Lead Cloud Solution Architect- AI & Data (AWS)

Remote from
USA flag
USA
Salary, yearly, USD
140,000 - 175,000
Employment type
Full Time,
Job posted
Apply before
17 Jul 2026
Experience level
Senior
Views / Applies
6 / 0

About World Wide Technology

World Wide Technology helps organizations discover, evaluate, architect, and implement advanced technology solutions.

Actively Hiring
Verified job posting
This job post has been manually reviewed for authenticity and compliance.

AI Summary

This lead role focuses on designing and implementing AI and data solutions on AWS for enterprise clients. The architect will develop scalable data platforms, AI architectures, and governance frameworks while leading presales activities and delivery oversight. Success involves reducing cycle times, improving delivery scalability, and enhancing client satisfaction. The position requires deep expertise in AWS data and AI services, as well as experience with platforms like Databricks and Snowflake. Strong communication skills are essential for bridging technical and executive audiences.

Role DNA

Job Complexity
Easy Hard
Pace & Pressure
Relaxed Fast-paced
Autonomy Level
Guided Full Ownership
Communication Load
Independent Highly Collaborative
AI Insight The role demands 10+ years of progressive experience, deep technical expertise across AWS data/AI services, and the ability to handle client-facing presales and delivery oversight, indicating a high level of complexity and responsibility.

Salary Analysis

Median Market Rate
USD157,500
US Market
USD130k โ€“ 200k
0 USD220k
AI Insight The offered salary range of $140,000 - $175,000 is competitive for a Lead Cloud Solution Architect with AI and Data expertise, aligning with market standards for senior roles requiring 10+ years of experience. The median of $157,500 falls within the typical range for this specialization in the US.

Key Skills

AWS Cloud Architecture Data Architecture AI/ML Enterprise Data Platforms SageMaker Bedrock Databricks Snowflake Solution Architecture

Dear Hiring Manager,

I am excited to apply for the Lead Cloud Solution Architect position. With over 10 years of experience in data architecture and AI on AWS, I have successfully designed and delivered enterprise-scale data platforms and AI solutions. My expertise includes leading presales engagements, developing technical frameworks, and mentoring teams to achieve scalable outcomes. I am confident in my ability to drive innovation and deliver measurable business value for your clients. Thank you for considering my application.

Can you describe your experience designing AI-ready data architectures on AWS, including specific patterns like RAG and vector stores?
In my previous role, I architected a data platform for a healthcare client that incorporated a lakehouse architecture on AWS using S3, Glue, and Lake Formation. For AI readiness, I implemented a RAG pattern using Amazon Bedrock and vector stores (Pinecone) to power a clinical decision support system. This involved building data pipelines for embedding generation and setting up a retrieval system with low latency. The architecture also included governance controls for PII handling and model governance.
How do you approach creating a business case for AI and data initiatives?
I start by understanding the client's strategic goals and identifying pain points where AI and data can deliver value. I quantify potential benefits such as cost savings, revenue growth, or efficiency gains, and map them to specific technical solutions. For example, for a retail client, I built a business case for a recommendation engine by estimating increased conversion rates and customer retention. I also include cost projections for the AWS services and operational expenses, and present a phased implementation plan to manage risk and demonstrate quick wins.
Describe a time you resolved a significant architectural issue that could have impacted a client's data platform.
While leading a data migration project from on-prem to AWS, we encountered a performance bottleneck in the data ingestion pipeline due to inefficient partitioning in Redshift. I conducted a thorough analysis of the query patterns and redesigned the distribution keys and sort keys, which improved query performance by 60%. Additionally, I implemented a monitoring solution using CloudWatch to proactively detect similar issues. This prevented the client from experiencing downtime during critical reporting periods and was recognized in the project retrospective.
What experience do you have with Databricks or Snowflake on AWS?
I have hands-on experience deploying Databricks on AWS for a financial services client, where we set up a multi-workspace environment with Unity Catalog for governance. I designed ETL pipelines using Delta Lake and integrated with AWS services like S3 and Kinesis for streaming data. For Snowflake, I led an implementation for a media company, configuring Snowpipe for real-time ingestion and setting up data sharing across business units. I am also familiar with cost optimization strategies for both platforms, including cluster sizing and auto-suspend policies.
How do you stay current with the rapid evolution of AWS data and AI services?
I regularly attend AWS re:Invent and re:Inforce, and follow AWS's What's New blog and official documentation. I also participate in the AWS Community and contribute to open-source projects. For AI specifically, I experiment with new services like Bedrock agents and SageMaker Canvas in my personal sandbox account. Additionally, I hold multiple AWS certifications (Solutions Architect Professional, Data Engineer Associate, and Machine Learning Specialty) which require continuous learning to maintain.

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-servicesย 

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.ย 

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

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

#LI-MP2

#LI-REMOTE

Qualifications

Why WWT?

At World Wide Technology, we work together to make a new world happen.ย Our important work benefits our clients and partners as much as it does our people and communities across the globe. WWT is dedicated to achieving its mission of creating a profitable growth company that is also a Great Place to Work for All. We achieve this through our world-class culture, generous benefits and by delivering cutting-edge technology solutions for our clients.

Founded in 1990, WWT is a global technology solutions provider leading the AI and Digital Revolution. WWT combines the power of strategy, execution and partnership to accelerate digital transformational outcomes for organizations around the globe. Through its Advanced Technology Center, a collaborative ecosystem of the world’s most advanced hardware and software solutions, WWT helps clients and partners conceptualize, test and validate innovative technology solutions for the best business outcomes and then deploys them at scale through its global warehousing, distribution and integration capabilities.

With over 15,000 employees across WWT and Softchoice and more than 60 locations around the world, WWT’s culture, built on a set of core values and established leadership philosophies, has been recognized 15 years in a row by Fortune and Great Place to Workยฎ for its unique blend of determination, innovation and creating a great place to work for all.

Want to work with highly motivated individuals on high-performance teams? Join WWT today!

Whatย isย the Solutions Consulting & Engineering (SC&E) Team and why join?

Solutions Consulting & Engineering is an organization that is Customer Focused and Solutions Led. We deliver end-to-end and emerging solutions to drive customer satisfaction, increaseย profitabilityย and growth. Our success is enabled by our world-class management consulting, deliveryย excellenceย and engineering brilliance. Our goal is to bring together business acumen with full-stack technicalย know-howย to develop innovative solutions for our clients’ most complex challenges.

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

Apply now >

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