Posted on: 18/05/2026
Description :
- Hands-on experience with LLMs (OpenAI, open-source models, etc.)
- Expertise in RAG (Retrieval-Augmented Generation) frameworks
- Experience building Agentic AI systems / autonomous workflows
- Understanding of GenAI architectures and use cases
- Experience with Vector Databases (Pinecone, FAISS, Weaviate, etc.)
- API integration and orchestration of AI services
- Full Stack Development (React, Node.js, or similar)
- Programming knowledge in Java (good to have)
- Experience with AI dev tools like Cursor, Replit, LangChain, LlamaIndex
- Exposure to prompt engineering and fine-tuning techniques
- Knowledge of cloud platforms (AWS / Azure / GCP)
- Experience in building chatbots, copilots, or AI assistants
Roles & Responsibilities :
- Build and deploy Agentic AI systems capable of multi-step reasoning and task automation
- Develop scalable backend services and APIs for AI integrations
- Implement and optimize vector search and embedding pipelines
- Work on prompt engineering, context management, and response optimization
- Integrate LLMs with enterprise data sources using RAG frameworks
- Collaborate with product and engineering teams to deliver end-to-end AI solutions
- Ensure performance, scalability, and reliability of AI systems
- Evaluate and experiment with latest GenAI tools, frameworks, and models
- Maintain code quality, documentation, and best practices
- Experience in building production-grade AI applications
- Strong problem-solving mindset with hands-on coding ability
- Ability to work in fast-paced, innovation-driven environments
- Understanding of AI limitations, hallucinations, and evaluation metrics
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