Summary
✨ AI‑Generated
A technology organization is seeking a Senior Full-Stack Software Engineer with strong Java expertise to build production-grade AI applications. You will design and implement RAG pipelines covering ingestion, chunking, embeddings, vector storage, retrieval, and generation, while developing scalable REST APIs and microservices. Experience with vector databases, LLM orchestration frameworks, event-driven systems, and cloud-native infrastructure is highly relevant.
Highlights
A senior engineering opportunity focused on production-grade AI applications and end-to-end RAG systems. The role combines strong Java and Spring expertise with cloud-native development, scalable microservices, event-driven architectures, and modern vector search and LLM orchestration technologies.
Description
About the Role
We are looking for a Senior Software Engineer with full-stack developer with strong Java expertise and hands-on experience in building Retrieval-Augmented Generation (RAG) systems.
You will design, develop, and deploy AI-powered applications on cloud-native infrastructure, working closely with cross-functional teams to deliver scalable, production-grade solutions.
Must-Have Requirements
Designed and implemented RAG pipelines end-to-end (document ingestion, chunking, embedding, vector storage, retrieval, and generation)
Experience with vector databases (e.g., Pinecone, Weaviate, pgvector, OpenSearch) and familiarity with LLM orchestration frameworks (LangChain, LlamaIndex, or similar)
POC-level experience is acceptable if depth of work is demonstrable.
Strong proficiency in core Java and Spring Boot / Spring Cloud
Building RESTful APIs and microservices at scale
Designing and operating event-driven architectures, Familiarity with Kafka Connect or Kafka Streams is a plus,
Deploying and managing containerized workloads on Amazon EKS
Writing and maintaining Helm charts for Kubernetes deployments
Working knowledge of EC2 instance management, networking, and IAM
Experience with NoSQL databases such as MongoDB Or Amazon DocumentDB and caching solutions like Redis.
Familiarity with CI/CD tools like Harness and monitoring/logging platforms like Splunk.
What You'll Do
Architect and build RAG-based features that integrate LLMs into existing product workflows
Develop high-throughput Java microservices backed by Kafka event streams
Package, deploy, and operate services on AWS EKS using Helm
Collaborate with data, platform, and product teams to define technical direction
Mentor junior engineers and contribute to engineering standards
Qualifications
B.Tech / B.E.
/ M.Tech in Computer Science or equivalent experience
5–7 years of professional software engineering experience
Strong communication skills and ability to work in an Agile environment
Self-driven with a bias for action and ownership
