Data Integration

15 hours ago

chennai district, India Chargebee Full time

About the Role We are seeking a highly motivated Software Engineer with a strong foundation in Java (Spring Boot) , data integration , and a growing expertise in Large Language Models (LLMs) . This role is ideal for engineers who enjoy working at the intersection of scalable data systems and AI-driven applications , building robust pipelines while also exploring cutting-edge generative AI solutions. Key Responsibilities Design and implement data integrations including APIs, SaaS connectors, and ETL/ELT pipelines to ensure reliable and scalable data flows. Build and maintain backend services and applications using Java (Spring Boot or equivalent frameworks) . Develop Python-based workflows for AI/ML pipelines, experimentation, and automation scripting. Integrate and experiment with LLMs (OpenAI, Anthropic, LLaMA, Mistral, etc.) for use cases such as retrieval-augmented generation (RAG), summarization, and intelligent data insights. Implement vector search solutions using Pinecone, Weaviate, Milvus, or FAISS for LLM-backed applications. Collaborate with product, data, and ML teams to design end-to-end solutions that combine data engineering with AI capabilities . Ensure systems meet high standards of performance, scalability, security, and compliance . Required Qualifications Strong programming experience in Java (Spring Boot or equivalent frameworks) . Familiarity with Python , particularly for AI/ML workflows and scripting . Proven experience with data integrations : APIs, SaaS connectors, ETL/ELT pipelines. Exposure to LLMs (OpenAI, Anthropic, LLaMA, Mistral, etc.) and associated frameworks (LangChain, LlamaIndex, Hugging Face Transformers). Experience working with databases (SQL/NoSQL) and vector search technologies (Pinecone, Weaviate, Milvus, FAISS). Preferred Skills Knowledge of cloud platforms (AWS, GCP, or Azure) for deploying scalable systems and ML workloads. Familiarity with containerization and orchestration (Docker, Kubernetes). Understanding of data governance, observability, and security best practices . Interest in generative AI advancements and a passion for building practical applications on top of them.

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