Data Integration & LLM Engineer

About the Role

Software Engineer

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.