Java Full Stack Engineer - React

LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 700+ clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world. Powered by nearly 90,000 talented and entrepreneurial professionals across more than 30 countries, LTIMindtree a Larsen & Toubro Group company combines the industry-acclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation  more information, please visit

Join our pioneering team as a Full-Stack AI Engineer and be at the forefront of building the next generation of intelligent AI-powered products that redefine user experiences and solve complex business challenges. This pivotal role empowers you to own the entire solution stack—from intuitive front-end interfaces to robust back-end infrastructure and cutting-edge agentic AI systems. You will play a critical role in designing, developing, and deploying high-impact AI-driven solutions, driving engineering excellence, and influencing our software architecture.

We’re seeking a passionate problem-solver who thrives in a collaborative, agile environment, dedicated to crafting innovative solutions and contributing to a vibrant technical community.

• Pioneer Full-Stack AI Application Development:
  Design, develop, and deploy transformative end-to-end applications leveraging modern web frameworks (React, Next.js), FastAPI (Python), and Java, with Large Language Models (LLMs) at their core.
• Architect Agentic AI Systems:
  Lead the design and implementation of sophisticated autonomous agents capable of multi-step reasoning, planning, and dynamic task execution using frameworks like Lang Chain, Lang Graph, or Auto Gen.
• Innovate RAG Pipeline Design:
  Architect and optimize production-grade Retrieval-Augmented Generation (RAG) pipelines, focusing on advanced embedding strategies, efficient vector database management (Pinecone, Milvus, Chroma), and superior retrieval performance.
• Build Scalable Back-End & API Integrations:
  Develop highly performant asynchronous back-end services that seamlessly integrate LLMs, external APIs, and tools, ensuring exceptional reliability and ultra-low latency.
• Optimize Data & Database Management:
  Strategically manage structured and unstructured data, overseeing both traditional SQL/No
  
  SQL databases and advanced vector databases to enable context-aware and intelligent AI systems.
• Champion Engineering Excellence & Agile Delivery:
  Drive best practices in code quality, unit testing, CI/CD, and security. Act as a strong contributor within an agile software delivery team, collaborating to achieve sprint goals and actively participating in the broader Citi technical community and Agile/Scrum processes.

• 5+ years of progressive professional software engineering experience
  , with a minimum of 1-2 years dedicated to building and deploying AI-powered solutions.
• Extensive hands‑on experience with Large Language Models (LLMs) (e.g., OpenAI GPT, Anthropic Claude, Gemini, Llama), including fine‑tuning techniques and advanced prompt engineering.
• Proven expertise in designing and implementing RAG architectures, encompassing embedding strategies, vector stores, and semantic search.
• Deep experience with microservices; designing and implementing RESTful/GraphQL APIs; and practical application of containerization technologies (Docker/Kubernetes/Open Shift).
• Practical experience with agentic frameworks (Lang Chain, Lang Graph, Auto Gen, CrewAI, etc.), including designing, implementing, and orchestrating multi‑agent systems.
• Solid understanding and practical application of frameworks such as Spring Boot, FastAPI, Express, etc.
• Significant experience working within agile and iterative…