AI Architect

Job Description

AI Architect / AI Solution Architect Consultant

Location: Seattle, WA

Work Arrangement: Hybrid, minimum 3 days onsite per week when not traveling. Client travel varies by engagement.

Work Authorization: U.S. Citizen or Green Card Holder

Our client is a global technology and management consulting organization that helps large enterprises modernize their operations through data, analytics, cloud technologies, and artificial intelligence. Working across complex enterprise environments, the organization combines business strategy with technical architecture and implementation expertise. With significant investment in Generative AI, Agentic AI, and enterprise data transformation, the company is expanding its AI and data architecture capabilities to meet growing demand for scalable, governed, production-ready solutions that deliver measurable business outcomes.

About the Role

We are seeking AI Architects / AI Solution Architects to join a growing Data and AI Transformation practice. This position combines enterprise architecture, technical solutioning, and client-facing consulting, working directly with enterprise organizations to understand complex business challenges, assess existing technology environments, and design practical AI and data architectures.

Unlike traditional architecture roles that focus primarily on technical standards or high-level design, this position requires architects who can engage directly with business stakeholders, understand the underlying problem, evaluate architectural options, and guide engineering teams through implementation.

The role emphasizes enterprise data architecture, AI solution design, client-facing technical consulting, and AI governance , with a strong focus on developing architectures that can be successfully implemented within production environments rather than remaining theoretical recommendations.

Projects may involve enterprise data platforms, cloud modernization, Generative AI, Agentic AI, retrieval-augmented generation (RAG), enterprise knowledge retrieval, and AI-enabled business workflows. Success is measured by the quality and scalability of architectural solutions, successful implementation, client adoption, and measurable business impact.

What You'll Do

\n
• Partner directly with enterprise clients, business stakeholders, and technical teams to understand business challenges and translate requirements into scalable AI and data architectures.
\n
• Assess existing enterprise data environments, cloud infrastructure, technology platforms, and AI capabilities to identify architectural gaps and opportunities.
\n
• Design future-state enterprise AI and data architectures that align with business objectives, technical requirements, scalability, security, and governance standards.
\n
• Lead technical solutioning discussions, evaluate architectural approaches, and recommend appropriate technologies and design patterns based on client needs.
\n
• Architect solutions involving Generative AI, Agentic AI, LLM-powered applications, RAG systems, enterprise knowledge retrieval, and AI-enabled workflows.
\n
• Design architectures that integrate AI capabilities with existing enterprise data platforms, applications, and cloud environments.
\n
• Establish architectural approaches for data governance, AI governance, responsible AI, security, and appropriate controls.
\n
• Work across cloud environments such as AWS, Azure, and GCP , selecting architectural approaches that align with existing client infrastructure.
\n
• Present architectural recommendations, technical tradeoffs, and future-state designs to both technical teams and business leadership.
\n
• Guide engineering and delivery teams through implementation, ensuring solutions align with the intended architecture and enterprise requirements.
\n
• Collaborate with data engineers, AI engineers, enterprise architects, and client stakeholders throughout the solution lifecycle.
\n
• Challenge initial requirements when necessary to identify underlying business problems and recommend more effective architectural solutions.
\n
• Develop reusable architecture patterns, solution frameworks, and technical documentation that can support future client engagements.
\n
• Help ensure that proposed AI solutions move beyond experimentation into scalable, secure, governed production environments.
\n

What We're Looking For

\n
• Significant experience in enterprise data architecture, AI solution architecture, or enterprise technology architecture , typically at the Manager or Senior Manager level.
\n
• Strong foundation in data architecture , including designing enterprise data environments, data platform architectures, and scalable data solutions.
\n
• Demonstrated experience designing enterprise AI architectures and integrating AI capabilities into broader enterprise technology environments.
\n
• Experience assessing current-state technology environments and developing future-state architecture recommendations.
\n
• Strong understanding of data governance, AI governance, responsible AI, security, and enterprise architecture considerations .
\n
• Experience with major cloud platforms such as AWS, Azure, or GCP , including architectural considerations for enterprise-scale solutions.
\n
• Demonstrated ability to work directly with business stakeholders, understand ambiguous requirements, and translate business challenges into practical technical architectures.
\n
• Experience leading technical solutioning discussions, evaluating architectural alternatives, and communicating design decisions and tradeoffs.
\n
• Ability to guide engineering teams through implementation and ensure technical solutions align with architectural requirements.
\n
• Strong understanding of how enterprise data platforms, cloud technologies, and AI systems interact within complex organizational environments.
\n
• Experience presenting architecture recommendations to both technical and non-technical stakeholders.
\n
• Comfort operating in a client-facing consulting environment and adapting architectural approaches to different industries, technology stacks, and business requirements.
\n

Nice to Have

\n
• Experience with Databricks, Palantir , or comparable enterprise data platforms.
\n
• Familiarity with Data Mesh architecture principles.
\n
• Experience with enterprise cloud modernization or large-scale data platform transformation initiatives.
\n
• Architecture experience involving Generative AI, Agentic AI, RAG systems, vector databases, or AI orchestration frameworks .
\n
• Hands-on software engineering, data engineering, or AI development experience that supports practical architectural decision-making.
\n
• Background in management consulting, technology consulting, or enterprise digital transformation.
\n
• Experience designing architectures for AI-enabled business workflows, enterprise knowledge systems, or automated decision support.
\n
• Experience developing reusable architecture frameworks, reference architectures, or technical accelerators.
\n
• Experience working across multiple enterprise cloud platforms or complex technology environments.
\n

Why This Role?

\n
• Enterprise architecture ownership: Take responsibility for assessing complex client environments, defining future-state architectures, and guiding solutions through implementation rather than being limited to high-level advisory work.
\n
• Investment in AI and emerging technologies: Join an organization actively expanding its Generative AI, Agentic AI, enterprise data architecture, and AI governance capabilities.
\n
• Direct client impact: Work closely with enterprise stakeholders to solve business challenges and develop technical architectures that support measurable operational improvements.
\n
• Variety of architectural challenges: Gain exposure to different industries, enterprise technology environments, cloud platforms, data ecosystems, and AI use cases.
\n
• Opportunity to shape enterprise AI adoption: Help clients move from isolated AI experiments toward scalable, governed AI capabilities integrated into their existing technology environments.
\n
• Technical and consulting career development: Build experience across enterprise architecture, AI strategy, technical solutioning, stakeholder engagement, and implementation leadership.
\n

Travel requirements depend on the specific client engagement. Some projects may involve regular weekly travel, while others may require little to no travel.