Data Integration

2 days ago

New Delhi, India Chargebee Full time

About the RoleWe 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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