Job description

Serving the needs of all families with young children, Carter’s Inc. is the largest North American apparel retailer exclusively for babies and young children, encompassing Carter’s, OshKosh B’gosh, Skip*Hop and Little Planet brands. Meaningful work, constant learning, genuine people, and a community guided by core values that promote inclusion and innovation is in everything we do. There are many reasons to build your career at Carter s. HOW YOU’LL MAKE AN IMPACT: This is a hands-on build role within the AI Center of Excellence (CoE). The AI Developer provides dedicated build capacity for prioritized use cases: directed by the Tech & Platform Lead, they build, test, and iterate enterprise AI solutions — apps, micro-apps, AI platforms, and integrations — for business units across merchandising, supply chain, finance, stores, and digital. All work is delivered to CoE engineering standards, and reusable components are documented and handed over so the rest of the CoE and its developer community can build on them. Success in this role is measured by building quality and delivery of velocity. Two positions are open. Build & Deliver AI Solutions (60%) Serve as the hands-on builder for enterprise-supported AI solutions coming out of the use-case intake funnel — apps, micro-apps, AI platform capabilities, and integrations. Build and ship agentic workflows and Claude/LLM-based tools — skills, connectors, and automations against systems such as Tableau, Redshift, Jira, and Outlook. Prototype the use cases the Solutions Manager has prioritized, then harden successful pilots into supported production solutions. Build, test, and iterate on the CoE’s approved platforms, connectors, and reusable components, meeting CoE engineering standards for code quality, review, and release. Document and hand over reusable components, patterns, and integrations to the shared platform library so other developers can reuse them. Work within the architecture, security, and platform standards set by the Tech & Platform Lead and the Integration/DE Manager — building on approved connectors, governed data sources, and the enterprise AI policy owned by Security, not one-off shadow tools. Apply the enterprise AI policy and risk tiring to everything built, partnering with the AI Security Manager on higher-tier use cases. Quality, Documentation & Handover (25%) Work from the Tech & Platform Lead’s direction and priorities, breaking assigned use cases into buildable scope and delivering against agreed timelines. Write the technical documentation, setup notes, and usage guidance that make each build maintainable and transferable to other developers. Partner with business-unit stakeholders and AI champions to validate requirements, test builds, and iterate feedback before release. Measurement & Operations (15%) Instrument adoption, hours saved, and business impact for every release, and track build quality and delivery velocity, feeding the CoE’s quarterly value reporting. Support and iterate on shipped solutions, keeping them reliable in production. Prepare documentation and user aids suitable to end user needs; contribute to the CoE’s shared prompt and pattern library. Provide handover walkthroughs and technical support to other developers, super users, and champions appropriate to the business needs. WE’D LOVE TO HEAR FROM YOU IF: Must have: Software Development — 1-3 years of experience (internships and co-ops count) with working proficiency in Python and/or TypeScript Experience with vector databases, embeddings, or LLM evaluation frameworks. Cloud platform experience (Azure, AWS, or GCP). LLM Application Development — Hands-on experience with LLM APIs prompting, function/tool calling, retrieval-augmented generation, or agent frameworks — through work, side projects, or coursework APIs & Integration — REST, webhooks, auth, and the ability to read and apply other systems’ documentation SQL & Data Fluency — Working SQL and enough data fluency to wrangle the inputs an AI solution needs Engineering Fundamentals — Git, code review, CI/CD, and writing code someone else can maintain Communication — Ability to work beside non-technical business partners every day and earn their trust Preferred skills and experience: Retail, supply chain, or consumer-products domain exposure. Contributions to internal tools, hackathons, or an AI champions/super-user community. Carters is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, genetics, disability, age, veteran status, or any other status protected by federal, state, or local law.

Requirements

Must-haves

Build & Deliver AI Solutions (60%)
Serve as the hands-on builder for enterprise-supported AI solutions coming out of the use-case intake funnel — apps, micro-apps, AI platform capabilities, and integrations.
Build and ship agentic workflows and Claude/LLM-based tools — skills, connectors, and automations against systems such as Tableau, Redshift, Jira, and Outlook.
Prototype the use cases the Solutions Manager has prioritized, then harden successful pilots into supported production solutions.
Build, test, and iterate on the CoE’s approved platforms, connectors, and reusable components, meeting CoE engineering standards for code quality, review, and release.
Document and hand over reusable components, patterns, and integrations to the shared platform library so other developers can reuse them.
Apply the enterprise AI policy and risk tiring to everything built, partnering with the AI Security Manager on higher-tier use cases.
Quality, Documentation & Handover (25%)
Work from the Tech & Platform Lead’s direction and priorities, breaking assigned use cases into buildable scope and delivering against agreed timelines.
Write the technical documentation, setup notes, and usage guidance that make each build maintainable and transferable to other developers.
Partner with business-unit stakeholders and AI champions to validate requirements, test builds, and iterate feedback before release.
Measurement & Operations (15%)
Instrument adoption, hours saved, and business impact for every release, and track build quality and delivery velocity, feeding the CoE’s quarterly value reporting.
Support and iterate on shipped solutions, keeping them reliable in production.
Prepare documentation and user aids suitable to end user needs; contribute to the CoE’s shared prompt and pattern library.
Provide handover walkthroughs and technical support to other developers, super users, and champions appropriate to the business needs.
Software Development — 1-3 years of experience (internships and co-ops count) with working proficiency in Python and/or TypeScript
Experience with vector databases, embeddings, or LLM evaluation frameworks.
Cloud platform experience (Azure, AWS, or GCP).
LLM Application Development — Hands-on experience with LLM APIs prompting, function/tool calling, retrieval-augmented generation, or agent frameworks — through work, side projects, or coursework
APIs & Integration — REST, webhooks, auth, and the ability to read and apply other systems’ documentation
SQL & Data Fluency — Working SQL and enough data fluency to wrangle the inputs an AI solution needs
Engineering Fundamentals — Git, code review, CI/CD, and writing code someone else can maintain
Communication — Ability to work beside non-technical business partners every day and earn their trust

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

airestllmjirapythontypescriptazureawsgcpsqlci/cd

Platform: workday
Effort: long