Key Responsibilities

- Design and develop scalable AI applications using Python, LangChain, and LangGraph.

- Build and optimize Retrieval-Augmented Generation (RAG) solutions using vector databases.

- Develop AI agents, multi-agent systems, and workflow orchestration using LangGraph.

- Integrate Large Language Models (LLMs) such as OpenAI GPT, Azure OpenAI, Claude, Gemini, or Llama.

- Create prompt engineering strategies to improve model performance and accuracy.

- Develop REST APIs and backend services for AI applications.

- Implement memory management, tool calling, agent execution, and workflow automation.

- Work with structured and unstructured data sources for AI-based solutions.

- Monitor, troubleshoot, and optimize GenAI application performance.

- Collaborate with cross-functional teams to deliver enterprise-grade AI solutions.

Required Skills





Technical Skills

- Strong proficiency in Python Programming.

- Hands-on experience with LangChain and LangGraph.

- Experience with Generative AI and Large Language Models (LLMs).

- Knowledge of Prompt Engineering techniques.

- Experience in building RAG (Retrieval-Augmented Generation) solutions.

- Hands-on experience with Vector Databases such as Pinecone, FAISS, ChromaDB, Weaviate, or Milvus.

- Knowledge of Embeddings and Semantic Search.

- Experience with REST APIs using Flask or FastAPI.

- Robust understanding of AI application deployment and MLOps concepts.

- Experience with Git and CI/CD pipelines.

📌 Senior Software Engineer (Bangalore Rural)
🏢 Cognizant
📍 Bangalore Rural