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Metro-based, mid-level generalist fullstack role attracts many qualified applicants.
Fullstack application skills and common stack enable easy cross-industry transfer.
Explicit 3+ years requirement but flexible tech stack makes filters moderately strict.
Own significant parts of the application layer for AI products, including design, architecture, and delivery of production frontend and backend systems.
Make major architecture and technology decisions focused on scalability, reliability, security, and maintainability, while integrating AI inference services and related AI capabilities.
Lead and guide other engineers through code reviews, technical decisions, debugging complex issues, and overall system ownership from design through production.
At least 3 years of hands-on full-stack software development experience with production applications covering frontend and backend.
Strong engineering fundamentals with experience designing APIs, data models, backend systems, and modern application architecture.
Proficiency in TypeScript, Node.js, React, Next.js, databases, cloud infrastructure, or similar tech stacks (experience with these is useful but not strictly mandatory).
Work Experience Required: Minimum 3 years of relevant full-stack software engineering experience.
Experienced engineer comfortable making design decisions in ambiguous environments and balancing trade-offs between technical constraints and product needs.
Demonstrates strong technical judgment, ownership of systems beyond code contribution, and ability to improve team engineering quality through mentorship and guidance.
Skilled in collaborative cross-functional work between AI engineering and application layers, with a focus on building scalable, maintainable production systems involving AI integrations.