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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Architect - Data Engineering - **Company:** Sysco Corporation - **Location:** United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data Architecture, Information Engineering, Data Governance, Data Systems, Software Design Patterns, Dimensional Modeling, Enterprise Data Management, Google Cloud, Large Language Models, Multi-Agent Systems, IT Architecture, Model Validation, Data Layers, Information Technology - **Published:** September 5, 2026 - **Apply:** https://wd5.myworkdaysite.com/recruiting/sysco/syscocareers/job/Sysco-LABS-----Sri-Lanka/Architect---Data-Engineering_R264166-1 ## About the Role * Bachelor's degree in Computer Science, Engineering, or a related field. * 8+ years of experience in Data Architecture, Solution Architecture, or senior Data Engineering roles, including 3+ years with demonstrated architectural ownership of enterprise-scale solutions. * Deep expertise in cloud platforms (AWS, GCP, or Azure). Hands-on experience with the GCP data ecosystem is a strong advantage. * Demonstrated ability to define and architect modern AI-enabled solutions, including agentic workflows, LLM application patterns, RAG, grounding, prompt and context engineering, model evaluation. * Proven experience designing agentic workflows and building agentic solutions using Google Gemini Enterprise and/or Vertex AI is a strong advantage. * Domain knowledge and familiarity with the core processes within relevant business domain(s). * Exceptional communication and presentation skills, with a proven ability to explain complex architectural concepts to technical, functional, and executive audiences. * Experience operating in a forward-deployed or embedded architecture model within business domains is an advantage. * Familiarity with data mesh and data product operating models, semantic layers, and dimensional modeling is an advantage. ## Description Domain Architecture Ownership * Serve as the single architectural point of accountability for data, analytics, and AI solutions within the assigned business domain (Supply Chain & Operations, Merchandizing, Pricing, Commercial Technology and Finance). * Define and maintain the domain-driven data models and target-state architecture, ensuring alignment with enterprise data platform standards, governance frameworks, and reference architectures. * Author architecture artifacts including logical architecture, detailed designs, ADRs and represent domain solutions through Architecture Review processes. AI & Agentic Solution Design * Translate product intent into architecture and technical direction for AI-augmented workflows. * Design agentic workflows and multi-agent architectures that solve domain business problems, leveraging Google Gemini Enterprise and Vertex AI. * Establish reusable agentic design patterns for the domain including evaluation frameworks, human-in-the-loop controls, observability, and cost-awareness built in from design. Data Architecture on Google Cloud Platform * Architect data solutions on the GCP data stack applying medallion architecture, data products, and semantic layer principles. * Embed data governance, security, observability, and FinOps considerations into every solution design. Stakeholder Engagement & Communication * Communicate fluently across technical, functional, and business audiences from engineering deep-dives to executive readouts. * Present complex concepts in clear accessible terms and build stakeholder confidence in emerging architecture patterns through storytelling, visuals, and working demonstrations. * Interface with business domain leaders, be at the forefront of planning and engagement and act as a trusted advisor to Domain Business leaders, proactively identifying where Data and AI solutions can create measurable operational value. Delivery & Enablement * Prototype conceptual models that prove out architecture proposals, then execute a structured handover to implementation teams for productionizing, scaling, and support. * Partner with solution delivery teams, platform engineering, and Run & Support partners to ensure design intent carries through from blueprint to production. * Conduct architecture reviews, provide design guidance to engineering teams, and uplift domain teams on agentic and AI architecture best practices. ## Related Videos - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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