Description

As an Data Scientist, you will design and implement cutting-edge AI solutions that power intelligent applications across industries like Healthcare, BFSI, and Retail. This role combines deep technical expertise in LLMs, RAG pipelines, and agentic AI with strong collaboration skills to deliver scalable, production-ready systems that drive business impact.

What You’ll Do
 

• Design and build Retrieval Augmented Generation (RAG) pipelines integrating LLMs, vector stores, and knowledge graphs from proof of concept to production.
   
• Develop and orchestrate multi-step LLM agents and decision-making loops using Lang Graph/Lang Chain.
   
• Write clean, test-driven Python code for model serving, data pipelines, and microservices.
   
• Integrate Java Services for legacy or latency-critical components via gRPC/REST.
   
• Containerize and Deploy services using Docker and Kubernetes (GKE/EKS), ensuring scalability and resilience.
   
• Set Up and Maintain GitLab CI/CD pipelines for automated testing, security scans, and blue-green deployments.
   
• Optimize Algorithms and Data Structures for efficient indexing, graph traversal, and low-latency retrieval.
   
• Collaborate Cross-functionally with product, UX, data science, and operations teams to translate requirements into technical solutions.
   
• Mentor Junior engineers and contribute to internal knowledge sharing through code reviews and tech talks.
   

Requirements

What You Bring
 

• 5+ years of professional Python development experience (async, type hints, testing).
   
• Strong understanding of data structures and algorithms (hash tables, trees, graphs, heaps).
   
• Expertise in LLMs, tokenization, fine-tuning, prompt engineering, and evaluation.
   
• Hands-on experience building end-to-end RAG systems (vector DBs, embeddings, similarity search, knowledge graph integration).
   
• Practical experience with LangGraph or LangChain for agentic workflows.
   
• Excellent communication and collaboration skills in Agile environments.
   

Preferred Skills:
 

• Java microservices integration via gRPC/REST.
   
• Docker, Kubernetes, Helm for production deployments.
   
• GitLab CI/CD, cloud platforms (GCP/AWS/Azure), and MLOps practices.
   
• Observability tools (Prometheus, Grafana) and container security.
   
• Open-source contributions to LangChain/LangGraph or similar AI tooling

Key Skills

Education

Any Graduate