Data Integration and LLM Engineer

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.