AI Developer

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.  Department: Tech@Lilly Location: Eli Lilly, Bengaluru Position Type: Full-Time Level: R2-3 Are you passionate about designing and building AI-powered applications that bring together large language models, agentic workflows, and full stack engineering to solve real business problems? Do you thrive working across the stack — AI/LLM integration, backend services, modern frontend frameworks, and cloud deployment — while staying curious about what GenAI can unlock next? If so, Tech@Lilly is looking for an AI Full Stack Engineer to design, build, and scale AI-powered applications and full stack solutions across the enterprise. As an AI Full Stack Engineer, you will design and develop AI-powered applications using Large Language Models, build Agentic AI workflows leveraging tools, reasoning, memory, and orchestration patterns, and develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge sources. You will work across the full stack — building responsive frontend applications, scalable backend services and APIs, and cloud-native deployments on AWS — while integrating AI services with business applications and ensuring systems are secure, reliable, and production-ready. What You’ll Be Doing: ·       Design and build AI-powered applications using Large Language Models, agentic AI workflows, and Retrieval-Augmented Generation (RAG) solutions built on enterprise knowledge sources. ·       Integrate AI services with business applications and external systems, and continuously evaluate, optimize, and monitor AI application performance and quality. ·       Build responsive, modern frontend applications and scalable backend services and APIs, using reusable components and clean, maintainable code. ·       Deploy and manage applications on cloud platforms (preferably AWS), building CI/CD pipelines, containerizing with Docker, and orchestrating workloads with Kubernetes. ·       Design and manage SQL and NoSQL databases, integrate enterprise systems and third-party services, and ensure secure, compliant handling of data. ·       Collaborate closely with product teams to translate business requirements into technical solutions, and implement monitoring, logging, and observability best practices. What You Will Bring: