Senior AI Engineer, AI Enablement
G
GameChangerAI developer tooling
GameChanger Remote - US; Work remotely throughout the US or from our office in Manhattan, NY.Full-TimeSenior
SalaryThe target salary range for this position is between $140,000 and $155,000. This is part of a total compensation package that includes incentive, equity, and benefits for eligible roles.
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Job Details
- Experience
- 5+ years of software engineering experience
- Required Skills
- Full Stack Development
Requirements
- Have 5+ years of software engineering experience.
- Bring strong backend and full-stack fundamentals and experience designing and operating complex production systems.
- Have personally built, deployed, and supported AI-powered systems or agentic workflows used by teams in a professional environment.
- Have experience improving AI systems or workflows after launch.
- Bring practical depth in LLMs, tool use, agentic workflows, retrieval, and evaluations.
- Have experience incorporating AI into your own software development workflow.
- Be able to turn ambiguous problems into solutions and drive work independently from concept through adoption.
- Be able to communicate clearly and work across teams to translate user needs into technical solutions and help others adopt tools and practices.
- Be able to measure AI system quality and impact through evaluations, observability, usage, feedback, and productivity outcomes.
- Be comfortable learning across technology stacks and partnering with web and mobile engineers.
- Experience in developer tooling, developer experience, or platform enablement is a plus; direct iOS or Android experience is also a plus.
Responsibilities
- Identify high-impact opportunities to improve software development with AI in partnership with engineering teams.
- Design, build, deploy, and operate production-grade AI tooling and agentic workflows from discovery through rollout and iteration.
- Develop AI-assisted workflows for code review, testing and validation, issue and crash triage, and development automation.
- Build and evolve shared AI infrastructure for model access, vendor integrations, usage observability, and cost controls.
- Create evaluation frameworks, monitoring, and feedback loops to measure reliability, adoption, and impact.
- Develop reusable skills, plugins, integrations, and engineering patterns for backend, web, iOS, and Android teams.
- Drive adoption through hands-on partnership, documentation, training, and feedback.
- Partner with Security, Platform, Quality Engineering, Product, and Design on guardrails, codebase modernization, and AI capabilities.
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