AI Platform Engineer ILocation: Akron, Ohioh or Dallas, TX (Hybrid)Position SummaryThe AI Platform Engineer is a hands-on individual contributor on the AI Platforms team who writes code to build the AI gateway, reusable AI building blocks, agent tooling, and AI-native SDLC automation on AWS. This work gives platform consumers across the organization a secure, consistent way to build with AI and improves developer productivity through intelligent automation. Working with guidance and code review from senior engineers, the engineer builds practical skills in LLM integrations, agent frameworks, MCP-based tooling, and cloud-native development.
Key Responsibilities1. AI Platform & Agent Framework Development - 40%- Develop reusable AI platform capabilities, AI gateway, agent runtimes, and orchestration services.
- Build APIs, integrations, and developer-facing platform features.
- Support LLM integrations, agent frameworks, and MCP-based tooling.
2. AI-Native SDLC Platform Development - 25%- Develop AI coding agents, testing automation, and SDLC workflows.
- Integrate AI capabilities with development tools, repositories, and CI/CD pipelines.
- Enhance developer productivity through intelligent automation.
3. AWS Cloud & Integration Engineering - 20%- Develop and maintain cloud-native applications and services on AWS.
- Implement serverless components, APIs, and infrastructure integrations.
- Follow cloud security and engineering best practices.
4. Platform Quality & Operations - 10%- Implement automated testing, monitoring, and troubleshooting.
- Support platform deployments, reliability, and performance improvements.
5. Documentation & Collaboration - 5%- Maintain technical documentation and reusable engineering examples.
- Collaborate with senior engineers and platform consumers.
Qualifications- 1-3 years of hands-on software, cloud, or platform engineering experience.
- Hands-on AWS experience, Python and/or TypeScript, APIs, Git, CI/CD, and generative AI fundamentals.
- Basic understanding of AI agents, agent frameworks, and MCP.
- Basic understanding of API authentication, secrets management, and least-privilege access principles (e.g., AWS IAM).
- Familiarity with AI coding agents (e.g., Claude Code, GitHub Copilot, OpenAI Codex, Cursor) in daily development.
- Strong problem-solving and troubleshooting skills, with an eagerness to learn new tools and technologies quickly.
