AI solutions and drive adoption. - Act as the central point of coordination among business lines, technology teams, and clients to ensure consistent delivery outcomes. - Identify opportunities for innovation within the AI domain, focusing on the development of reusable assets and tools. Qualifications And Skills - Master’s degree in Computer Science, Engineering, Data Science, or a related field. Ph.D. is a plus. - 18+ years of experience in enterprise architecture, solution delivery with a strong focus on ML and Gen AI technologies. - Proven experience in solutioning AI-powered solutions at scale, preferably in client-facing environments. - Deep understanding of Gen AI/Agentic frameworks including frameworks like Lang chain and other LLM based services including OpenAI, cloud platforms (AWS, Azure, GCP), and MLOps practices. - Strong understanding of CI/CD, containerization (Docker, Kubernetes), and microservices architecture. Familiarity with Agile and DevOps methodologies. - Excellent communication, stakeholder engagement, and team leadership skill. - Exposure to industry-specific Gen AI/Agentic use cases (e.g., SAP, Salesforce, Finance, Supply Chain etc.,) - Minimum 8 years of extensive experience in solutioning end to end product/assets by leveraging multiple technology components including AI/ML and Generative AI. - Strong problem-solving, strategic thinking and analytical skills, with the ability to synthesize complex information and make data-driven decisions. - Proven experience in leading large-scale AI solution deployments and managing cross-functional teams.