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.