AI Solutions Architect

• Lead the architecture, design, and development of enterprise-scale web applications with integrated Generative AI capabilities.
• Define technical standards, architectural patterns, and best practices for scalable and secure software systems.
• Collaborate with product, AI/ML, Dev Ops, and security teams to ensure alignment between business goals and technical execution.
• Oversee full-stack development lifecycle, ensuring robust design, performance tuning, and security compliance.
• Evaluate and integrate AI components such as LLMs, embedding services, and vector databases into product architecture.

• Cloud-Native Architecture & Microservices
• Proven experience designing scalable, cloud-native applications using microservices and event-driven patterns on Azure Ecosystem.
• Performance Optimization

Implementing caching strategies (Redis, CDN), asynchronous job processing (RabbitMQ, Kafka), and load-balanced architectures using Kubernetes or serverless platforms.

• GenAI Integration & LLM Orchestration
• Hands-on with Generative AI technologies—Azure OpenAI, prompt engineering, RAG pipelines, embeddings, and vector search (e.g., Azure AI search, Azure PostgreSQL etc..).
• Strong expertise in REST APIs with versioning, throttling, and gateway integrations., PostgreSQL/MongoDB, OAuth2/SSO, and secure coding aligned with GDPR/SOC2 standards.
• Frontend Development (React/Next.js)
• Deep experience building enterprise-grade UIs using React.
  
  JS, component libraries, and modern design systems.
• Dev Ops & Infrastructure as Code
• Proficiency in Azure CI/CD pipelines , Docker, and Kubernetes for automated, scalable deployments.
• Real-Time & Scalable UI Patterns
• Experience with Web Sockets/SSE, UI performance optimization, and handling large-scale dynamic frontends.

Competence in automated unit/E2E testing , frontend performance profiling, and monitoring of Deployed solutions