Job Description
Lead Azure AI, Security & MCP ArchitectEmployment Type: Full-Time Employment (FTE)

Location:
Bangalore / Pune / Hyderabad Work Model: Work From Office (WFO) Budget: Up to ₹35 LPA, including variable pay (VP)

Experience:
9–10+ Years

Working Hours
3:00 PM – 12:00 AM IST Job SummaryWe are seeking a senior, hands-on Azure Solution Architect with strong expertise in cloud architecture, enterprise security, Generative AI, and Model Context Protocol (MCP). The candidate will lead the design of secure, scalable, production-ready AI applications and agent-based solutions integrated with enterprise platforms.

Key Responsibilities
• Define end-to-end architecture for enterprise AI applications and agent-based solutions.
• Design Azure infrastructure and application-hosting architecture using Azure Container Apps and supporting services.
• Define secure networking using VNets, subnets, peering, private endpoints, private DNS, and controlled ingress and egress.
• Architect authentication and authorization using Microsoft Entra ID, app registrations, managed identities, OAuth flows, RBAC, and service-to-service security.
• Design reusable MCP architecture covering tools, actions, schemas, access boundaries, observability, and error handling.
• Architect secure API integrations with enterprise HR systems, service-management platforms, Microsoft 365, and other enterprise applications.
• Design Generative AI and agentic solutions using Azure AI services.
• Define controls for security, privacy, Responsible AI, monitoring, auditability, retention, and resilience.
• Develop reference architectures, architecture standards, and reusable design patterns.
• Lead options analysis and document technical decisions, risks,



and trade-offs.
• Create architecture diagrams, data flows, security designs, and component inventories.
• Lead solutions through technical architecture reviews, architecture review boards, and security-review processes.
• Review implementation designs and resolve technical blockers with Engineering, Infrastructure, DevOps, and Security teams. Mandatory Skills and Experience
• Minimum 9–10 years of overall technology experience, including strong Azure solution-architecture experience.
• Demonstrable experience designing and delivering Azure solutions in production.
• Strong architectural knowledge of Azure Container Apps, Azure Storage, Azure SQL or PostgreSQL, Key Vault, Azure Monitor, and Application Insights.
• Robust knowledge of Azure networking, including VNets, subnets, peering, private endpoints, private DNS, and Network Security Groups (NSGs).
• Deep understanding of Microsoft Entra ID, OAuth 2.0, OpenID Connect, app registrations, managed identities, and RBAC.
• Strong REST API, integration, and API-orchestration experience.
• Strong understanding of MCP tools, schemas, authentication, and authorization.
• Experience designing Generative AI or agentic solutions using Azure OpenAI or Azure AI Foundry.
• Experience with Infrastructure as Code (IaC) using Bicep or Terraform.
• Knowledge of Azure DevOps, CI/CD,



containerisation, and environment architecture.
• Experience producing and presenting architecture designs through formal review processes.
• Working knowledge of Python/FastAPI or .
NET to prototype, review, and troubleshoot services.
• Strong communication skills and the ability to explain architecture decisions to technical and non-technical stakeholders. Desirable Skills
• Oracle Fusion HCM REST APIs, extracts, or Oracle Integration Cloud experience.
• Experience designing MCP-based integrations with enterprise HR systems or other SaaS platforms.
• ServiceNow and Microsoft Graph API integration experience.
• Exposure to Copilot Studio and Power Platform architecture.
• Experience with Azure AI Search, Retrieval-Augmented Generation (RAG), vector stores, and document-processing solutions.
• Experience designing solutions that process sensitive employee or HR data.
• Exposure to third-party AI-agent platforms such as Lyzr Studio.
• Familiarity with Responsible AI and enterprise AI-governance frameworks.
• Relevant certifications such as AZ-305, AI-102, AZ-500, SC-100, PL-600, or TOGAF. Key Success Outcomes
• Reusable Azure reference architectures for enterprise AI solutions.
• Approved patterns for Container Apps, Entra ID, networking, and private connectivity.
• Secure and reusable MCP and API integration architecture.
• Standards for AI security, monitoring, auditability, and operational support.
• Complete architecture artefacts for technical design reviews and security assessments.
• Reduced technical dependency through reusable standards, workbooks, and architecture assets.

📌 Lead Azure AI, Security (India)
🏢 Helios Systems Asia
📍 India