Career-Path Engine: Adaptive Development Plan & Upskilling Analyzer
Adaptive Development Plan & Upskilling Analyzer
¶ 01Context & Design Rationale
“A reliable system is designed not around hypothetical optimal conditions, but around deterministic resilience under resource pressure.”
Three-tier career guidance system. A Python ML backend deployed on Vertex AI clusters user assessment data into career profiles. A Flask orchestration service on Google Cloud Run combines those clusters with Google Gemini API responses to produce personalised development roadmaps and career guidance. A React/Vite frontend handles user assessment input and conversational chat with the guidance engine. Engineered with strict architectural boundaries, deterministic memory models, and zero extraneous runtime dependencies.
¶ 02Architectural Pipeline
SUBSYSTEM RUNTIMEINGESTION PHASE
Protocol Parser
Zero-Copy Frame
→
TRANSFORMATION
Core Logic Unit
Deterministic Arena
→
PERSISTENCE
Storage / State Layer
Atomic Append