Azure AI & .NET Backend Engineer

Remote / Hybrid (India)•5 - 8 Years•Competitive / Based on 5-8 Yrs Exp

Core Competencies & Skills

Azure APIMAzure AI FoundryAzure AI SearchAzure Blob StorageAzure Document IntelligenceDatabricksMosaic AISSE StreamingRAGVector SearchEmbeddingsLLMsPrompt EngineeringTool CallingC#.NETAngularCode Sandboxing

Role Requirements

5–8 years of professional experience in backend development using C# and .NET.
Hands-on experience with the Azure AI Stack: Azure API Management (APIM), Azure AI Foundry, Azure AI Search, and Blob Storage.
Experience with Databricks & Mosaic AI, implementing SSE (Server-Sent Events) streaming, inference logging, and token usage tracking.
Strong understanding of RAG Pipelines: document chunking, embedding generation, and vector search for knowledge base retrieval.
Proficiency in LLM Integration: prompt engineering, structured outputs, and tool/function calling.
Familiarity with Azure Document Intelligence for advanced document analysis.
Understanding or experience with Code Execution & Sandboxing for secure spreadsheet-based reasoning.
Working familiarity with Angular for cross-functional collaboration with frontend teams.
Immediate joiners preferred; full-time on GcsteQ payroll.

Job Details & Overview

About GuruGrace Consultancy Services (GcsteQ)

GuruGrace Consultancy Services (GcsteQ) is a technology consulting and solutions organization specializing in enterprise cloud architecture, AI platform development, and modern backend engineering.

Position Overview

Position: Azure AI & .NET Backend Engineer
Experience Bracket: 5 - 8 Years
Employment Type: Full-time (on GcsteQ payroll)
Notice Period / Availability: Immediate joiner is preferred
Location: Remote / Hybrid (India)
Point of Contact: Saroj Gediya (support@goairm.com | +91 98241 80477)

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Core Skills & Responsibilities

Azure AI Stack: Hands-on experience with Azure API Management (APIM), Azure AI Foundry, Azure AI Search, and Azure Blob Storage.
Databricks & Mosaic AI: Experience implementing Server-Sent Events (SSE) streaming, inference logging, and token usage tracking.
RAG Pipelines: Strong understanding of document chunking, embedding generation, and vector search, as knowledge base retrieval is a core product feature.
C# / .NET: Backend development experience integrating with AI and LLM APIs.
LLM Integration: Proficiency in prompt engineering, structured outputs, and tool / function calling.

Good to Have

Azure Document Intelligence: Experience strengthening document analysis capabilities.

Code Execution & Sandboxing: Experience enabling secure code execution for spreadsheet-based reasoning.

Angular: Working familiarity to collaborate effectively with frontend engineering teams.

Technical Stack

Azure APIM, Azure AI Foundry, Azure AI Search, Azure Blob Storage, Azure Document Intelligence, Databricks, Mosaic AI, SSE Streaming, RAG, Vector Search, Embeddings, LLMs, Prompt Engineering, Tool Calling, C#, .NET, Angular, Code Sandboxing.

Requirements

5–8 years of professional software engineering and backend systems experience.
Deep hands-on proficiency with C# / .NET enterprise backends.
Solid experience building production RAG pipelines and integrating with Azure AI / Databricks Mosaic AI.
Demonstrated background in SSE streaming, inference logging, and prompt engineering.
Ready to join immediately on GcsteQ payroll.

How to Apply

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