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High — generalist senior fullstack role with mid-level experience in a metro market increases competition.
Medium — core fullstack skills are transferable, but private AI integrations add moderate domain specificity.
Medium — explicit minimum experience and senior ownership expectations, but flexible on exact tech stack.
Own significant parts of the application layer for AI products including designing and building frontend/backend systems, APIs, data models, and integrations with AI inference services.
Make architecture and technology decisions focusing on scalability, reliability, security, and maintainability, and troubleshoot complex multi-layer production issues.
Lead and mentor engineers and interns, improving engineering quality, and take ownership of production systems from design through release and operation.
At least 3 years of hands-on full-stack software development experience with production frontend and backend applications.
Strong understanding and experience with backend systems, APIs, databases, modern application architecture, and debugging multi-layer systems.
Experience making technical design decisions and practical trade-offs with clear communication skills.
Work Experience Required: Minimum 3 years as specified in the JD. Other strict mandatory requirements like degree or location: Not explicitly mentioned in the JD.
Experienced in both frontend and backend technologies, comfortable making ambiguous product or technical problems into clear implementation plans.
Strong technical judgment with ability to evaluate AI-assisted code/tools critically and take ownership beyond coding, improving system design and mentoring others.
Skilled at working closely with AI engineering teams to build reliable application layers interfacing with AI inference and evaluation systems.