Principal AI Architect Jobs
Principal AI Architect jobs are open across technology, financial services, healthcare, and enterprise software, from senior staff to distinguished and principal levels, with specializations in large language model infrastructure, MLOps platform design, and responsible AI governance. Find a role that fits below and apply directly.
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Description
The Solution Architect is a hybrid technical delivery and client-facing role that spans the full life of an engagement, from the first conversation to successful delivery. When a Client Executive identifies an opportunity, the Solution Architect is the technical expert they bring in to understand the client's real problem, design the right solution, and scope the engagement. Once the deal is signed and depending on the scope of the engagement, the Solution Architect converts to a billable technical lead. The Solution Architect will work with the Delivery Manager to build a team to deliver on their engagement and will provide technical leadership & account management through project completion. Additionally, the Solution Architect should have a “Forward Deployed Engineer” mindset, always looking for new problems we can solve for our clients, ways we can expand our team or scope to deliver an even better solution, and advising our clients on technical strategies that lead to improved business outcomes.
This role is for a builder and an advisor in equal measure. Clients often know what they want but not always what they need, and sometimes what they ask for is not in their best interest. The Solution Architect guides them to the right outcome with credibility, candor, and deep technical judgment, becoming the trusted advisor the client relies on well beyond the initial sale. This role spans the entire project lifecycle and requires the tenacity to not only design and start a project, but to see it through to its successful end.
What you will do
- Partner with Client Executives and Solution Executives to qualify opportunities, lead technical discovery, and uncover the business problem behind the request.
- Facilitate envisioning sessions and workshops that help clients define outcomes, priorities, and a realistic roadmap.
- Design end-to-end solutions and translate them into clear scope, estimates, staffing plans, business outcomes, and risk assessments.
- Architect and co-author high-level designs (HLDs), level-of-effort (LOE) estimates, proposals, statements of work (SOWs), RFP responses, business cases, and client presentations, and serve as a core member of the team that closes the sale.
- Own the commercial soundness of solutions by structuring the engagement staffing mix and delivery approach, including AI-accelerated delivery, to achieve target margin while providing strong client outcomes.
- Identify where AI can create meaningful value for the client, and where it cannot, and shape solutions accordingly.
- Present and defend the solution to client stakeholders and maintain continuity from pursuit through delivery.
- Convert to billable delivery once an engagement is signed, when it makes sense in the project context, serving as technical lead and primary architecture authority for the project.
- Build, onboard, and lead delivery teams, including large teams on multi-million, multi-year engagements; set engineering standards, architecture guardrails, and AI-enabled development practices.
- Assume hands-on design or development responsibilities when needed, particularly during team ramp-up.
- Manage technical risk, scope, and change in partnership with project management and the client, protecting delivery quality and the client relationship.
- Serve as a primary client contact alongside Project and Delivery Managers, transition steady-state leadership appropriately, and continue advising prior engagements as needed.
- Use AI tools, including agentic development workflows, as a core part of how software is designed, built, and delivered.
- Lead teams that build client solutions incorporating AI, from LLM-powered features to agent-based systems, with appropriate attention to quality, security, and responsible use.
- Coach engineers and clients on effective, practical AI adoption and contribute reusable patterns and accelerators to the practice.
- Build external thought leadership through white papers, case studies, conference talks, webinars, and partner events on agentic software development, AI-accelerated delivery, and practical AI adoption.
- undefined
What we expect of you
- Bachelor’s degree and 10+ years of software engineering and architecture experience, including hands-on development in at least one of Java, .NET (C#), Python, or JavaScript/TypeScript OR 14+ years of software engineering and architecture experience, including hands-on development in at least one of Java, .NET (C#), Python, or JavaScript/TypeScript
- 1+ year experience in AI & Agentic Engineering: LLM application design (RAG, tool use, agents, orchestration); model selection and evaluation; responsible AI and guardrails; daily use of AI coding assistants and agentic development tools. Agent harness engineering (e.g., Claude Agent SDK, LangGraph, Microsoft Agent Framework), including tool and MCP integration, context and memory management, sandboxing, permissions, and human-in-the-loop controls; evaluation harnesses for testing and regression-checking model and agent behavior.
