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Infosys

Gen AI Consultant

Bangalore, India

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hirly's read of this role

Seniority
Mid level
Country
IN
Work mode
On-site / unstated
First seen by hirly
1 Oct 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

We are seeking a highly skilled Generative AI Engineer with 2 to 5 years of experience in designing, developing, and deploying AI-powered applications. The ideal candidate should have hands-on expertise in LLMs, RAG, Agentic AI, Prompt Engineering, Python, LangChain, Vector Databases, and AI Model Integration.

Responsibilities

Design and develop Generative AI solutions using Large Language Models (LLMs).

Build and optimize RAG (Retrieval-Augmented Generation) pipelines.

Develop AI Agents using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar.

Integrate OpenAI, Azure OpenAI, Claude, Gemini, Llama, or other foundation models into enterprise applications.

Implement prompt engineering and fine-tuning strategies to improve AI outputs.

Build APIs and microservices to serve AI applications.

Work with vector databases such as Pinecone, ChromaDB, FAISS, Weaviate, or Milvus.

Collaborate with business and technical teams to translate requirements into AI solutions.

Optimize model performance, scalability, security, and cost.

Conduct testing, validation, and deployment of AI systems.

Technical requirements

Hands-on experience with Generative AI, LLMs, and Prompt Engineering.

Experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.

Knowledge of RAG Architecture and Vector Databases.

Experience with Azure OpenAI, OpenAI APIs, Gemini, Claude, Llama, or Hugging Face Models.

Understanding of NLP, Machine Learning, and Deep Learning concepts.

Experience with REST APIs and microservices.

Knowledge of Git, Docker, and CI/CD pipelines.

Familiarity with cloud platforms such as Azure, AWS, or GCP.

Additional responsibilities

Knowledge of MCP (Model Context Protocol).

Experience in multi-agent systems and Agentic AI workflows.

Exposure to fine-tuning, embeddings, and model evaluation.

Experience with Kubernetes and MLOps practices.

Knowledge of AI governance, security, and responsible AI practices.

Education

MCA,MTech,Bachelor of Engineering,BTech

Original posting on Infosys's site ↗

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