Agentic AI Solution Architecture

Job Description: Agentic AI QE Architect

Experience: 12 to 15 Years

Location: Hyderabad
Role Type: Individual Contributor / Solution Architect

Role Overview

We are seeking an experienced Agentic AI QE Architect to define architect and lead next-generation AI-powered Quality Engineering transformations for enterprise customers. The role combines expertise in Quality Engineering Test Architecture GenAI Agentic AI LLM orchestration and enterprise platform architecture to drive autonomous intelligent and scalable testing solutions across the SDLC.

The ideal candidate will architect AI-native QE ecosystems build multi-agent frameworks establish governance models and enable customers to achieve accelerated release cycles improved quality and higher engineering productivity.

Key Responsibilities

Agentic AI Solution Architecture

• Architect enterprise-grade Agentic AI platforms for Quality Engineering.
• Design autonomous AI agents across the testing lifecycle:
• Requirements Intelligence
• Test Design Generation
• Test Data Engineering
• Automation Engineering
• Defect Intelligence
• Impact Analysis
• Release Readiness
• Define agent interaction patterns memory frameworks reasoning flows and orchestration models.

Technical Skills

Agentic AI & GenAI

• Multi-Agent Systems
• Autonomous Software Workflows
• LLM Orchestration
• Prompt Engineering
• RAG Architectures
• Vector Databases
• Knowledge Graphs
• AI Evaluation Frameworks

AI Technologies

• OpenAI / Azure OpenAI
• Anthropic Claude
• Gemini
• LangChain
• LangGraph
• Semantic Kernel
• AutoGen
• CrewAI
• Hugging Face

Must Have

• 12-15 years of experience in Quality Engineering and Test Architecture.
• Minimum 3 years in AI/GenAI-based solution architecture.
• Proven experience designing enterprise-scale automation and QE platforms.
• Hands-on experience building AI agents and orchestration workflows.
• Experience implementing RAG and LLM-based enterprise solutions.
• Strong stakeholder management and consulting skills.

Preferred

• Experience with AI Foundry Bedrock Vertex AI or similar enterprise AI platforms.
• Exposure to MCP Agent-to-Agent frameworks and AI governance models.
• Relevant certifications in Azure AI AWS AI/ML Google AI or enterprise architecture.

Success Metrics

• Reduction in test design and execution effort through AI automation.
• Increase in test asset reuse and self-healing automation coverage.
• Improvement in release readiness and defect prediction accuracy.
• Adoption and scale of Agentic AI solutions across customer portfolios.
• Measurable productivity gains and quality improvements delivered through AI-led QE transformation.