AI Architect

Strong AI Leader for Agentic SDLC Transformation (Large Retail Client) Profile Summary

A seasoned Engineering Leader/Architect with 15+ years of experience in enterprise software delivery, AI engineering, and digital transformation, capable of leading the adoption of Agentic SDLC across a large retail organization. The individual should combine deep technical expertise with strong stakeholder management skills and a proven track record of delivering large-scale technology programs.

Key Responsibilities

• Lead end-to-end Agentic Software Development Lifecycle (SDLC) implementation, integrating AI agents across requirements, design, development, testing, deployment, and operations.
• Building and governing AI-powered developer productivity solutions at enterprise scale.
• Define engineering standards, guardrails, governance, security, and responsible AI practices. Agentic SDLC Strategy & Transformation
• Define and lead the enterprise roadmap for Agentic SDLC adoption.
• Implement AI-assisted workflows across requirements, design, coding, testing, security, deployment, and operations.
• Drive engineering productivity improvements through AI-powered development platforms and tools.
• Establish best practices, governance frameworks, and operating models for AI-driven engineering.
• Define engineering standards, quality metrics, and delivery excellence frameworks.
• Design solutions utilizing LLMs, RAG architectures, autonomous agents, and AI orchestration platforms.
• Establish responsible AI practices, guardrails, and compliance mechanisms.
• Client & Stakeholder Management
• Support business capabilities across various spectrum of Retail Industry like Digital Commerce, Omnichannel Retail, Supply Chain & Logistics etc.

Mandatory Technical Stack

• Cloud-native architectures (Azure/AWS/Google Cloud Platform)
• Microservices and API ecosystems
• DevSecOps and CI/CD
• Platform Engineering
• SRE and Observability
• Experience in GenAI, Agentic AI frameworks, LLMs, RAG architectures, and AI-assisted engineering platforms.

Preferred Technical Stack

• Python, Java, .NET, TypeScript
• Azure OpenAI / OpenAI / Anthropic ecosystems
• LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI or similar agent frameworks
• GitHub Copilot, Azure DevOps, GitHub Actions
• Kubernetes, Docker, Terraform
• Vector databases and knowledge platforms