Description

Job Description:
Key Responsibilities
- Design and develop Java‐based microservices integrated with Generative AI frameworks.
- Implement solutions using LangChain/LangGraph for orchestration of LLM workflows.
- Build and optimize Retrieval‐Augmented Generation (RAG) pipelines for enterprise applications.
- Integrate LLMs (Large Language Models) with backend services to deliver intelligent features.
- Work with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus) for semantic search and knowledge retrieval.
- Collaborate with product owners, architects, and cross‐functional teams to define AI‐driven solutions.
- Mentor engineers and lead technical discussions, ensuring adherence to best practices.
- Ensure scalability, performance, and security of AI‐enabled distributed systems.
Essential Skills
- Strong expertise in Java 8+, Spring Boot, and Microservices architecture.
- Hands‐on experience with LangChain/LangGraph for LLM orchestration.
- Deep understanding of RAG pipelines and LLM integration.
- Proficiency in working with vector databases (Pinecone, Weaviate, FAISS, Milvus).
- Experience with RESTful APIs, JSON/XML integration, and service orchestration.
- Familiarity with CI/CD pipelines, Docker, Kubernetes, and container orchestration.
- Exposure to cloud platforms (AWS, Azure, GCP) for AI/ML services.
Desirable Skills
- Knowledge of prompt engineering and fine‐tuning LLMs.
- Experience with transformer models (OpenAI, Hugging Face, Anthropic).
- Exposure to data pipelines and streaming platforms (Kafka, Flink, Spark).
- Strong problem‐solving, analytical, and leadership skills.
- Agile/Scrum methodology experience

Key Skills

Education

Any Graduate