Senior Solutions Architect – Data & AI

About the role

We are seeking a Senior Solutions Architect – Data & AI to lead the design and delivery of enterprise‑scale data, analytics, machine learning and AI solutions for a global foodservice and distribution leader. The role is fully remote and requires hands‑on architecture expertise across modern cloud platforms and AI technologies.

Key responsibilities

• Lead end‑to‑end solution architecture for complex Data, Analytics, ML and AI initiatives.
• Design AI‑powered analytics solutions that combine enterprise data, ML models, AI agents and conversational analytics.
• Create architectures for Generative AI, Retrieval‑Augmented Generation (RAG), natural‑language analytics and agentic AI workflows using governed data sources.
• Define ML/AI enablement capabilities, including feature stores, model serving and MLOps pipelines.
• Develop analytics solutions on modern cloud data platforms, especially Google Cloud Platform (GCP) and BigQuery.
• Establish patterns for semantic layers, dimensional models, governed metrics, certified datasets and self‑service analytics.
• Translate enterprise reference architectures into practical project designs and ensure architectural integrity throughout delivery.
• Collaborate with Enterprise Architecture, Data Platform, AI, Engineering, Cybersecurity and Cloud Governance teams.
• Lead architecture reviews and contribute to Architecture Decision Records (ADRs) and Key Design Decisions (KDDs).

Required profile

• Extensive experience designing and delivering large‑scale data, analytics and AI solutions.
• Strong technical depth combined with excellent architectural judgment and communication skills.
• Ability to influence senior technical teams and navigate architecture governance.
• Comfortable working remotely and collaborating across multiple disciplines.

Required skills

• Google Cloud Platform (GCP) and BigQuery.
• Data and analytics architecture, semantic layers, dimensional modeling.
• Feature stores, model serving, MLOps pipelines.
• Generative AI, Retrieval‑Augmented Generation (RAG), natural‑language processing and AI agents.
• Enterprise data governance, APIs and integration patterns.
• Architecture Decision Records (ADRs) and Key Design Decisions (KDDs).