AI Engineer

Medline India; Maharashtra; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Medline India seeks an AI Solutions Engineer to design and build intelligent apps and AI-powered search experiences using Microsoft’s AI stack. You will engineer autonomous/assisted agents, weaving in Azure OpenAI, embeddings, and RAG pipelines.

Lead ingestion pipelines, chunking, and metadata enrichment while optimizing latency, token usage, and performance. Strong .NET and cloud Architecture skills are essential.

Qualifications

• 7-10 years of full stack experience in the .NET ecosystem.
• 2-4 years in AI engineering with Azure OpenAI and search.
• Experience with Azure AI services and embeddings is essential.

Responsibilities

• Design end‑to‑end AI search and agent systems.
• Build ingestion pipelines with chunking and metadata enrichment.
• Optimize latency, embeddings, and token usage; tune performance.
• Develop prompt strategies for AI agents and search experiences.

Skills

Full stack .Net

AI engineering

Azure OpenAI Service

Azure AI Search

Azure Machine Learning

RAG pipelines

Power Platform

Microsoft Graph API

Foundry

Tools

Designing AI search systems

Ingestion pipelines

Azure cloud architecture

Performance tuning

Prompt Engineering

Job description

AI Solutions Engineer to design, build intelligent apps, and operationalize AI-powered search experiences and autonomous/assisted agents using Microsoft’s AI ecosystem

Core Technical Skills

• Overall 7-10 years of Full stack experience- . Net ecosystem - Must have
• 2-4 Years of experience in AI engineering
• Experience in Azure OpenAI Service, embeddings - Must have
• Azure AI Search (vector search, hybrid search, reranking)- Must have
• Azure Machine Learning -
• Retrieval Augmented Generation (RAG) pipelines with Azure OpenAI Service
• Power platform, specifically power automate - Nice to have
• Microsoft Graph API & M365 integration - Nice to have
• Foundry - Nice to have

Engineering Skills

• Designing end‑to‑end AI search and agent systems
• Implementing ingestion pipelines, chunking, metadata enrichment
• Understanding of Azure cloud architecture (App Service, AKS, Key Vault, Monitor, DevOps)
• Performance tuning (latency, token optimization, embeddings, caching)
• Prompt Engineering