- 5+ years of experience in a solution architect, technical lead, or similar role designing solutions that span applications, integration, data, and cloud infrastructure.
- 3+ years of experience in a client-facing consulting or professional services role, including direct participation in pre-sales discovery, solution design, estimation, proposal development, and closing.
- Demonstrated experience developing software using AI tools, ideally including agentic development workflows.
- Experience leading teams that designed and delivered client solutions incorporating AI capabilities.
- Proven ability to lead delivery teams through ambiguity, including ramping teams up and personally filling gaps.
- Exceptional communication skills, with the ability to engage executive stakeholders and engineers and respectfully challenge client assumptions.
- Hands-on depth in at least one and working fluency in another: Cloud Platforms: Microsoft Azure, AWS, and/or Google Cloud; landing zones, compute, networking, identity, cost, and security design.
- Languages & Frameworks: Java, .NET (C#), Python, JavaScript/TypeScript; front-end with React, React Native, and Angular.
- Architecture & Platforms: Microservices, event-driven, and serverless architectures; domain-driven design; modernization and migration patterns; non-functional requirements (scale, resilience, security, cost).
- Integration & APIs: REST and GraphQL API design; API gateways and management; messaging and streaming (e.g., Kafka, Service Bus, SQS/SNS); iPaaS/integration platforms; identity and auth (OAuth 2.0, OIDC).
- Applications: Custom web and mobile applications, enterprise and line-of-business systems, SaaS/platform extensions, and legacy modernization.
- DevOps & Tooling: CI/CD (GitHub Actions, Azure DevOps, GitLab) including mobile CI/CD (Fastlane); Infrastructure as Code and configuration management (Terraform, Bicep, CloudFormation, Ansible); containers and Kubernetes, including Red Hat OpenShift; observability; DevSecOps practices.
- Data-Centric Solutions: Relational and NoSQL data modeling; data pipelines and ETL/ELT; modern data platforms (e.g., Databricks, Snowflake, Fabric); vector databases; data governance as it relates to AI readiness.
- Testing & QA: Test-driven development with a minimum of 90% unit test coverage on all code; unit, integration, end-to-end, and contract testing; test automation frameworks across the stack (e.g., JUnit, xUnit/NUnit, pytest, Jest, Playwright, Cypress, Detox for React Native); coverage and quality gates enforced in CI/CD (e.g., SonarQube); performance and security testing; validation of AI-generated code and AI-powered features.
- Willingness to travel 25%
- Professional or specialty cloud certifications (e.g., Azure Solutions Architect Expert, AWS Solutions Architect Professional, Google Professional Cloud Architect), a plus.
- Professional certifications in AI-enabled development (e.g., Claude Certified Architect, Microsoft Azure AI App and Agent Developer, Microsoft Agentic AI Business Solutions Architect Expert, AWS Certified Generative AI Developer - Professional, Google Cloud Professional Machine Learning Engineer), a plus.
- Experience building production agentic or LLM-based systems, including evaluation, observability, and guardrails, a plus.
- Background in both greenfield builds and legacy modernization or migration efforts, a plus.
- Experience working within a quota-carrying or sales-incentivized structure, a plus.
- Familiarity with Agile delivery methods and consulting engagement models (fixed fee, time and materials, managed capacity), a plus.
