Python Engineer Agentic Ai Llms

Role

We are looking for a Python Engineer to develop AI-powered enterprise applications with a focus on agentic AI workflows and large language model (LLM) integrations. The role involves designing and implementing intelligent automation solutions, retrieval-augmented generation (RAG) architectures, and production-ready services that expose AI capabilities.

Key Responsibilities

• Develop AI-powered enterprise applications using Python and modern AI frameworks.
• Design and implement agentic AI workflows and intelligent automation solutions.
• Build applications leveraging LLMs, RAG architectures, embeddings, and prompt engineering techniques.
• Integrate third-party AI frameworks and APIs such as OpenAI, LangChain, LangGraph, and LlamaIndex into enterprise solutions.
• Develop REST APIs and microservices to expose AI capabilities.
• Deploy AI applications using Docker, Kubernetes, and cloud platforms (Azure, AWS, GCP).
• Collaborate with Data Scientists, Product Teams, and Solution Architects to deliver AI-driven solutions.
• Participate in CI/CD pipelines, MLOps implementation, testing, and production deployments.

Requirements

• Strong Python development skills.
• Experience with generative AI, agentic AI concepts, and working with large language models (LLMs).
• Familiarity with OpenAI APIs and framework integrations (e.g., LangChain, LangGraph, LlamaIndex).
• Knowledge of RAG architectures, embeddings, and prompt engineering.
• Experience with TensorFlow, PyTorch, or Keras.
• Experience building REST APIs and microservices.
• Experience with containerization and orchestration tools: Docker and Kubernetes.
• Experience deploying to cloud platforms such as Azure, AWS, or GCP.
• Experience with CI/CD, MLOps practices, and version control (e.g., GitHub).