About The Position

Carter's is establishing an enterprise AI Center of Excellence (CoE) to implement safe, governed, and high-value AI across the business. As the Manager, AI Development, you will act as a player-coach, leading the CoE's build team. This role involves managing and mentoring AI developers, providing guidance on solution design, and remaining hands-on with coding. You will be responsible for translating prioritized use cases into deployed and supported AI solutions, such as agentic workflows, connectors, automations, and reporting tools. Additionally, you will focus on elevating the team's technical capabilities and establishing reusable patterns for enterprise-wide adoption. Collaboration with the Tech & Platform Lead on architecture and the Solutions Manager on delivery commitments is essential.

Requirements

  • At least 7+ years of software and/or data analytics development experience
  • At least 2+ years leading or managing developers including 1+ years building Generative AI (GenAI)/large language models (LLMs)-based solutions
  • Hands-on AI development — practical experience shipping LLM applications, agentic workflows, or AI-powered automations against enterprise systems and APIs
  • Proven experience with enterprise AI platforms and frameworks (e.g., Claude/Anthropic API, Azure OpenAI, MCP-style tool integrations, RAG architectures)
  • Experience in leading sprint planning, backlog grooming, and prioritization processes, collaborating with stakeholders to deliver critical features and meet strategic goals.
  • Communication — excels at partnering with non-technical stakeholders, clarifying ambiguous needs, facilitating productive discussions, and guiding developers with clear, constructive, and empathetic feedback.
  • Delivery leadership — track record running agile delivery: backlog management, code review discipline, and predictable releases
  • Integration fluency — comfort working with enterprise data and platform integrations (e.g., BI tools, cloud data warehouses, collaboration and ticketing systems)
  • At least a Bachelor's degree in Computer Science, Software Engineering, and/or related field, or equivalent practical experience

Nice To Haves

  • Familiarity with MLOps/LLMOps practices: evaluation, monitoring, versioning, and cost management
  • Retail or consumer-products industry experience
  • Building out cross-functional teams along with team development

Responsibilities

  • Manage the AI CoE development team (Junior/Mid AI Developers and intern developers): assignments, priorities, performance, and career growth
  • Own sprint planning and delivery execution for the CoE build backlog, in partnership with the Solutions Manager's intake and prioritization
  • Run code and design reviews; unblock developers and manage delivery risks and dependencies
  • Coordinate with Forward-Deployed Engineers so embedded builds follow CoE standards and hand back cleanly
  • Report delivery status, capacity, and velocity to CoE leadership
  • Personally design and build the most complex or highest-stakes AI solutions (agentic workflows, LLM applications, skills, and connector-based automations)
  • Consult with business units and FDEs on solution feasibility, approach, and effort — turning ambiguous asks into buildable designs
  • Prototype new patterns (e.g., natural-language query over governed data, document generation, incident summarization) and harden successful pilots into production solutions
  • Serve as escalation point for technical issues across CoE-supported solutions
  • Define and enforce development standards: coding practices, testing, documentation, versioning, and release management for AI solutions
  • Curate the CoE pattern library of reusable, governed building blocks for business super users and champions
  • Partner with the AI Security & Governance Manager so every building pass security review efficiently (access controls, data flows, prompt-injection safeguards)
  • Mentor super developers in business units; support office hours and paired builds that move prototypes into supported solutions
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