Role Overview :

As an AI Lead Architect, you will serve as the technical visionary responsible for designing and scaling enterprise-grade AI platforms that bridge the gap between cutting-edge research and production-ready business solutions. You will lead the end-to-end architecture of Generative AI and LLM-based systems, working closely with cross-functional engineering teams, data scientists, and executive stakeholders to translate complex business requirements into robust, scalable cloud infrastructure. Your work will directly influence the organization's competitive edge by driving AI-led innovation, ensuring high-performance model deployment, and establishing the governance frameworks necessary to maintain security and compliance in an evolving AI landscape.

Key Responsibilities :

- Architect and deploy scalable AI platforms on Azure, ensuring seamless integration of LLMs and Generative AI models to drive measurable business outcomes.

- Design high-performance RAG pipelines and VectorDB implementations to optimize data retrieval and model accuracy for internal and external stakeholders.

- Establish comprehensive AI governance and security protocols, including identity management and data privacy, to ensure all AI initiatives meet enterprise compliance standards.

- Orchestrate complex microservices architectures using Kubernetes and CI/CD pipelines to streamline the deployment and lifecycle management of AI models.

- Collaborate with product and engineering leadership to define the long-term AI infrastructure roadmap, ensuring the technology stack remains agile and future-proof.

- Mentor senior engineering teams on best practices in AI architecture, fostering a culture of technical excellence and innovation across the organization.

Required Skillset :

- Demonstrated expertise in designing and managing large-scale cloud architectures, specifically leveraging Azure AI services to build production-grade AI ecosystems.

- Advanced proficiency in Python and modern software engineering practices, with a proven ability to integrate complex AI models into existing enterprise microservices.

- Deep technical understanding of LLM orchestration, RAG frameworks, and VectorDB management, with the ability to optimize these systems for latency and cost-efficiency.

- Strong leadership and communication skills, with the ability to articulate complex technical strategies to non-technical stakeholders and influence executive decision-making.

- Proven experience in implementing AI governance, security, and identity management frameworks within highly regulated environments.

- Exceptional problem-solving abilities and a track record of leading high-impact technical projects in a hybrid work environment based in Gurugram.

- A Master's degree in Computer Science, Engineering, or a related quantitative field is preferred, complemented by 14 - 20 years of progressive experience in software and AI architecture.