AI Engineer – Azure GenAI / Agentic AI

• Role: AI Engineer
  
• Minimum Relevant Experience: 7+ years
  
• Primary Skills: Python, C#, Azure OpenAI, Azure AI Foundry, Azure AI Search, RAG, Agentic AI, REST / GraphQL APIs
  
• Cloud Platform: Azure
  
• Deployment: AKS, App Service, Azure Functions
  
• Location/ Mode/ Budget : Bengalru/ Hybrid/ Open (As per Market Standards)
  
• Contract Duration: 12 months

We are looking for an experienced AI Engineer to design, build, deploy, and support enterprise-grade AI solutions and products. The role requires strong hands-on experience in LLM-powered application development, Azure AI services, RAG architectures, Agentic AI, APIs, cloud deployments, and production support.

The candidate will work in an agile environment with cross-functional teams and will be responsible for delivering secure, scalable, maintainable, and production-ready AI solutions aligned with enterprise quality standards.

• Build full-stack LLM-powered AI applications using Azure technologies.
  
• Implement prompt engineering, grounding, RAG patterns, embeddings, and vector search.
  
• Develop APIs and microservices using Python, .NET / C#, or Node.js.
  
• Integrate AI solutions with user interfaces and enterprise systems.
  
• Develop Agentic AI solutions using Azure AI Foundry and Copilot Studio.
  
• Implement CI/CD pipelines using GitHub Actions or Azure DevOps.
  
• Deploy AI solutions on AKS, Azure App Service, and Azure Functions.
  
• Build data and feature pipelines using Azure Data Factory, Synapse, or Databricks.
  
• Manage prompt versioning, embeddings, model deployments, and production monitoring.
  
• Conduct code reviews, audits, health checks, and quality reviews.
  
• Ensure clean, secure, maintainable, production-level code is delivered.
  
• Follow responsible AI, privacy, and enterprise data security standards.
  

• Strong hands-on experience with:
  • Azure OpenAI
    
  • Azure AI Foundry
    
  • Azure Cognitive Services
    
  • Azure AI Search
    
  • Azure ML
    
  • NLP concepts
    
  • Vector databases / vector indexes
    
• Experience building RAG-based applications.
  
• Experience with Agentic AI development using Azure AI stack.
  
• Strong understanding of prompt design, embeddings, retrieval, grounding, and AI application patterns.
  

• Strong coding experience in:
  • Python
    
  • C#
    
• Experience building REST / GraphQL APIs.
  
• Strong understanding of testing, code reviews, clean code, and coding standards.
  
• Experience with GitHub, branching strategies, linters/formatters, and PEP8.
  

• Experience with GitHub Actions and/or Azure DevOps pipelines.
  
• Hands-on experience with:
  • Docker
    
  • AKS
    
  • Azure App Service
    
  • Azure Functions
    
• Knowledge of:
  • Azure Key Vault
    
  • Managed Identity
    
  • RBAC
    
  • Network security basics
    

• Experience building data or feature pipelines using:
  • Azure Data Factory
    
  • Synapse
    
  • Databricks
    
• Understanding of embeddings, prompt/version management, and production model operations.
  

• GitHub Copilot experience.
  
• Microsoft Copilot Studio / Power Platform experience.
  
• PromptFlow, MLflow, Databricks.
  
• Streamlit or React exposure.
  
• Practical MLOps / LLMOps experience.
  
• Azure certifications such as AI-102 or AZ-204.
  
• Experience with tool/function calling, retrieval caching, and advanced RAG patterns.
  
• Prior experience in asset-heavy enterprise projects will be an advantage.
  

• Strong written and verbal communication.
  
• Ability to explain complex AI and cloud concepts in simple terms.
  
• Experience working in small, empowered, cross-functional virtual teams.
  
• Proactive ownership and strong problem-solving mindset.
  
• Good stakeholder management skills.
  
• Independent analytical thinker with the ability to challenge assumptions and bring creative solutions.
  

The ideal candidate will be a hands-on Azure AI Engineer with 7+ years of relevant experience, strong coding skills in Python and C#, and proven experience building enterprise GenAI applications using Azure OpenAI, Azure AI Foundry, Azure AI Search, RAG, Agentic AI, APIs, CI/CD, Docker, and AKS/App Service/Functions.