Greenwich
We are looking for a highly motivated AI Engineer to join our IT team. This role is ideal for someone passionate about building real-world AI solutions and eager to work across the full AI technology stack—from model integration and retrieval pipelines to agentic AI workflows, multi-agent orchestration, and application-level features used by business teams. You will also contribute to data engineering efforts that feed AI capabilities, working alongside a modern analytics platform built on Microsoft Fabric. As an AI Engineer, you will help design, develop, and deploy AI capabilities. You will contribute to production-grade AI features in areas such as Open-to-Buy planning, Sales Forecasting, Intelligent Order Management Systems (OMS), Product Copy Generation, and Image Generation. This is a unique opportunity to work on meaningful, high-impact AI initiatives while implementing modern AI infrastructure, LLMOps practices, and scalable system design. This role will work from our Greenwich, CT office and report to the Senior Director of System Integration & Operation on our current hybrid schedule, 3 days in office and 2 days remote. Key Responsibilities: AI Application Development Build and maintain AI-powered features including: • Open-to-Buy optimization and inventory planning models, • Sales forecasting and demand prediction solutions, • Intelligent OMS features for routing, allocation, and automation RAG, GraphRAG, + Vector DB Engineering • Develop retrieval pipelines using vector embeddings and similarity search (Azure AI Search, FAISS, Pinecone, or equivalent)., • Implement chunking, embedding, indexing, query routing, and relevance-tuning strategies, including advanced reranking and hybrid search techniques., • Maintain a high-quality knowledge base to support AI features via Retrieval-Augmented Generation., • Explore and implement GraphRAG patterns to improve knowledge retrieval over structured enterprise data and entity relationships. AI Agents & Orchestration • Design and build AI agents capable of planning, tool use, and multi-step reasoning using frameworks such as LangGraph, PydanticAI, CrewAI, or Google ADK., • Implement Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocol integrations to connect AI agents with internal tools, APIs, data systems, and other agents in a standardized, interoperable way., • Build guardrails, evaluation frameworks, and human-in-the-loop checkpoints to ensure reliable and safe agent behavior in production. AI Infrastructure & System Architecture • Maintain private cloud LLM instance landscape, ensuring secure and efficient usage., • Assist in deploying scalable inference pipelines, batching, and caching layers., • Collaborate with DevOps and Data Engineering on CI/CD, model deployment workflows, monitoring, and integration with the Microsoft Fabric data platform (including Fabric MCP for agent-to-data connectivity). Data Engineering, Pipelines & Model Training • Clean, transform, and prepare datasets for ML/AI pipelines; contribute to data engineering workflows including ELT pipeline design, medallion architecture patterns, and data transformation within the Lakehouse layer., • Train, validate, and fine-tune models where appropriate (LLMs, forecasting models, classification models, etc.); familiar with parameter-efficient techniques such as LoRA and QLoRA., • Evaluate model performance and optimize latency, accuracy, and cost using LLM evaluation and observability frameworks (e.g., RAGAS, LangSmith, Langfuse, Helicone, or custom evals); manage prompt versioning and regression testing. Required Qualifications: • Bachelor’s degree in Computer Science, Data Science, AI/ML, Engineering, or related field., • Strong foundations in Python, data structures, and machine learning concepts., • Comfortable working with LLM APIs, embeddings, vector databases, and RAG patterns; exposure to agentic patterns, tool use, and GraphRAG concepts is a strong plus., • Familiarity with cloud environments (Azure preferred; AWS or GCP also acceptable)., • Understanding of systems diagrams, architecture patterns, and AI infrastructure components., • Exposure to SQL/NoSQL databases., • Exposure to data engineering concepts such as ELT/ETL pipelines, data transformation, and data modeling., • Awareness of responsible AI principles including bias detection, fairness, and model interpretability., • Awareness of AI agent frameworks and orchestration concepts (e.g., LangGraph, PydanticAI, Semantic Kernel, CrewAI, or Google ADK)., • Familiarity with prompt engineering best practices including chain-of-thought, few-shot prompting, and structured output design. Preferred Qualifications: • Familiarity with Microsoft Fabric (OneLake, Lakehouse, Spark notebooks, semantic models) and Power BI; experience with Fabric MCP integrations is a strong differentiator., • Experience implementing MCP (Model Context Protocol) servers or A2A (Agent-to-Agent) protocol endpoints, or integrating AI agents with external tools and APIs., • Exposure to multimodal AI capabilities (vision-language models) for applications such as product image analysis or document understanding., • Experience building small AI apps, demos, or tools—portfolio/GitHub encouraged. What you'll Gain: • Hands-on impact in designing enterprise AI capabilities from the ground up., • Opportunities to work with cutting-edge LLM technologies in a private, secure environment, alongside a modern Microsoft Fabric data platform., • A chance to shape AI products used across supply chain, marketing, and e-commerce. Company Overview: Established in 2005, Marc Fisher Footwear company is a leading full-service, product-driven fashion footwear company with knowledge and expertise in design, sales, sourcing, distribution and marketing – all with dedicated and strategic direction for each brand within the portfolio, which includes GUESS, G by Guess, Nine West, Tommy Hilfiger, Earth, Calvin Klein, Kenneth Cole Men's, Hunter Boots, Rockport, Bandolino, indigo rd., Unisa, and Easy Spirit along with the namesake brands – Marc Fisher and Marc Fisher LTD. Our diverse portfolio of globally recognized brands – available domestically and internationally via wholesale and retail channels – consistently meets the widest range of consumers’ fashion footwear needs, from classic to contemporary, sport to dress, men’s to women’s. Headquartered in Greenwich, Connecticut, with showrooms in New York City, Marc Fisher Footwear is sold worldwide through department stores, specialty stores and e-commerce channels. Marc Fisher Footwear is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with a disability. EEO Employer/Vet/Disabled.