AI Software Lead

First Student • Cincinnati, OH

2d

About The Position

This role is for an AI Software Lead at First Student, a company focused on student transportation. The position is part of the company's investment in AI and involves building practical, reliable, and governed AI-enabled capabilities. This is not a traditional software engineering role; the 'Lead' title does not imply people management. The primary responsibility is to lead agent-driven software delivery, which includes deciding what to build, decomposing work for AI coding agents, supervising their output, validating quality, and owning the final product. Success will be measured by the ability to direct AI coding agents effectively, create supporting structures for their work, review their output with senior-level judgment, and ensure the software is reliable, maintainable, and production-ready. When the solution involves an AI agent (e.g., routing assistant, dispatcher copilot, parent communications agent), the role includes designing, building, evaluating, and operating it in production. The work will focus on net-new tools and agents, with some involvement in existing systems. The standard technology stack includes React, React Native, and AWS. Given the potential involvement with student data, FERPA and enterprise governance are important considerations. The role is part of a small AI pod, contributing to the development of AI governance and delivery practices.

Requirements

• 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.

Nice To Haves

• Direct experience building in React, React Native, and AWS.
• Experience with Product Management, UI/UX, Business Analysis, Analytics and SDLCs
• Experience with AWS services relevant to AI workloads, such as Bedrock, Lambda, ECS/Fargate, API Gateway, S3, DynamoDB, RDS, or Step Functions.
• Experience with agent frameworks, RAG, vector databases, embeddings, context engineering, tool use, or function-calling patterns.
• Experience with LLM observability, evaluation, structured outputs, prompt optimization, guardrails, or deterministic-output patterns.
• Experience with advanced testing practices such as contract testing, property-based testing, or mutation testing.
• Experience with Snowflake, Power BI, geospatial, routing, logistics, transportation, or operations-focused software.
• Experience applying AI within governed enterprise environments, including FERPA-relevant or similarly regulated data.
• Relevant AWS, AI, cloud, or data certifications.

Responsibilities

• Lead agent-driven software delivery
• Translate business problems into clear specifications, constraints, and implementation plans for AI coding agents.
• 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 that outputs meet business and technical requirements.
• Run agents in parallel where useful; review, reconcile, and integrate their output.
• Prototype rapidly to gather feedback and inform product direction.
• Design and maintain agent harnesses, including project context, architectural rules, file conventions, allowed dependencies, and review checkpoints.
• Use test-driven practices to constrain agent output and catch drift early.
• Ensure appropriate automated test coverage across unit, integration, end-to-end, and contract tests based on risk.
• Review agent-produced code for correctness, security, maintainability, and architectural fit.
• Enforce patterns that keep codebases maintainable as AI agents contribute to development.
• Build solutions using design systems, tool use, APIs, function calling, RAG, DAG, MCP, context engineering, harness engineering and multi-agent workflows where appropriate.
• Evaluate models and AI tools across providers based on cost, quality, latency, reliability, security, and fit for purpose.
• Implement evals, monitoring, logging, and guardrails so AI systems are measurable and supportable.
• Design for reliable and repeatable outputs where the business requires consistency.
• Communicate technical concepts, tradeoffs, risks, and recommendations clearly to technical and non-technical stakeholders.
• Partner with architecture, security, and AI governance to align solutions with enterprise standards.

Benefits

• Consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior