Solution Architect

Overview

We are seeking a highly skilled Azure Architect with expertise in designing and deploying production-ready Generative AI workflows. This is a client-facing role where the candidate will be instrumental in obtaining approvals from client architecture governance bodies such as the Architecture Review Board and AI Council. The ideal candidate will have deep technical expertise in the Azure ecosystem, solid understanding of DevOps practices, and hands-on experience with Generative AI systems.

Job Description

Responsibilities:

  • Design, develop, and deploy scalable and secure solutions on Azure.

  • Represent the company in architecture discussions with client stakeholders.

  • Prepare and present documentation for Architecture Review Board and AI Council.

  • Lead the implementation of Generative AI solutions using Azure AI services.

  • Set up and manage CI/CD pipelines and production deployments.

  • Ensure compliance with security and regulatory requirements.

  • Collaborate with cross-functional teams including backend, frontend, and AI/ML teams.

  • Produce clear and comprehensive system documentation including HLDs and LLDs.

Skills Required:

Azure Architecture Expertise (Mandatory):

  • Azure Kubernetes Service (AKS), Azure App Services, Azure Container Apps, Container App Jobs

  • Azure Redis Cache for caching and message brokering

  • Azure Storage (Blob/File), Azure Files

  • Azure Cosmos DB familiarity

  • Azure Virtual Networks, Subnets, Private Endpoints

  • Azure Key Vault for secrets and certificate management

  • Azure Monitor and Application Insights for logging and tracing

  • Azure AI Services such as Azure OpenAI and AI Search

DevOps & Deployment:

  • Experience with Azure DevOps, GitHub Actions, or similar CI/CD tools

  • Docker, Docker Compose, Kubernetes orchestration

  • Blue-green and rolling deployment strategies

  • Observability tools: logging, tracing, and alerting with Azure Monitor and Application Insights

Generative AI System Design:

  • Understanding of RAG (Retrieval-Augmented Generation) patterns

  • Experience with embedding databases like Azure AI Search, PG_VECTOR, or FAISS

  • Familiarity with agent-based architectures (LangChain/LangGraph)

  • Knowledge of session management, streaming outputs, latency control, and token usage

Job Processing & Backend Integration:

  • Azure Container App Jobs or Celery for background processing

  • Message brokers like Redis, RabbitMQ, Azure Cache

  • Design of asynchronous pipelines using queues and tasks

Security & Compliance:

  • API security best practices, RBAC, JWT

  • Network isolation, encryption, and secure gateways

  • Awareness of compliance needs for regulated domains such as healthcare

Soft Skills & Team Collaboration:

 

  • Strong system design documentation and diagramming skills

  • Experience with HLD and LLD documentation

  • Proven ability to collaborate with cross-functional technical teams

Skills & Requirements

Azure Kubernetes Service (AKS), Azure App Services, Azure Container Apps, Container App Jobs, Azure Redis Cache, Azure Storage (Blob/File), Azure Files, Azure Cosmos DB, Azure Virtual Network, Subnets, Private Endpoints, Azure Key Vault, Azure Monitor, Application Insights, Azure OpenAI, Azure AI Search, Azure DevOps, GitHub Actions, Docker, Docker Compose, Kubernetes orchestration, blue-green deployment, rolling deployment, RAG (Retrieval-Augmented Generation), Azure AI Search, PG\_VECTOR, FAISS, LangChain, LangGraph, streaming outputs, Session persistence, Azure Container App Jobs, Celery, Redis, RabbitMQ, RBAC, JWT, API security, Network isolation, Encryption, Secure API gateways, HLD, LLD, System design documentation, Cross-functional team collaboration.

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