Pay range: $156,000 - $240,800 depending on experience and skill set
Annual bonus target of 10% subject to terms and conditions of plan
Benefits overview: https://cdw.benefit-info.com/
Salary ranges may be subject to geographic differentials
CDW is committed to being an AI-fluent organization
We’re looking for people who bring curiosity, a learner’s mindset, and a willingness to engage with ever-evolving technology and tools. We value adopting AI as a partner, openness to experimentation, and a shared interest in learning together on AI. Our goal is to create a culture where AI enhances—not replaces—human creativity and decision-making. You don’t need to be an expert today; what matters is your readiness to explore, adapt, and grow with us as we integrate AI responsibly and effectively into our work.Additionally, CDW is committed to fostering an equitable, transparent, and respectful hiring process for all applicants. During our application process, our goal is to understand your experience, strengths, skills, and qualifications. As an AI forward company, we see AI not just as a tool, but as a catalyst for new ways of thinking, creating, and communicating. We encourage candidates to embrace an AI mindset, one that’s curious, adaptive, and ready to explore what’s possible. We welcome thoughtful use of AI to expand your perspective and elevate how you share your story, while ensuring your application remains rooted in your own background, judgment, and voice.
About Us
CDW is a Fortune 500 technology solutions provider that helps businesses, government, education, and healthcare organizations achieve what’s possible through technology. What makes CDW different isn’t just what we do—it’s how we do it. At CDW we act as one—building trust, speaking candidly, and working together to achieve more. We play to win—focusing on what matters most and delivering for our customers. And we think forward—staying curious, moving fast, and continuously learning. We believe meaningful work happens when people feel supported, heard, and empowered to contribute. That’s why we think of ourselves as coworkers, not just employees—working together to solve complex challenges and deliver real impact for our customers and communities.
As a full‑stack, full‑lifecycle technology partner, CDW brings deep expertise, strong relationships, and broad industry knowledge to help turn ideas into outcomes. When you join CDW, you become part of a collaborative environment where your work matters, your growth is supported, and your contributions help shape what’s next.
Together, we deliver the full promise of what technology can do. Together, we Make Amazing Happen.
CDW is an equal opportunity employer. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by state and local law.
Description
The Solution Architect is a hybrid technical delivery and client-facing role that spans the full life of an engagement, from the first conversation to successful delivery. When a Client Executive identifies an opportunity, the Solution Architect is the technical expert they bring in to understand the client's real problem, design the right solution, and scope the engagement. Once the deal is signed and depending on the scope of the engagement, the Solution Architect converts to a billable technical lead. The Solution Architect will work with the Delivery Manager to build a team to deliver on their engagement and will provide technical leadership & account management through project completion. Additionally, the Solution Architect should have a “Forward Deployed Engineer” mindset, always looking for new problems we can solve for our clients, ways we can expand our team or scope to deliver an even better solution, and advising our clients on technical strategies that lead to improved business outcomes.
This role is for a builder and an advisor in equal measure. Clients often know what they want but not always what they need, and sometimes what they ask for is not in their best interest. The Solution Architect guides them to the right outcome with credibility, candor, and deep technical judgment, becoming the trusted advisor the client relies on well beyond the initial sale. This role spans the entire project lifecycle and requires the tenacity to not only design and start a project, but to see it through to its successful end.
What you will do
- Partner with Client Executives and Solution Executives to qualify opportunities, lead technical discovery, and uncover the business problem behind the request.
- Facilitate envisioning sessions and workshops that help clients define outcomes, priorities, and a realistic roadmap.
- Design end-to-end solutions and translate them into clear scope, estimates, staffing plans, business outcomes, and risk assessments.
- Architect and co-author high-level designs (HLDs), level-of-effort (LOE) estimates, proposals, statements of work (SOWs), RFP responses, business cases, and client presentations, and serve as a core member of the team that closes the sale.
- Own the commercial soundness of solutions by structuring the engagement staffing mix and delivery approach, including AI-accelerated delivery, to achieve target margin while providing strong client outcomes.
- Identify where AI can create meaningful value for the client, and where it cannot, and shape solutions accordingly.
- Present and defend the solution to client stakeholders and maintain continuity from pursuit through delivery.
- Convert to billable delivery once an engagement is signed, when it makes sense in the project context, serving as technical lead and primary architecture authority for the project.
- Build, onboard, and lead delivery teams, including large teams on multi-million, multi-year engagements; set engineering standards, architecture guardrails, and AI-enabled development practices.
