Job Summary

We are seeking a highly skilled Generative AI Engineer with 5+ years of software engineering experience and strong expertise in AWS and Azure cloud platforms. The ideal candidate should have hands-on experience designing, developing, deploying, and optimizing LLM-based applications, RAG pipelines, AI agents, and enterprise-grade GenAI solutions. The role requires strong proficiency in Python, cloud-native development, MLOps practices, and up-to-date AI frameworks.

Responsibilities

- Design, develop, and deploy enterprise-scale Generative AI solutions using LLMs and foundation models.
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge-based applications.
- Develop intelligent AI agents and workflows using LangChain, LangGraph, Semantic Kernel, CrewAI, or similar frameworks.
- Integrate GenAI solutions with enterprise systems, APIs, databases, and third-party services.
- Implement prompt engineering, prompt tuning, and LLM evaluation frameworks.
- Deploy, monitor, and scale AI applications on AWS and Azure cloud environments.
- Design secure and scalable cloud architectures leveraging serverless and containerized services.
- Implement CI/CD pipelines and MLOps best practices for model deployment and lifecycle management.
- Collaborate with Data Scientists, ML Engineers, Product Owners,



and Architects to deliver business-focused AI solutions.
- Monitor model performance, latency, cost optimization, hallucination control, and overall system reliability.
- Stay updated on advancements in LLMs, Agentic AI, Multi-Agent Systems, Vector Databases, and Cloud AI services.

Technical Requirements

- GenAI
- Generative AI
- LLM
- RAG
- LangChain
- LangGraph
- Semantic Kernel
- Agentic AI
- AI Agents
- AWS Bedrock
- Azure OpenAI
- Azure AI Studio
- Prompt Engineering
- Vector Database
- Pinecone
- FAISS
- ChromaDB
- FastAPI
- Python
- AKS
- EKS
- Docker
- Kubernetes
- MLOps
- Azure ML
- OpenSearch
- Hugging Face

Additional Responsibilities

- Experience with multi-agent frameworks and autonomous AI workflows.
- Knowledge of Responsible AI, AI Safety, and Governance.
- Familiarity with model monitoring, evaluation, and feedback loops.
- Hands-on experience in productionizing GenAI applications.
- Exposure to distributed systems and microservices architecture.

Educational Requirement Bachelor of Engineering,Bachelor Of Technology (Integrated)

Preferred Skills

- Technology->AI-Data science->Machine Learning
- Technology->AI-Generative AI->Generative AI for Data Analytics
- Technology->AI-Generative AI->Artificial Intelligence - BASIC

Service Line

Data Analytics Unit

📌 Gen Ai Engineer (Bengaluru)
🏢 Infosys
📍 Bengaluru