[Hiring] Lead Cloud Solution Architect- AI & Data (AWS) @World Wide Technology

Role Description

As a Lead Solution Architect, AWS AI/Data, you are a senior individual contributor and recognized AWS data and AI expert who builds the go-to-market assets and leads the solution architecture that win WWT's AI & Data business. This is a sales-facing role, not a delivery execution role. Your primary mandate is to create the pitch materials, sales plays, competitive positioning, and business-case content that Solution Architects and account teams use to win pursuits, and to personally lead technical discovery and solution design in the highest-value pursuits.

You bring deep, current technical expertise in enterprise data and AI architecture, but your output is measured by the strength of the GTM materials you build and the deals you help win, not by internal delivery frameworks. You understand that AI outcomes are only as strong as the data foundation beneath them. You bring real-world experience designing enterprise data platforms, and you know how to structure, govern, move, and prepare data so AI can work. Critically, you also know how to translate that technical depth into a business case and a compelling client narrative. You've sold solutions, not just built them, and you're comfortable owning the technical story in front of an economic buyer.

Qualifications

• Minimum 10 years of progressive experience in data architecture, data engineering, cloud architecture, or related technical disciplines
• Minimum 7 years of hands-on experience designing, deploying, and operating data and AI workloads on AWS in enterprise environments
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience
• Demonstrated real-world experience designing and delivering enterprise data platforms, including data lakes, data warehouses, streaming architectures, and data governance frameworks
• Deep expertise in AWS data and AI platform services: Redshift, Glue, Lake Formation, Kinesis, EMR, Athena, SageMaker, Bedrock, and related ecosystem services
• Proven hands-on experience with Databricks or Snowflake deployed on AWS in enterprise environments
• Demonstrated experience designing AI-ready data architectures, including data preparation pipelines, vector stores, retrieval-augmented generation (RAG) patterns, and AI governance frameworks
• Proven ability to develop and articulate AI & Data business cases, connecting technical architecture decisions to client outcomes and measurable business value
• Experience authoring SOWs, LOEs, reference architectures, and delivery playbooks that technical teams can execute from
• Strong communication skills, able to present data and AI architecture concepts to executive audiences and technical depth to delivery teams with equal effectiveness

Requirements

• AWS Certifications
• AWS Certified Solutions Architect: Professional (strongly preferred)
• AWS Certified Data Engineer: Associate or Professional
• AWS Certified Machine Learning: Specialty
• Platform Certifications
• Databricks Certified Data Engineer (Associate or Professional)
• Snowflake SnowPro Core or Advanced: Data Engineer
• Technical Depth
• Enterprise data architecture patterns: data lakehouse, data mesh, data fabric, medallion architecture
• Data pipeline and orchestration tooling: Apache Airflow, AWS Step Functions, Glue workflows, dbt
• Streaming and real-time data architectures: Kinesis Data Streams, Kafka on AWS (MSK), EventBridge
• Data governance and cataloging: AWS Lake Formation, Glue Data Catalog, data lineage and quality frameworks
• AI operationalization on AWS: Bedrock, RAG architecture design, agentic workflow patterns, prompt engineering, AI governance
• Vector database and embedding patterns relevant to enterprise AI workloads
• SageMaker for model deployment, inference, and MLOps; experience with model training is a differentiator
• Application security patterns relevant to data and AI (data access controls, PII handling, model governance)
• Cloud cost modeling and FinOps principles as applied to data platform architecture decisions
• Multi-Cloud Exposure
• Familiarity with Azure data and AI services (Azure Synapse, Azure Data Factory, Azure AI Foundry, Microsoft Fabric)
• Experience advising clients on multi-cloud data strategy or workload placement decisions across AWS and Azure
• Microsoft Azure certifications (any level) are a plus

Benefits

• Health and Wellbeing: Health (Medical & Prescription), Dental, and Vision Care, Onsite Health Centers (MO & IL), Employee Assistance Program, Wellness program
• Financial Benefits: Competitive Pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Flexible Spending Accounts, Tuition Reimbursement
• Paid Time Off: PTO & Holidays, Parental Leave, Medical Leave, Military Leave, Bereavement, Day of Caring
• Additional Perks: Family Planning Benefits, Nursing Mothers Benefits, Voluntary Legal, Voluntary Supplemental Accident/Illness/Hospital, Voluntary ID Theft, Pet Insurance, Employee Discount Program