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

Strongly Desired Skills

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

What Success Looks Like in Year One

• WWT's AI & Data service offerings are sharper, more repeatable, and faster to scope, measurably reducing presales cycle time
• Solution Architects trust this role as their go-to technical escalation for AI & Data pursuits
• Delivery oversight has prevented at least one significant architectural problem from reaching the client
• The frameworks, playbooks, and standards this role has built have made WWT's AI & Data delivery more scalable, enabling the team to take on greater volume without sacrificing quality
• Client satisfaction scores on AI & Data engagements reflect a measurable improvement in delivery consistency and outcome achievement

Want to learn more about Consulting Services? Check us out on our platform:

https://www.wwt.com/consulting-services

Certain states and localities require employers to post a reasonable estimate of salary range. A reasonable estimate of the current base pay range for this position is $140,000 to $175,000 annually. Actual salary will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs. The range for this position in other geographic locations may differ. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that is not included in the base pay.

The well-being of WWT employees is essential. So, when it comes to our benefits package, WWT has one of the best. We offer the following benefits to all full-time employees:

• Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program
• Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement
• Paid Time Off: PTO and Sick Leave (starting at 20 days per year) & Holidays (10 per year), Parental Leave, Military Leave, Bereavement
• Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program

If you have any questions or concerns about this posting, please email [email protected].

#LI-MP2

#LI-REMOTE

Position Overview

As a Lead Cloud Solution Architect - AI & Data (AWS), you are a senior individual contributor and recognized AWS expert who shapes how WWT builds, sells, and delivers data and AI outcomes for enterprise clients.

This is not a delivery execution role. Your primary mandate is to define the delivery process, build the technical frameworks, and provide the subject matter expertise that enables WWT's AI & Data offerings to scale. The role is composed of three focus areas: building and maturing WWT's AI & Data service offerings, supporting pre-sales pursuits as a technical SME, and providing delivery oversight on strategic accounts and pilots.

You understand that AI outcomes are only as strong as the data foundation beneath them. You bring real-world experience designing and delivering enterprise data platforms, and you know how to structure, govern, move, and prepare data so that AI can work. You have guided clients through the technical and organizational complexity of becoming a data-driven enterprise, and you have helped them take that foundation and operationalize AI on top of it.

Key Responsibilities

Solution Development

• Define and continuously improve WWT's AI & Data delivery process, including reference architectures, delivery playbooks, assessment frameworks, and reusable delivery assets for the AWS platform
• Define and document repeatable engagement patterns for the full AI & Data lifecycle: data platform assessment, data architecture design, data engineering and pipeline development, AI readiness, and AI operationalization
• Develop and maintain SOW templates, LOE models, and scope frameworks that enable Solution Architects and delivery teams to structure and price engagements consistently
• Partner with Practice Leadership to align AI & Data offerings to client demand signals, competitive positioning, and AWS partner co-investment opportunities
• Provide technical oversight on pilot engagements and strategic accounts, not as a delivery executor, but as a quality gate ensuring architectural decisions align with WWT standards and client outcomes
• Collaborate with the Cloud Migration, Security, and Infrastructure solution areas to ensure AI & Data offerings integrate cleanly across the WWT Cloud portfolio

Pre-Sales SME Support

• Engage directly with clients during discovery and solutioning as the senior technical voice on data architecture and AI operationalization, translating ambiguous business problems into well-scoped, value-anchored technical solutions
• Review and validate SOWs, LOEs, and technical proposals produced by Solution Architects; identify scope gaps, risk patterns, and pricing inconsistencies before they reach the client
• Support RFP/RFI responses as the technical subject matter expert, providing solution narratives, architecture rationale, and differentiators that reflect WWT's actual delivery experience
• Partner with AWS field teams and WWT account executives to position AI & Data offerings and develop pursuit strategies for strategic accounts

Technical Delivery Excellence

• Serve as a technical executive sponsor on WWT's highest-complexity AI & Data engagements, providing architectural guidance, escalation support, and quality assurance at key delivery milestones
• Identify delivery risk early, including scope creep, architectural drift, data quality issues, and team skill gaps, and work with Delivery Leads to course-correct before issues reach the client
• Conduct architecture and design reviews on active engagements to ensure alignment with WWT reference patterns and AWS Well-Architected principles
• Capture delivery learnings and feed them back into the solution development process, closing the loop between what we promise and what we deliver