Java Full stack Engineer

Required skill: Core Java, React, Spring boot
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.


Key Responsibilities
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 LangChain, LangGraph, or AutoGen.
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/NoSQL 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 Client technical community and Agile/Scrum processes.
Required Qualifications
5+ years of progressive professional software engineering experience, with a minimum of 1-2 years dedicated to building and deploying AI-powered solutions.
Expert proficiency in Python, Java, or TypeScript/JavaScript, coupled with a profound understanding of data structures and object-oriented principles.
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/OpenShift).
Demonstrated experience with modern web stacks (React, Next.js, Tailwind CSS, JavaScript, TypeScript, etc.).
Practical experience with agentic frameworks (LangChain, LangGraph, AutoGen, 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 software delivery methodologies (SAFe, Scrum, Kanban).
Proficiency in various database technologies, including advanced SQL and vector databases (Oracle, PostgreSQL, MongoDB, Aurora, Pinecone, pgvector, etc.).
Experience with event-driven design and architecture (e.g., SQS, SNS, Kinesis, Kafka, Spark, Flink, RabbitMQ).
B.Tech/B.Eng. degree or equivalent work experience.
Preferred Qualifications
Experience in designing and implementing complex multi-agent collaboration architectures.
Familiarity with AI-driven development tools (e.g., Cursor, Claude, Copilot) to enhance productivity.
Proven architectural experience in building horizontally scalable, highly available, highly resilient, and low-latency applications.
Experience with both on-premises and public cloud infrastructure (e.g., OpenShift, AWS), including Infrastructure as Code tools (e.g., Terraform, CloudFormation).
Knowledge of security, observability, and monitoring tools (e.g., Grafana, Prometheus, Splunk, ELK, CloudWatch).
Prior experience mentoring and providing technical leadership to teams of 5 or more developers.
Familiarity with job schedulers (e.g., Apache Airflow, AutoSys, CloudWatch).