Description

Key Responsibilities

• Design and develop Agentic AI and Generative AI applications using LLMs, AI agents, and modern AI frameworks.
• Build and optimize LLM-powered solutions using RAG architecture, embeddings, semantic search, and contextual retrieval.
• Implement AI agents with tool calling, function calling, multi-step reasoning, workflow orchestration, and memory management.
• Integrate vector databases such as Pinecone, Chroma, Weaviate, or FAISS for efficient document retrieval and knowledge management.
• Develop scalable, secure, and high-performance REST APIs using Python and FastAPI.
• Work with frameworks such as LangChain, LangGraph, or LlamaIndex to build and orchestrate AI workflows.
• Integrate LLMs from providers such as OpenAI, Azure OpenAI, Anthropic, or open-source models.
• Optimize prompts, retrieval quality, response accuracy, latency, and token consumption.
• Implement evaluation, monitoring, guardrails, and error-handling mechanisms for production AI applications.
• Collaborate with cross-functional teams to understand business requirements and deliver production-ready AI solutions.
• Follow best practices for coding, testing, deployment, scalability, and AI application security

Key Skills

Education

Bachelor's degree