AI Engineer / Technical Consultant – AI Integration

AI Engineer / Technical Consultant – AI Integration

Summary

Responsibilities

• Architect and develop enterprise-grade AI solutions utilizing Python, Azure Functions, Logic Apps, and Event Grid to automate complex workflows.
  
• Establish and maintain robust DevOps pipelines using GitHub Actions and Azure DevOps to ensure efficient Continuous Integration and Continuous Deployment (CI/CD).
  
• Implement comprehensive security frameworks including Role-Based Access Control (RBAC), Entra ID integration, and Key Vault management to protect sensitive data and resources.
  
• Design and refine prompt engineering strategies, oversee Model Context Protocol (MCP) implementation, and enforce Responsible AI guidelines with continuous monitoring mechanisms.
  
• Define and govern enterprise architecture standards, ensuring alignment with organizational goals and regulatory compliance.
  
• Engineer scalable data solutions using Azure Databricks, SQL, Azure Data Factory (ADF), and Azure Data Lake Storage (ADLS) for advanced data modeling and processing.
  
• Develop Retrieval-Augmented Generation (RAG) systems and Agentic AI applications using Azure OpenAI to deliver intelligent, context-aware user experiences.
  
• Build and manage secure REST APIs via API Management (APIM) to facilitate seamless cloud-native integration across diverse enterprise systems.
  

• Experience: 6-8 years of professional experience in AI engineering, technical consulting, or related cloud-native development roles.
  
• Programming & Automation: Proficiency in Python with extensive hands-on experience in Azure Functions, Logic Apps, and Event Grid.
  
• DevOps Expertise: Demonstrated ability to configure and manage CI/CD pipelines using GitHub Actions and Azure DevOps.
  
• Security Knowledge: Strong background in implementing security controls, including RBAC, Entra ID, and Key Vault configurations.
  
• AI & ML Skills: Expertise in prompt engineering, MCP, Responsible AI principles, and AI monitoring tools.
  
• Architecture & Governance: Proven track record in enterprise architecture design and governance frameworks.
  
• Data Engineering: Advanced skills in Azure Databricks, SQL, ADF, ADLS, and data modeling techniques.
  
• Generative AI: Experience in building RAG pipelines and Agentic AI solutions using Azure OpenAI.
  
• Integration: Competence in developing REST APIs and managing them through APIM for cloud-native integration.
  
• Salary Expectation: The role offers a competitive compensation package of ₹20 LPA.