- Assume hands-on design or development responsibilities when needed, particularly during team ramp-up.
- Manage technical risk, scope, and change in partnership with project management and the client, protecting delivery quality and the client relationship.
- Serve as a primary client contact alongside Project and Delivery Managers, transition steady-state leadership appropriately, and continue advising prior engagements as needed.
- Use AI tools, including agentic development workflows, as a core part of how software is designed, built, and delivered.
- Lead teams that build client solutions incorporating AI, from LLM-powered features to agent-based systems, with appropriate attention to quality, security, and responsible use.
- Coach engineers and clients on effective, practical AI adoption and contribute reusable patterns and accelerators to the practice.
- Build external thought leadership through white papers, case studies, conference talks, webinars, and partner events on agentic software development, AI-accelerated delivery, and practical AI adoption.
- undefined
What we expect of you
- Bachelor’s degree and 10+ years of software engineering and architecture experience, including hands-on development in at least one of Java, .NET (C#), Python, or JavaScript/TypeScript OR 14+ years of software engineering and architecture experience, including hands-on development in at least one of Java, .NET (C#), Python, or JavaScript/TypeScript
- 1+ year experience in AI & Agentic Engineering: LLM application design (RAG, tool use, agents, orchestration); model selection and evaluation; responsible AI and guardrails; daily use of AI coding assistants and agentic development tools. Agent harness engineering (e.g., Claude Agent SDK, LangGraph, Microsoft Agent Framework), including tool and MCP integration, context and memory management, sandboxing, permissions, and human-in-the-loop controls; evaluation harnesses for testing and regression-checking model and agent behavior.
- 5+ years of experience in a solution architect, technical lead, or similar role designing solutions that span applications, integration, data, and cloud infrastructure.
- 3+ years of experience in a client-facing consulting or professional services role, including direct participation in pre-sales discovery, solution design, estimation, proposal development, and closing.
- Demonstrated experience developing software using AI tools, ideally including agentic development workflows.
- Experience leading teams that designed and delivered client solutions incorporating AI capabilities.
- Proven ability to lead delivery teams through ambiguity, including ramping teams up and personally filling gaps.
- Exceptional communication skills, with the ability to engage executive stakeholders and engineers and respectfully challenge client assumptions.
- Hands-on depth in at least one and working fluency in another: Cloud Platforms: Microsoft Azure, AWS, and/or Google Cloud; landing zones, compute, networking, identity, cost, and security design.
- Languages & Frameworks: Java, .NET (C#), Python, JavaScript/TypeScript; front-end with React, React Native, and Angular.
- Architecture & Platforms: Microservices, event-driven, and serverless architectures; domain-driven design; modernization and migration patterns; non-functional requirements (scale, resilience, security, cost).
- Integration & APIs: REST and GraphQL API design; API gateways and management; messaging and streaming (e.g., Kafka, Service Bus, SQS/SNS); iPaaS/integration platforms; identity and auth (OAuth 2.0, OIDC).
- Applications: Custom web and mobile applications, enterprise and line-of-business systems, SaaS/platform extensions, and legacy modernization.
- DevOps & Tooling: CI/CD (GitHub Actions, Azure DevOps, GitLab) including mobile CI/CD (Fastlane); Infrastructure as Code and configuration management (Terraform, Bicep, CloudFormation, Ansible); containers and Kubernetes, including Red Hat OpenShift; observability; DevSecOps practices.
- Data-Centric Solutions: Relational and NoSQL data modeling; data pipelines and ETL/ELT; modern data platforms (e.g., Databricks, Snowflake, Fabric); vector databases; data governance as it relates to AI readiness.
- Testing & QA: Test-driven development with a minimum of 90% unit test coverage on all code; unit, integration, end-to-end, and contract testing; test automation frameworks across the stack (e.g., JUnit, xUnit/NUnit, pytest, Jest, Playwright, Cypress, Detox for React Native); coverage and quality gates enforced in CI/CD (e.g., SonarQube); performance and security testing; validation of AI-generated code and AI-powered features.
