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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Cloud Solution Architect- AI & Data (AWS) - **Company:** World Wide Technology - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - $175,000.0 - **Contract:** Permanent contract - **Skills:** Training Data, Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Engineering, Encodings, Information Systems, Databases, Data Architecture, Data Cleansing, Information Engineering, Data Governance, Data Infrastructure, Data Warehousing, Machine Learning, Data Mesh, Data Streaming, Enterprise Data Management, Azure Data Factory, Retrieval-Augmented Generation, Snowflake, Prompt Engineering, IT Architecture, Software Security, Multi-Cloud, Data Strategy, Event Driven Architecture, Microsoft Fabric, Data Lakes, AI Platforms, Information Technology, Data Lineage, AWS Lake Formation, AWS Data Analytics, Real Time Data, Apache Kafka, Machine Learning Operations, Data Lakehouse, Data Delivery, Cloud Optimization, Azure Synapse Analytics, Data Pipelines, Databricks - **Published:** October 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=0ce201950d301a69 ## About the Role * 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, * 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 ## Description * 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, We strive to create an environment where all employees are empowered to succeed based on their skills, performance, and dedication. Our goal is to cultivate a culture of belonging that encourages innovation, collaboration, and respect for all team members, ensuring that WWT remains a great place to work for all! If you require accessibility accommodation(s) or adjustment during any stage of the hiring process, please let your WWT Recruiter know. The recruiter will work with you to understand your needs and help ensure an accessible experience throughout the interview process., 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. Key Responsibilities GTM & Sales Enablement Development * Build and maintain pitch decks, sales plays, and solution narratives for WWT's AI & Data offerings on AWS, translating technical architecture into client-ready business value * Develop competitive battlecards, differentiators, and positioning content that account teams and Solution Architects use in active pursuits * Create ROI models and business-case frameworks that connect data and AI architecture decisions to measurable client outcomes * Produce industry point-of-view and thought-leadership content that establishes WWT's credibility in AI & Data ahead of the pursuit * Partner with Practice Leadership and Marketing to align GTM content to client demand signals, competitive positioning, and AWS partner co-investment opportunities * Maintain a working library of reusable GTM assets, refreshed as offerings, competitive dynamics, and AWS services evolve Solution Architecture in the Sales Cycle * Lead client-facing discovery and solutioning as the senior technical voice on data architecture and AI operationalization, translating ambiguous business problems into well-scoped, value-anchored solutions * Design and present the proposed solution architecture directly to client stakeholders, from technical teams through economic buyers * Own the technical narrative in RFP/RFI responses, including the solution narrative, architecture rationale, and differentiators grounded in WWT's actual delivery experience * Partner with AWS field teams and WWT account executives to position AI & Data offerings and shape pursuit strategy on strategic accounts * Review SOWs, LOEs, and technical proposals for scope, risk, and pricing consistency before they reach the client Technical Credibility & Light-Touch Governance * Stay hands-on and current with AWS data and AI services to remain a credible technical voice with clients and AWS field teams * Spot-check architecture on the largest or highest-risk pursuits prior to signature and flag material risk to Delivery Leads; this is not a delivery oversight function * Capture pursuit and win/loss learnings and feed them back into GTM content, closing the loop between what wins deals and what the market is asking for