We are seeking a hands-on AI Solution Architect to lead feature-level execution within our Agentic Software Development Lifecycle (SDLC).
This role uniquely blends Product Ownership and Solution Architecture, ensuring seamless collaboration between AI agents and engineering teams. You will orchestrate daily agent workflows, refine prompts, manage technical dependencies, and validate AI-generated outputs before production release.
You are accountable for transforming strategic intent into shipped, production-ready AI-assisted features.
🎯 Key Responsibilities
1️⃣ Agentic Workflow Orchestration
* Drive daily execution of Agentic flows across Inception, Construction, and Production phases
* Coordinate AI agents to ensure structured, high-quality handoffs
* Configure, test, and continuously refine prompts and tools
* Identify friction points and optimize multi-agent collaboration
2️⃣ Feature Ownership
* Translate roadmap initiatives into structured, feature-level requirements
* Own and prioritize the domain backlog
* Define acceptance criteria for AI-generated deliverables
* Review and validate AI-generated refactoring plans and feature packages
3️⃣ Agile Delivery Leadership
* Facilitate sprint planning, stand-ups, reviews, and retrospectives
* Manage cross-functional dependencies
* Monitor milestones and ensure production readiness
* Lead gate reviews and feature demos prior to release
4️⃣ Human-in-the-Loop Governance
* Serve as the final reviewer of critical AI outputs
* Enforce architectural, security, and quality standards
* Escalate integration risks in brownfield and legacy environments
✅ Required Experience
Essential
* Proven experience as AI Solution Architect, Technical Product Owner, or similar hybrid role
* Experience working with LLM-based agents or AI-assisted development environments
* Strong understanding of Agile and end-to-end SDLC execution
* Ability to structure prompts and critically validate AI-generated results
Strong Technical Plus
* Ability to read and write code (Java, Python, scripting preferred)
* Experience troubleshooting AI-generated outputs during development
* Understanding of CI/CD pipelines and observability tooling