Job
Description
Job Summary We are looking for a highly skilled Solutions Architect or Engineering Lead to join our team for a critical client-facing role. The ideal candidate will have extensive hands-on experience with Azure, production-level deployment workflows, and Generative AI systems. This role includes representing our company to the client’s Architecture Review Board, AI Council, and other senior stakeholders, making strong communication and documentation skills essential. Job Responsibilities: Design and implement scalable Azure architectures for enterprise-level applications Lead deployment and infrastructure planning for production environments Represent the company in client meetings, architecture reviews, and AI-related discussions Develop and maintain system design documentation (HLD, LLD, architecture diagrams) Collaborate with cross-functional teams including backend, frontend, AI/ML engineers Ensure solutions meet compliance, performance, and security standards Required Skills and Experience: 1. Azure Architecture Expertise: Proficient with Azure Kubernetes Service (AKS), Azure App Services, Azure Container Apps & Jobs Experience with Azure Redis Cache for caching or messaging Skilled in using Azure Storage (Blob/File) and Azure Files Familiarity with Azure Cosmos DB Understanding of Azure Virtual Networks, Subnets, and Private Endpoints Experience managing secrets and certificates with Azure Key Vault Hands-on with Azure Monitor and Application Insights Familiarity with Azure AI Services like Azure OpenAI and AI Search 2. DevOps & Deployment: Hands-on experience with CI/CD using Azure DevOps or GitHub Actions Proficiency in Docker and Docker Compose for containerization Working knowledge of Kubernetes orchestration and deployment strategies Familiarity with blue-green and rolling deployment techniques Experience with observability tools: centralized logging, tracing, and alerting 3. Generative AI System Design: Experience with Retrieval-Augmented Generation (RAG) architecture Familiarity with embedding databases such as Azure AI Search, PG_VECTOR, FAISS Knowledge of agent-based architectures (LangChain/LangGraph) Understanding of streaming outputs and session memory in LLMs Skills in cost optimization and performance tuning for LLM workflows 4. Job Processing & Backend Integration: Familiarity with job processing frameworks like Azure Container App Jobs or Celery Understanding of message brokers like Redis, RabbitMQ, Azure Cache Ability to design asynchronous, decoupled workflows using queues/tasks 5. Security & Compliance: Knowledge of RBAC, JWT, and API security best practices Familiarity with network isolation, encryption standards, and secure API gateways Understanding of compliance requirements for sensitive/regulated data (e.g., healthcare content) 6. Soft Skills & Collaboration: Strong written communication and documentation skills Experience in creating High-Level Design (HLD) and Low-Level Design (LLD) Proven ability to collaborate with backend, frontend, and AI/ML teams Show more Show less
