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Signet Jewelers is the world's largest retailer of diamond jewelry, operating more than 2,800 stores worldwide under the iconic brands: Kay Jewelers, Zales, Jared, H.Samuel, Ernest Jones, Peoples, Banter by Piercing Pagoda, Rocksbox, JamesAllen.com and Diamonds Direct. We are a people-first company and this core value is at the heart of everything we do, from empowering our valued team members, to collaborating with our customers, to fostering the communities in which we live and serve. People – and the love their actions inspire – are what drive us. We’re not only proud of the love we inspire outside our walls, we’re especially proud of the diversity, inclusion and equity we’re inspiring inside. There are dynamic career paths awaiting you – rewarding opportunities to impact the lives of others and inspire love. Join us!

AI Platform Engineer I

Location: Akron, Ohioh or Dallas, TX (Hybrid)

Position Summary

The 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 Responsibilities

1. 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.