Description

What You'll Do:

• Build scalable and reusable AI services using Python and FastAPI/Flask.
• Design, build, and deploy GenAI applications using leading LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, and Llama.
• Develop and implement Agentic AI workflows using LangChain Agents and LangGraph, with exposure to CrewAI or AutoGen.
• Design and implement RAG pipelines, embedding strategies, and semantic retrieval solutions.
• Translate business and functional requirements into working GenAI and agentbased solutions.
• Apply effective prompt engineering techniques, context management, and hallucination reduction strategies.
• Integrate LLMs and agent systems with enterprise APIs, internal systems, and automation workflows.
• Work with vector databases (FAISS, Pinecone, Chroma, Weaviate) for semantic search and retrieval.
• Evaluate and optimize GenAI solutions for accuracy, performance, and cost efficiency.

Expertise You'll Bring:

• Strong experience in Python-based backend platforms
• Strong experience in LangChain and LangGraph
• Strong experience in Agentic environments
• Strong MongoDB or any NOSQL
• Experience in MCP
• Experience in Kafka/Queues, Workflows
• Exposure to Banking domain (KYC, Onboarding, Banking)
• Basic understanding of cloud-native concepts
• 8 years of experience in AI/ML, including data preprocessing, model development, training, and evaluation.
• 2-3 years of handson experience in Generative AI, including LLMs, embeddings, RAG, and LLMbased applications.
• 1+ year of practical experience with Agentic AI frameworks, especially LangChain Agents and LangGraph (CrewAI / AutoGen is a plus).
• Strong proficiency in Python and core libraries such as Pandas and NumPy.
• Handson experience with LangChain and LangGraph for building workflowbased and multiagent AI systems.
• Experience with OpenAI APIs, Azure OpenAI, HuggingFace, and prompt design techniques.
• Proficiency in building REST APIs using FastAPI or Flask.
• Experience deploying AI solutions on cloud platforms (Azure / AWS / GCP).
• Solid understanding of microservices architecture, API integration patterns, and enterprise application integration.
• Familiarity with Git, Docker, and standard development best practices

Key Skills

Education

Any Graduate