AI Architect​/Artificial Intelligence Architect

Key Responsibilities AI Architecture & Strategy

• Define and own the enterprise AI architecture for retail use cases, aligning with business priorities and technology strategy.
• Develop reference architectures, patterns, and standards for AI/ML and Generative AI solutions.
• Translate retail business problems into scalable AI solution blueprints with clear data, model, and integration designs.
• Partner with business and product leaders to identify and prioritize high-impact AI opportunities across merchandising, supply chain, marketing, stores, and e-commerce.

• Architect end-to-end AI solutions, including data ingestion, feature engineering, model training, inference, and system integration.
• Design AI systems for core retail domains such as:
  • Search, recommendations, and personalization
  • Demand forecasting, inventory optimization, replenishment, and allocation
  • Pricing and markdown optimization
  • AI assistants and copilots for store, merchandising, and supply-chain teams
• Define integration patterns between AI services and retail platforms (POS, OMS, WMS, CRM, e-commerce).
• Lead architectural reviews, ensuring solutions meet performance, scalability, security, cost, and reliability requirements.

• Establish MLOps and AIOps practices, including CI/CD for models, automated retraining, monitoring, drift detection, and cost controls.
• Define standards for Generative AI and LLM usage, including:
  • Multi RAG architectures, MCP and vector search
  • Prompt orchestration and tool-calling
  • Safety, guardrails, and human-in-the-loop workflows
• Ensure AI solutions comply with data privacy, security, and responsible AI principles.
• Partner with Security, Legal, and Enterprise Architecture to align AI solutions with governance and risk standards.

• Work closely with AI Engineers, ML Engineers, Data Engineers, and platform teams to ensure architectures are production-ready and executable.
• Provide hands‑on guidance during implementation, including reference code, pipelines, schemas, and infrastructure patterns.
• Evaluate and recommend AI SAAS solutions, cloud services, and frameworks (AWS, Azure, GCP, Databricks, etc.).
• Lead build vs. buy decisions and support vendor selection for AI capabilities.

• 9+ years of experience in software, data, or AI engineering, with 5+ years in AI/ML architecture roles.
• Proven experience designing and delivering production AI solutions in retail, e-commerce, supply chain, or adjacent domains.
• Strong hands‑on expertise in:
  • Python and ML frameworks (PyTorch, Tensor Flow, scikit-learn)
  • Modern data architectures (lakehouse, streaming, batch pipelines)
  • Modern Data Platforms (Databricks, Snowflake)
  • Cloud platforms and managed AI/ML services
  • MLOps practices (model lifecycle, monitoring, CI/CD)
• Solid understanding of LLMs, Generative AI patterns, and AI system integration.
• Excellent communication skills with the ability to explain complex architectures to both technical and business stakeholders.

• Deep experience in retail or consumer‑facing industries (merchandising, stores, supply chain, digital commerce).
• Experience building or scaling enterprise AI platforms or AI Centers of Excellence.