AI Developer

The AI Developer is responsible for developing new AI applications and software including agentic AI applications, analytical solutions and pilot new ideas from incubation to deployment. This role is a critical part of Family Dollar’s capability to build our own AI applications inhouse using top of line agent development kits, APIs, software libraries and interface with our vendors and partners to trial their products for fit within Family Dollar’s IT estate, including our cloud environments, digital applications, and our operational systems., * Design, build, and deploy production AI applications on Google Cloud Platform, applying machine learning and generative AI techniques to deliver solutions across merchandising, supply chain, store operations, finance, and customer experience.

• Develop agentic AI applications using modern agent development kits and frameworks (e.g., Google Agent Development Kit, Gemini Agent Platform, LangGraph), including multi-agent workflows, tool integration, and human-in-the-loop checkpoints.
• Build and operate retrieval-augmented generation (RAG) solutions that ground LLMs in Family Dollar’s enterprise data, including ingestion, embeddings, vector and hybrid search, reranking, and evaluation.
• Establish and maintain MLOps pipelines for AI workloads, including CI/CD, model and prompt versioning, evaluation harnesses, monitoring, cost controls, and rollback procedures.
• Implement enterprise-grade guardrails for AI applications, including prompt injection defense, PII handling, content safety, role-based access controls, and audit logging - partnering closely with platform, security, infrastructure, and business stakeholders to ensure deployments meet Family Dollar’s standards for identity, networking, data residency, and compliance.
• Evaluate vendor and partner AI products for fit within Family Dollar’s IT estate; build proofs of concept, run technical bake-offs, and produce clear recommendations.
• Execute experiments to vet emerging AI capabilities and determine their internal product-market fit.
• Deploy and maintain production-grade AI agents capable of reasoning, tool-use, and multi-step task execution.
• Manage the full lifecycle of your code, from initial prompt engineering and fine-tuning to CI/CD and real-time monitoring of agent performance.
• Mentor junior engineers and share knowledge across the AI and Automation team.
• Partner with IT support teams to co-own AI application support, including on-call coverage, while progressively transitioning ownership through SOPs, runbooks, and helpdesk documentation
• Performs other duties as assigned.

The ideal candidate is a senior engineer with 8+ years of professional software development experience, deep proficiency in Python, and hands-on experience building and deploying production AI workloads on Google Cloud Platform and interconnecting multiple applications via robust secure best practices and scalable enterprise frameworks. They are adept with generative AI, large language models, and agentic AI frameworks, and bring a working knowledge of MLOps, retrieval-augmented generation (RAG), and applied data science. They can take new ideas from incubation through pilot to production, run experiments on their own to validate feasibility, define success metrics, evaluation methodology, and exit criteria at each stage., * Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field (Master’s degree preferred).

• 8+ years of progressive IT experience in large, cross functional teams or projects, preferably in a retail environment.
• Write clean, well-tested, well-documented Python code; conduct code reviews; and contribute to internal libraries, templates, and engineering best practices.
• Ability in developing, presenting and communicating technical concepts to varying audiences.
• Possesses a sense of urgency as well as the ability to motivate a team towards achieving results in a dynamic environment
• Experience in retail, supply chain, or large-scale operational environments within retail systems (POS, ERP, CRM, inventory, supply chain, etc).
• Advanced knowledge of recent GenAI platform advancements from top providers as well as equivalent platforms hyperscalers
• Experienced in responsible AI practices, model governance, and frameworks for evaluating LLM safety and accuracy.
• Contributions to open-source AI projects or relevant publications.