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Salary
≈ $12k – $32k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Junior · 2+ years exp

Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Oct 1, 2026. Infosys scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Infosys Limited is an Indian multinational information technology company providing business consulting, information technology, and outsourcing services. Founded in 1981 by N. R. Narayana Murthy and six engineers in Pune, India, the company is headquartered in Bengaluru and stands as one of India's largest IT services companies.

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.

Preferred skills

Technology->AI-Generative AI->Generative AI for Data Analytics

Education

MCA,MTech,Bachelor of Engineering,BTech

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