AI Software Lead: Agent-Driven, Production-Ready

First Student, Inc.

Cincinnati, Northern (OH, KY)

Hybrid

USD 140,000 - 190,000

Full time

14 days+

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Job summary

First Student, Inc. is seeking a Lead to steer agent-driven software delivery, translating business problems into specifications and AI-ready plans.

You will guide AI coding agents, decompose work, review outputs, and ensure production-ready results in React, React Native, and AWS within a safety-governed environment. You will build scaffolding around agent-driven development, establish tests, rules, and review checkpoints, and collaborate with stakeholders to reduce risk and improve delivery

Qualifications

Strong understanding of Product Management, UI/UX concepts, Business Analysis, Analytics and SDLCs.
5+ years of professional software engineering experience, including senior-level code review and architectural judgment.
Demonstrated experience using AI coding agents or AI-assisted development tools to ship production software beyond basic autocomplete or experimentation.
Ability to decompose business problems into clear technical specifications, implementation plans, tests, and review checkpoints.
Strong test-driven development and automated testing practices, including using tests to validate AI-generated or agent-produced code.
Practical experience building or operating LLM-based systems in production, including evaluation, monitoring, and handling non-deterministic behavior.
Experience working in enterprise environments with security, governance, data-handling, and production support constraints.
Strong written and verbal communication skills, including the ability to explain technical tradeoffs to technical and non-technical stakeholders.
Bachelor's degree in Computer Science, Engineering, a related field, or equivalent practical experience.

Responsibilities

Lead agent-driven software delivery by translating problems into specifications and plans.
Direct AI coding agents to design, build, test, and ship applications, workflows, and AI-enabled tools.
Decompose ambiguous requests into agent-executable work and validate outputs meet business and technical requirements.
Run agents in parallel and integrate their output.
Prototype rapidly to gather feedback and inform product direction.
Maintain agent harnesses, project context, architectural rules, and review checkpoints.
Use test-driven practices to constrain agent output and catch drift early.
Ensure automated test coverage across unit, integration, end-to-end, and contract tests.
Review agent-produced code for correctness, security, maintainability, and architectural fit.
Enforce patterns to keep codebases maintainable as AI agents contribute to development.