Sr.Automation tester / Automation Lead

As an AI Platform Architect, you will spearhead the design and implementation of an enterprise-scale AI Agentic Platform that enables Quality Engineering and modern Software Delivery. This position is responsible for end-to-end technical architecture, developing engineering standards, and mentoring the AI Platform Engineering team. You will collaborate closely with Enterprise Architecture, Cloud Engineering, Security, DevOps, Application Teams, and Quality Engineering to create a scalable, secure, and reusable AI platform designed to serve hundreds of enterprise applications. Required Qualifications

• 12+ years in software engineering or platform engineering.
• 5+ years designing enterprise cloud-native platforms.
• 3+ years with Generative AI, LLMs, or AI agent frameworks.
• Expert-level Python development.
• Strong experience with Kubernetes, Docker, APIs, microservices, and cloud platforms (AWS/Azure).
• Hands-on experience with RAG, vector databases, MCP, prompt engineering, and agent orchestration.         
• Define the vision and roadmap for the Enterprise AI Platform.
• Design a scalable multi-agent architecture supporting SDLC and Quality Engineering use cases.
• Establish standards for AI agent development, orchestration, prompt engineering, and governance.
• Evaluate emerging AI technologies, LLMs, and agent frameworks.
• Design agent orchestration using frameworks such as LangGraph, Semantic Kernel, or similar.
• Define the Model Context Protocol (MCP) architecture and enterprise connector framework.
• Design RAG, vector database, knowledge graph, memory, and context management strategies.
• Build reusable SDKs, APIs, templates, and reference implementations.
• Define integration patterns for Jira, Azure DevOps, GitHub, Confluence, ServiceNow, cloud platforms, and enterprise APIs. • Establish event-driven communication patterns and secure authentication mechanisms.