Role Overview:
You will serve as the Technical Analyst within an AI-led SDLC programme, supporting the migration of applications from AWS cloud-native environments to Microsoft Azure. You will also review and refine AI-generated artefacts such as user stories, acceptance criteria, and backlog items, ensuring they accurately represent the intended system behaviour and align with the programme’s migration objectives. Working closely with Solution Architects, Pod Leads, and AI Orchestration teams, you will ensure that the requirements and functional context required for migration are complete, validated, and ready for execution by the agentic engineering pipeline.
Key Responsibilities:
Requirements Discovery & SME Collaboration
Engage with domain SMEs, product owners, and operational stakeholders to gather requirements that are not present within the application code or infrastructure definitions.
Document business rules, workflows, system behaviours, and operational constraints required to support the migration.
Identify and capture implicit or undocumented functionality that must be preserved during migration.
AI-Generated Backlog Validation
Review user stories, tasks, and acceptance criteria generated by Agentic AI pipelines.
Validate AI-generated artefacts against Business intent
SME input
Refine and restructure stories to ensure they are clear, testable, and migration-ready.
Functional Context EnrichmentProvide contextual inputs that improve AI-driven code and migration analysis, including:
Business workflows
Integration dependencies
Data flows
Operational procedures
Ensure migration work packages contain sufficient functional and operational detail for engineering pods.
Backlog Structuring for AI-led SDLC
Validated and refined user stories and acceptance criteria
Documented business rules and functional behaviours
Migration functional mapping documentationSME knowledge capture artefactsStructured backlog items ready for AI-led implementation