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Metro location and broad full-stack plus GenAI skillset increase candidate competition.
Enterprise SaaS, multi-tenant and GenAI experience preferred, though leadership engineering skills remain transferable.
Mandatory 15+ years, 5+ leadership, and specific full-stack plus GenAI/cloud expertise narrow the candidate pool.
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Lead strategic and technical direction for 30+ engineers across multiple Java Full Stack teams focused on scalable, resilient, cloud-native, AI-enabled supply chain SaaS platforms.
Drive architecture vision and delivery of Generative AI integrations including intelligent recommendations, conversational interfaces, and AI model lifecycle management (LLMOps).
Establish engineering KPIs around AI adoption, productivity, and model performance, and oversee AI governance, data privacy, and responsible AI practices.
15+ years software engineering experience with 5+ years in leadership roles.
5+ years working with microservices and cloud-native architectures, strong full stack (Java Spring Boot, React) development skills.
Experience leading large global/distributed engineering teams and delivering enterprise SaaS products at scale.
Not explicitly mentioned: any mandatory educational degree; certifications in Cloud or DevOps are nice-to-have but not mandatory.
Experienced leader capable of driving AI-first full stack engineering across Java, React, microservices, and GenAI technologies in supply chain domain.
Demonstrates both strategic vision and hands-on technical expertise required to embed AI/ML into SaaS platforms and lead large engineering organizations.
Comfortable working cross-functionally with Product, Data Science, and Architecture to implement AI-enabled features and scalable cloud solutions.