Gen AI Engineer

Job highlights

• The ideal candidate should have strong expertise in Python,AI / ML concepts,prompt engineering,vector databases,and cloud-native deployment architectures
• Preferred Skills
• Strong programming skills in Python . Hands-on experience with LLMs and GenAI ecosystems .
• Experience with LangChain,LangGraph,CrewAI,OpenAI APIs,Hugging Face,AutoGen .

Job Summary

We are seeking a skilled and innovative Generative AI Engineer to design, develop, and deploy AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks. The ideal candidate should have strong expertise in Python, AI/ML concepts, prompt engineering, vector databases, and cloud-native deployment architectures. The role involves building scalable GenAI solutions such as AI chatbots, copilots, intelligent search systems, document processing platforms, and AI automation workflows.

Responsibilities

• Design and develop Generative AI applications using LLMs such as GPT, Claude, Gemini, Llama, or Mistral

• Build and optimize RAG pipelines using embeddings and vector databases

• Develop AI copilots, chatbots, document intelligence systems, and multi-agent workflows

• Implement prompt engineering, function/tool calling, and AI orchestration frameworks

• Fine-tune and evaluate foundation models for enterprise use cases

• Integrate GenAI capabilities with APIs, databases, enterprise systems, and cloud platforms

• Build scalable backend services using Python and FastAPI

• Deploy and monitor AI applications on cloud platforms like AWS, Azure, or GCP

• Implement LLMOps/MLOps practices including model monitoring, observability, governance, and evaluation

• Collaborate with product managers, data engineers, and business stakeholders to deliver AI solutions

• Ensure responsible AI practices including security, hallucination mitigation, and data privacy

  Requirements

  Technical Skills

• Strong programming skills in Python

• Hands-on experience with LLMs and GenAI ecosystems

• Experience with LangChain, LangGraph, CrewAI, OpenAI APIs, Hugging Face, AutoGen

• Knowledge of RAG Architecture

• Prompt Engineering

• Embeddings

• Vector Databases

• AI Agents

• Experience with vector DBs such as Pinecone, FAISS, ChromaDB, Weaviate, Milvus

• Understanding of ML/DL fundamentals and Transformer architecture

• Experience with cloud services: AWS Bedrock / SageMaker, Azure OpenAI, GCP Vertex AI

• Experience with Docker, Kubernetes, CI/CD pipelines

• Knowledge of SQL and NoSQL databases

  Preferred Skills

• Experience in fine-tuning LLMs using LoRA / QLoRA / PEFT

• Exposure to multimodal AI systems

• Knowledge of AI evaluation frameworks and observability tools

• Experience with GPU optimization and inference tuning

• Understanding of AI governance and responsible AI practices

• Exposure to autonomous and agentic AI systems

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.