Senior AI Engineer, AI Enablement

GameChanger Remote - USfull timeRemote

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senior

$140k–$155k

H1B: no

Gamechanger Senior AI Engineer at GameChanger builds AI-powered developer tooling and workflows to accelerate software development. The role includes designing, deploying, and operating AI tooling and infrastructure to improve engineering productivity and software quality.

Responsibilities

Identify high-impact opportunities to improve software development with AI, partnering with engineering teams to understand their workflows and shape practical solutions.
Independently design, build, deploy, and operate production-grade AI tooling and agentic workflows, owning projects from discovery and technical design through rollout and iteration.
Develop AI-assisted engineering workflows, including code review, testing and validation, issue and crash triage, and development automation.
Build and evolve shared AI infrastructure that supports model access, vendor integrations, usage observability, and cost controls.
Create evaluation frameworks, monitoring, and feedback loops to measure reliability, adoption, and impact on engineering productivity and software quality.
Develop reusable skills, plugins, integrations, and engineering patterns that support teams across backend, web, iOS, and Android.
Drive adoption through hands-on partnership, documentation, training, and ongoing feedback, helping teams integrate AI into their everyday work.
Partner with Security, Platform, Quality Engineering, Product, and Design to establish appropriate guardrails, support codebase modernization, and evaluate when to build, buy, or adapt emerging AI capabilities.

Qualification

Have personally builtBring practical depth in LLMs

Required

Have 5+ years of software engineering experience, with 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, with experience improving them after launch.
Bring practical depth in LLMs, tool use, agentic workflows, retrieval, and evaluations, along with experience incorporating AI into your own software development workflow.
Can turn ambiguous problems into useful solutions: you identify opportunities, make sound technical tradeoffs, and drive work independently from concept through adoption.
Communicate clearly and work effectively across teams, translating user needs into technical solutions and helping others adopt new tools and practices. Experience in developer tooling, developer experience, or platform enablement is a plus.
Can measure the quality and impact of AI systems through evaluations, observability, usage, feedback, and productivity outcomes. You’re comfortable learning across technology stacks and partnering with web and mobile engineers; direct iOS or Android experience is a plus.