We are seeking a highly skilled Generative AI Engineer with expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and scalable AI application development. The ideal candidate should have hands-on experience in designing, developing, and deploying enterprise-grade GenAI solutions using leading LLMs, modern AI frameworks, vector databases, and cloud platforms. You will collaborate with cross-functional teams to build intelligent AI applications that solve real-world business problems.
Key Responsibilities
- Design, develop, and deploy enterprise-grade Generative AI applications using LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, Llama, and similar models.
- Build and implement Agentic AI workflows using frameworks like CrewAI, AutoGen, LangGraph, and LangChain Agents.
- Design and optimize Retrieval-Augmented Generation (RAG) pipelines, embedding-based retrieval systems, and semantic search solutions.
- Develop scalable AI services and APIs using Python, FastAPI, Flask, or similar frameworks.
- Integrate LLMs with enterprise applications, third-party APIs, automation workflows, and business systems.
- Implement advanced prompt engineering, hallucination reduction techniques, and model evaluation strategies to improve response quality.
- Work with vector databases such as FAISS, Pinecone, Chroma, and Weaviate for efficient knowledge retrieval.
- Deploy AI solutions on Azure, AWS, or GCP, ensuring scalability, security, and performance.
- Monitor, evaluate, and optimize AI models for accuracy, latency, reliability, and cost efficiency.
- Collaborate with Data Scientists, ML Engineers, Product Managers, and Software Developers to deliver production-ready AI solutions.
- Follow software engineering best practices, including version control, CI/CD, Docker, and automated deployments.
Required Skills & Qualifications
- 4+ years of experience in Artificial Intelligence/Machine Learning, including model development, data preprocessing, exploratory data analysis (EDA), model training, and evaluation.
- 2+ years of hands-on experience building Generative AI applications using LLMs, embeddings, RAG, and LLM-powered solutions.
- Minimum 6 months of practical experience with Agentic AI frameworks such as CrewAI, AutoGen, LangGraph, or LangChain Agents.
- Strong programming skills in Python.
- Experience with ML libraries including Scikit-learn, Pandas, NumPy, and related AI/ML ecosystems.
- Hands-on experience with OpenAI APIs, Azure OpenAI, Hugging Face, and prompt engineering techniques.
- Experience developing RESTful APIs using FastAPI, Flask, or Django.
- Strong understanding of REST APIs, microservices architecture, and system integration.
- Experience with vector databases including FAISS, Pinecone, Chroma, or Weaviate.
- Knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).
- Familiarity with Git, Docker, CI/CD pipelines, and deployment best practices.
- Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
- Experience with LangSmith, MLflow, LlamaIndex, or similar LLM observability and evaluation tools.
- Knowledge of AI governance, responsible AI practices, and LLM security.
- Experience with Kubernetes, container orchestration, and scalable cloud-native deployments.
- Exposure to MLOps pipelines and model monitoring solutions.
- Relevant certifications in Azure AI, AWS AI/ML, or Google Cloud AI are a plus.
Why Join Us?
- Work on cutting-edge Generative AI and Agentic AI technologies.
- Build production-scale AI solutions for enterprise applications.
- Collaborate with experienced AI, Data Engineering, and Product teams.
- Opportunity to work with the latest LLMs, cloud platforms, and modern AI frameworks.
- Continuous learning and career growth in one of the fastest-growing technology domains.
Pay: ₹50,000.00 - ₹90,000.00 per month
Benefits:
- Health insurance
- Provident Fund
Application Question(s):
- its a contract base job are you comfortable ?
Language:
Location:
- Indore, Madhya Pradesh (Indore) (Required)
Work Location: In person
