Python Engineer Agentic Ai Llms

Vibehackers; Hyderabad; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Vibehackers is seeking a Python Engineer to build AI-powered enterprise applications with a focus on agentic AI workflows and LLM integrations. You will design and implement intelligent automation solutions and production-ready services exposing AI capabilities.

Responsibilities include developing AI apps with LLMs, RAG architectures, embeddings, and prompt engineering, integrating OpenAI/LangChain/LangGraph/LlamaIndex, and deploying with Docker, Kubernetes, and major cloud platforms.

Qualifications

• Experience with generative and agentic AI concepts and LLMs.
• Familiarity with OpenAI APIs and frameworks LangChain, LangGraph, LlamaIndex.
• Knowledge of RAG architectures, embeddings, and prompt engineering.
• Experience with REST APIs and microservices.
• Experience with Docker, Kubernetes, and cloud platforms.
• Experience with CI/CD, MLOps, and Git.

Responsibilities

• Develop Python AI-powered enterprise applications.
• Design and implement agentic AI workflows and automation solutions.
• Build apps leveraging LLMs, RAG architectures, embeddings, and prompt engineering.
• Integrate 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.
• 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.

Skills

Collaboration

Cross-functional communication

API design

Microservices architecture

CI/CD

MLOps

Prompt engineering

System design

Testing and production deployment

Tools

OpenAI API integrations

LangChain

LangGraph

LlamaIndex

Docker

Kubernetes

REST APIs

Job description

Building agentic AI with LLMs and prompt engineering; integrates LangChain, LlamaIndex and OpenAI for AI-driven applications.

About the Role

Build and deploy enterprise AI applications in Python focusing on agentic AI workflows, LLM integration, RAG architectures, embeddings, and prompt engineering. Implement REST APIs and microservices, integrate OpenAI and related frameworks, and deploy solutions on Docker/Kubernetes and cloud platforms.

Job Description

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

• 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).

Skills

Collaboration Cross-functional communication API design Microservices architecture CI/CD MLOps Prompt engineering System design Testing and production deployment