- Willingness to travel 25%
- Professional or specialty cloud certifications (e.g., Azure Solutions Architect Expert, AWS Solutions Architect Professional, Google Professional Cloud Architect), a plus.
- Professional certifications in AI-enabled development (e.g., Claude Certified Architect, Microsoft Azure AI App and Agent Developer, Microsoft Agentic AI Business Solutions Architect Expert, AWS Certified Generative AI Developer - Professional, Google Cloud Professional Machine Learning Engineer), a plus.
- Experience building production agentic or LLM-based systems, including evaluation, observability, and guardrails, a plus.
- Background in both greenfield builds and legacy modernization or migration efforts, a plus.
- Experience working within a quota-carrying or sales-incentivized structure, a plus.
- Familiarity with Agile delivery methods and consulting engagement models (fixed fee, time and materials, managed capacity), a plus.
Pay range: $156,000 - $240,800 depending on experience and skill set
Annual bonus target of 10% subject to terms and conditions of plan
Benefits overview: https://cdw.benefit-info.com/
Salary ranges may be subject to geographic differentials
CDW is committed to being an AI-fluent organization
We’re looking for people who bring curiosity, a learner’s mindset, and a willingness to engage with ever-evolving technology and tools. We value adopting AI as a partner, openness to experimentation, and a shared interest in learning together on AI. Our goal is to create a culture where AI enhances—not replaces—human creativity and decision-making. You don’t need to be an expert today; what matters is your readiness to explore, adapt, and grow with us as we integrate AI responsibly and effectively into our work.Additionally, CDW is committed to fostering an equitable, transparent, and respectful hiring process for all applicants. During our application process, our goal is to understand your experience, strengths, skills, and qualifications. As an AI forward company, we see AI not just as a tool, but as a catalyst for new ways of thinking, creating, and communicating. We encourage candidates to embrace an AI mindset, one that’s curious, adaptive, and ready to explore what’s possible. We welcome thoughtful use of AI to expand your perspective and elevate how you share your story, while ensuring your application remains rooted in your own background, judgment, and voice.
About Us
CDW is a Fortune 500 technology solutions provider that helps businesses, government, education, and healthcare organizations achieve what’s possible through technology. What makes CDW different isn’t just what we do—it’s how we do it. At CDW we act as one—building trust, speaking candidly, and working together to achieve more. We play to win—focusing on what matters most and delivering for our customers. And we think forward—staying curious, moving fast, and continuously learning. We believe meaningful work happens when people feel supported, heard, and empowered to contribute. That’s why we think of ourselves as coworkers, not just employees—working together to solve complex challenges and deliver real impact for our customers and communities.
As a full‑stack, full‑lifecycle technology partner, CDW brings deep expertise, strong relationships, and broad industry knowledge to help turn ideas into outcomes. When you join CDW, you become part of a collaborative environment where your work matters, your growth is supported, and your contributions help shape what’s next.
Together, we deliver the full promise of what technology can do. Together, we Make Amazing Happen.
CDW is an equal opportunity employer. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by state and local law.
Principal AI Architect Jobs by Experience Level
See All 425+ Principal AI Architect Jobs
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Find Principal AI Architect JobsPrincipal AI Architect Job Market
Who's Hiring
- Booz Allen Hamilton20
- JPMorganChase12
- Boston Consulting10
- Johns Hopkins University Applied Physics Laboratory9
- Genesys7
Top Industries Hiring
- Technology & Software19
- Consulting & Professional Services12
- Education8
- Insurance5
- Banking & Financial Services5
What Employers Look For
The qualifications that appear most often in principal AI architect jobs.
