Lead Cloud Solution Architect- AI & Data (AWS)

Lead Cloud Solution Architect - AI & Data (AWS)

Company: World Wide Technology Location: Remote (USA) Contract: Permanent Seniority: Senior

World Wide Technology (WWT) is a global technology solutions provider at the forefront of the AI and Digital Revolution. We are seeking a highly experienced Lead Cloud Solution Architect with deep expertise in AWS, AI, and Data Architecture to join our remote team. In this senior individual contributor role, you will be instrumental in shaping how WWT builds, sells, and delivers cutting-edge data and AI solutions for enterprise clients.

This position focuses on defining delivery processes, building technical frameworks, and providing subject matter expertise to scale WWT's AI & Data offerings. You will be a recognized AWS expert, understanding that robust AI outcomes depend on a solid data foundation.

Key Responsibilities

Solution Development

• Define and continuously improve WWT's AI & Data delivery processes, including reference architectures, delivery playbooks, assessment frameworks, and reusable assets for the AWS platform.
• Document repeatable engagement patterns for the entire AI & Data lifecycle: data platform assessment, data architecture design, data engineering and pipeline development, AI readiness, and AI operationalization.
• Develop and maintain Statement of Work (SOW) templates, Level of Effort (LOE) models, and scope frameworks.
• Align AI & Data offerings with client demand, competitive positioning, and AWS partner co-investment opportunities.
• Provide technical oversight on pilot engagements and strategic accounts, ensuring architectural decisions align with WWT standards and client outcomes.
• Collaborate with Cloud Migration, Security, and Infrastructure solution areas to ensure seamless integration across the WWT Cloud portfolio.

Pre-Sales SME Support

• Engage directly with clients as the senior technical voice on data architecture and AI operationalization, translating business problems into well-scoped, value-anchored technical solutions.
• Review and validate SOWs, LOEs, and technical proposals, identifying scope gaps, risks, and pricing inconsistencies.
• Support RFP/RFI responses as the technical subject matter expert, providing solution narratives and architectural rationale.
• Partner with AWS field teams and WWT account executives to position AI & Data offerings and develop pursuit strategies.

Technical Delivery Excellence

• Serve as a technical executive sponsor on high-complexity AI & Data engagements, providing architectural guidance, escalation support, and quality assurance.
• Identify and mitigate delivery risks, including scope creep, architectural drift, data quality issues, and team skill gaps.
• Conduct architecture and design reviews to ensure alignment with WWT reference patterns and AWS Well-Architected principles.
• Capture delivery learnings to refine and improve the solution development process.

Requirements

• 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 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 such as Redshift, Glue, Lake Formation, Kinesis, EMR, Athena, SageMaker, and Bedrock.
• 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.
• Strong communication skills, capable of presenting complex concepts to both executive and technical audiences.

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, Kafka on AWS, EventBridge), data governance and cataloging (AWS Lake Formation, Glue Data Catalog), AI operationalization on AWS (Bedrock, RAG, agentic workflows, prompt engineering, AI governance), vector database and embedding patterns, SageMaker for model deployment and MLOps, application security patterns