Generative AI + ML Engineer (8 -12 years)

Purpose of

To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure. Accountabilities • Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data. • Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures. • Development of processing and analysis algorithms fit for the intended data complexity and volumes. • Collaboration with data scientist to build and deploy machine learning models. • Own the end-to-end product lifecycle for Generative AI, Agentic AI, AI/ML solutions, from design to deployment • .Act as a bridge between business and technology teams, ensuring alignment of

and technical specifications • .Enable data-driven insights and AI-powered automation for Conversational AI, GenAI, and ML use cases . Key Responsibiliti • es Design & Implement Agentic, GenAI Solutions: Build robust Generative AI and Agentic AI applications using AWS Bedrock, SageMaker, and other AWS ML servic • es.Develop LLM bases Use Cases: Architect and implement LLM based use cases like RAG, Summarization, data analysis etc. for enterprise-scale applicatio • ns.LLM Finetuning & Evaluation: Fine-tune, evaluate, and optimize Large Language Models (LLMs) for performance, accuracy, and safe • ty.Integration & Collaboration: Work closely with product managers, engineers, and UX teams to embed AI capabilities into business workflo • ws.Innovation & Research: Stay ahead of AI trends, frameworks, and best practices; apply them to drive continuous innovati • on.Quality & Governance: Maintain system design integrity, review test strategies and ensure compliance with AI ethics and security standar • ds.Optimize solutions through thorough research experimentation, and advanced problem-solving techniqu • es.Communicate complex concepts and results effectively to both technical and non-technical stakeholde rs.