Job Summary

We are seeking a highly skilled Generative AI Engineer with robust expertise in Python, Machine Learning, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Natural Language Processing (NLP), and Cloud Technologies. The ideal candidate will design, develop, and deploy scalable AI-powered applications leveraging modern AI frameworks, vector databases, cloud platforms, and microservices architecture.

Key Responsibilities

Generative AI & LLM Development

- Design and implement AI-powered applications using Large Language Models (GPT, Llama, Claude, Gemini, Mistral, etc.).
- Build and optimize Retrieval Augmented Generation (RAG) pipelines for enterprise use cases.
- Develop conversational AI solutions, chatbots, virtual assistants, and AI agents.
- Create and optimize prompts using advanced Prompt Engineering techniques.
- Fine-tune, evaluate, and deploy LLMs for business-specific requirements.
- Integrate AI solutions with enterprise applications and APIs.

Machine Learning & NLP
- Develop, train, and deploy Machine Learning models using Python-based frameworks.

- Implement NLP solutions including

- Text Classification

- Named Entity Recognition (NER)

- Sentiment Analysis

- Information Extraction

- Document Processing

- Semantic Search
- Perform model monitoring, evaluation, and performance optimization.

RAG & Vector Databases
- Build scalable RAG architectures using LangChain and related frameworks.
- Implement embedding generation and semantic search solutions.
- Work with vector databases such as:

- Pinecone

- ChromaDB

- Weaviate

- FAISS

- Milvus

- Azure AI Search
- Optimize retrieval accuracy, latency, and relevance.

Backend Development
- Develop scalable backend services using:

- Python

- Java

- Spring Boot




- Build and maintain RESTful APIs and microservices.
- Design robust integration layers between AI models and enterprise systems.

Cloud & DevOps
- Deploy AI and ML workloads on:

- AWS

- Azure
- Develop serverless applications using Azure Functions.
- Containerize applications using Docker.
- Implement CI/CD pipelines and cloud-native deployment strategies.
- Monitor and optimize cloud infrastructure costs and performance.

Database Management
- Design and optimize SQL queries and database schemas.
- Work with relational databases and AI data pipelines.
- Manage metadata and vector storage solutions.

Required Skills

Technical Skills

- Strong programming experience in Python.
- Good experience in Java and Spring Boot.
- Strong understanding of Machine Learning and Deep Learning concepts.
- Hands-on experience with Large Language Models (LLMs).
- Experience building production-grade RAG solutions.
- Expertise in Natural Language Processing (NLP).
- Experience with LangChain, LangGraph, LlamaIndex, or equivalent frameworks.
- Knowledge of Prompt Engineering techniques.
- Experience with Vector Databases and Embedding Models.
- Strong SQL and database design skills.
- Experience developing REST APIs and Microservices.
- Hands-on experience with Docker.
- Experience with AWS and/or Microsoft Azure.
- Experience with Azure Functions.

Preferred Skills
- Experience with MLOps tools and model deployment.
- Knowledge of Kubernetes.
- Familiarity with Hugging Face ecosystem.
- Experience with AI Agents and Agentic AI frameworks.
- Knowledge of Generative AI governance and responsible AI practices.
- Exposure to multi-modal AI applications.

Qualifications
- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Engineering, or related field.
- Experience delivering enterprise-scale AI applications.

📌 Artificial Intelligence Engineer- Pan India (Bengaluru)
🏢 Infosys
📍 Bengaluru