- Ten or more years of experience designing and deploying production machine learning or AI systems
- Deep expertise in large language model architecture, fine-tuning, and inference optimization
- Proficiency with cloud AI platforms such as AWS SageMaker, Google Vertex AI, or Azure Machine Learning
- Experience setting enterprise-wide AI architecture standards and leading cross-functional technical reviews
- Advanced degree in computer science, machine learning, or a closely related quantitative field
- Familiarity with MLOps tooling, model governance frameworks, and responsible AI practices
Tips for Your Principal AI Architect Job Search
Lead your resume with system design
Principal AI Architect roles screen heavily on architectural decision-making, so your resume needs concrete examples of LLM infrastructure choices, tradeoffs you owned, and the scale those systems ran at. Titles and years alone won't get you through.
Distinguish architecture from engineering on paper
Many candidates blur the line between building models and designing the systems those models run inside. Make clear which decisions you owned at the platform or infrastructure layer, not just what you trained or deployed.
Apply early to roles that fit
Migrate Mate lists principal ai architect openings from across the United States in one place, so you can find roles that match your specialization and apply directly to each listing without sorting through unrelated postings.
Target postings by governance maturity
Job descriptions that mention responsible AI, model risk management, or AI policy committees signal a governance-forward environment. If that's your strength, prioritize those openings. If you prefer greenfield infrastructure, look for language around platform buildout or foundation model adoption.
Prepare a system design narrative for interviews
Principal-level interviews almost always include an open-ended architecture exercise. Practice walking through a real design you led, covering data flow, latency constraints, failure modes, and the specific tradeoffs you made rather than an idealized textbook answer.
Negotiate scope before you negotiate compensation
At the principal level, your offer letter's title, reporting line, and decision authority matter as much as pay. Clarify whether you own architectural standards across teams or advise a single product line before the offer stage, not after.
Principal AI Architect Jobs: Frequently Asked Questions
Which companies are hiring the most principal ai architects?
The most active employers for principal ai architects right now are Booz Allen Hamilton, JPMorganChase, and Boston Consulting, and the most openings are in Texas, California, and Virginia, based on current listings on Migrate Mate as of November 2026. Demand is especially strong at large technology companies, financial institutions building internal AI platforms, and healthcare organizations scaling clinical AI infrastructure.
How many principal ai architect jobs are remote?
About 63% of principal ai architect openings are fully remote or hybrid as of November 2026, reflecting strong demand for distributed senior technical talent. Roles focused on LLM platform design and AI governance tend to be the most remote-friendly, while positions requiring hands-on data center or on-premises infrastructure work more often require an on-site presence.
How do you become a principal ai architect?
Most principal ai architects progress from machine learning engineering or software architecture roles, gradually taking ownership of system-level decisions rather than individual model work. Building expertise in infrastructure design, model deployment pipelines, and cross-team technical leadership is essential. Contributing to open-source AI projects, publishing design case studies, and presenting at technical conferences can accelerate the transition into a recognized principal-level role.
Can you get hired as a principal ai architect without prior principal-level experience?
Some candidates move into principal ai architect roles without holding that exact title if they can demonstrate principal-level scope in a previous position. Concrete evidence of owning architectural decisions, influencing engineering standards across multiple teams, and delivering production AI systems at scale carries more weight than a matching title. A strong portfolio of system design work and clear examples of technical leadership often matter more than seniority on paper.
What does the principal ai architect interview process look like?
Most processes include an initial screening conversation, a technical deep-dive on a past architecture you designed, and a live system design exercise focused on AI or machine learning infrastructure. Later rounds typically involve cross-functional interviews with product, engineering leadership, and sometimes legal or compliance stakeholders if the role includes governance responsibilities. Expect to explain architectural tradeoffs in plain language for non-technical audiences.
Where can I find and apply to principal ai architect jobs?
You can find and apply to principal ai architect jobs on Migrate Mate, which lists current openings from across the United States in one place. Search the listings to find roles that match your specialization and experience level, then apply directly to each one that fits.
See All 425+ Principal AI Architect Jobs
Find roles that match your experience and apply in just a few clicks.
Find Principal AI Architect Jobs