Descripción de la oferta
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
