Job Summary

We are a Microsoft Partner Company building Custom AI Solutions on the Azure Platform. We are seeking an experienced AI Engineer who can engineer and deliver production-ready AI systems across Azure AI Services, Generative AI, Agentic AI, and contemporary data platforms.

The AI Engineer is responsible for building complete AI solutions end to end – provisioning Azure resources, implementing AI workflows, building Agentic AI systems, engineering data pipelines, and deploying to production. This role requires strong hands-on Azure AI expertise, system-level thinking, and the ability to independently architect implementation approaches for complex AI use cases.

Key Responsibilities

Solution Engineering & Development

 Build end-to-end AI systems using Azure AI Services – Azure OpenAI, AI Search, Document Intelligence, Cognitive Services, Azure ML

 Engineer Agentic AI solutions including multi-agent workflows, MCP server implementations, and orchestration patterns

 Implement RAG (Retrieval-Augmented Generation) pipelines using Azure AI Search, Cosmos DB, and vector stores

 Build data pipelines and integrations using Microsoft Fabric, Azure Data Factory, or equivalent services

 Develop NL2SQL, intelligent document processing, and AI-powered automation solutions

 Configure and optimize Cosmos DB collections, indexing strategies, and AI Search indexes for production workloads

 Implement Copilot Studio solutions for applicable customer scenarios

Technical Ownership & Quality

 Own technical delivery of AI projects from development through production deployment

 Select appropriate frameworks, patterns, and tools for implementation

 Design and implement CI/CD pipelines, MLOps workflows, and deployment automation

 Build reusable components and patterns aligned with the AI Harness framework

 Perform model evaluation, optimization, and performance tuning

 Implement security,



governance, and monitoring for deployed AI solutions

 Conduct code reviews and ensure engineering quality standards

Delivery & Collaboration

 Support customer demos, POCs, and proof-of-value engagements

 Participate in sprint planning, technical discussions, and architecture reviews

 Maintain technical documentation including implementation guides, runbooks, and API specifications

 Provide implementation feasibility input during solution design discussions

Required Skills

Core Technical Skills

Programming

Python (advanced), REST API development, async programming

Azure AI Services

Azure OpenAI, Azure AI Search (vector + hybrid), Document Intelligence, Cognitive Services, Azure ML

Generative AI

LLM integration, Prompt Engineering, RAG implementation, Fine-tuning, Embeddings

Agentic AI

Multi-Agent systems, MCP (Model Context Protocol) implementation, Semantic Kernel, LangChain/LangGraph, AutoGen

Data Platforms

Microsoft Fabric (Data Engineering, Pipelines), Azure Data Factory, data transformation

Databases

Cosmos DB (SQL API, vector search), Azure AI Search index design, SQL/NoSQL databases

ML/AI

Machine Learning model development, Deep Learning, NLP, model deployment & serving

DevOps

Git, CI/CD pipelines (Azure DevOps/GitHub Actions), Docker, Kubernetes, MLOps

Engineering Skills

 System-level thinking – ability to design how multiple Azure services work together

 Strong debugging, troubleshooting, and performance optimization

 Experience building production-grade AI applications

 Understanding of distributed systems, scalability patterns, and cloud cost optimization

 API design and microservices architecture

Good to Have

 Copilot Studio development experience

 Power Platform integration (Power Automate, custom connectors)

 AI Harness or similar AI solution frameworks

 Azure Kubernetes Service (AKS) for AI workload deployment

 Application Insights and Azure Monitor

📌 AI Engineer (Ahmedabad)
🏢 atQor
📍 Ahmedabad