Role Overview :

As a GenAI Architect based in Hyderabad, you will serve as the technical visionary responsible for designing and deploying advanced artificial intelligence solutions that drive business value. You will bridge the gap between high-level business requirements and technical execution, working closely with cross-functional engineering teams, data scientists, and senior stakeholders.

Your day-to-day will involve architecting robust LLM-based systems, overseeing the integration of generative models into existing enterprise workflows, and ensuring that AI initiatives are scalable, secure, and aligned with long-term organizational goals. This role is pivotal in shaping the company's AI roadmap and delivering high-impact solutions that transform how our clients interact with data.

Key Responsibilities :

- Design and implement end-to-end Generative AI architectures, ensuring high performance and reliability for enterprise-grade applications.

- Lead the development of RAG (Retrieval-Augmented Generation) pipelines to enhance the accuracy and relevance of AI-generated outputs for specific business domains.

- Architect scalable MLOps frameworks to streamline the deployment, monitoring, and lifecycle management of large-scale machine learning models.

- Collaborate with stakeholders to translate complex business problems into actionable AI strategies, ensuring technical solutions directly contribute to operational efficiency.

- Evaluate and integrate cutting-edge LLM frameworks and tools, such as LangChain, to build sophisticated, context-aware AI agents.

- Mentor engineering teams on best practices in AI development, fostering a culture of technical excellence and continuous innovation.

Required Skillset :

- Demonstrated expertise in designing and deploying Generative AI and LLM-based solutions within complex, high-traffic enterprise environments.

- Strong proficiency in building RAG architectures and leveraging frameworks like LangChain to optimize model performance and data retrieval.

- Deep technical knowledge of MLOps principles, including model versioning, automated testing, and deployment pipelines, specifically within the Azure ecosystem.

- Proven ability to communicate complex technical concepts to non-technical stakeholders, ensuring alignment between engineering efforts and business objectives.

- Exceptional problem-solving skills with a track record of delivering AI initiatives that scale effectively across global platforms.

- A minimum of 10 - 15 years of experience in software architecture and machine learning, with a strong preference for candidates who have successfully led large-scale AI transformations.

- Ability to thrive in a collaborative, hybrid work environment, demonstrating leadership and adaptability in a fast-paced consulting setting.