Customer AI Solution Architect

Deloitte US · Multiple Locations · $141,200–$278,300 (stated in the posting)

Lead the design and delivery of artificial intelligence (AI)-enabled customer experiences across marketing, commerce, sales, and service. As a Customer AI Solution Architect, you will help clients identify AI use cases, design solutions that align with front-office platforms and operating models, and guide delivery from prototypes to production. You will act as a senior individual contributor with client technology executives and architects while leading a Deloitte team of developers and engineers through delivery. You will also establish reusable architecture patterns and engineering standards that support delivery across programs.

Recruiting for this role ends on January 27, 2027

Work you'll do

As a Customer AI Solution Architect, you will be responsible for designing and delivering AI-enabled customer experiences from discovery through production. You will…

Architect agentic customer experiences for marketing, commerce, sales, and service, including customer assistants, conversational commerce, personalization, sales enablement, and support experiences.
Design agentic systems that address orchestration, planning, tool use, state management, retrieval, memory, model selection, routing, failure handling, and cost management; determine when agentic approaches add value over deterministic workflows.
Integrate AI solutions with front-office platforms and enterprise services using composable, headless, application programming interface (API)-led, and event-driven architectures; account for identity, consent, real-time data, security, and experience latency.
Embed oversight and safeguards through human approvals, escalation and override paths, scoped permissions, prompt-injection defenses, personally identifiable information (PII) handling, audit logging, and privacy and data-residency controls.
Lead architecture and security reviews with client stakeholders, resolve design issues, and coach technical teams on reference architectures, reusable patterns, and engineering standards.
Lead and manage a Deloitte team of developers and engineers: set technical direction, plan and assign work, run design and code reviews, manage delivery quality and risk, and develop team members through coaching and feedback.
Lead rapid prototypes and production delivery using AI-accelerated engineering practices; establish practices for AI evaluation, regression testing, observability, drift and latency monitoring, cost tracking, and continuous integration and continuous delivery (CI/CD); and partner with stakeholders to prioritize use cases, define AI-enabled and AI-native experiences, and connect delivery to business and customer outcomes.

A successful candidate would possess these skills:

Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead and manage technical teams, projects, or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to mentor and provide clear guidance to others

The Team

Deloitte's Advertising, Marketing and Commerce team creates content and experiences that inspire action. We design and implement technology platforms for personalized marketing across all digital touchpoints, specializing in customer-centric B2B and B2C solutions. Our in-house agency engages customers throughout their journey, working on projects like AdTech, MarTech, campaign automation, CRM, and lead-to-loyalty orchestration. Join us to drive impactful customer interactions and business growth.

Qualifications

Required:

6+ years of experience architecting and delivering high-performance enterprise technology solutions (for example, web, mobile, commerce, CRM, or integration platforms), including work that predates generative AI.
Hands-on experience designing and delivering two or more artificial intelligence (AI) solutions or agentic systems deployed in production and used by real customers or employees, in one or more of marketing, commerce, sales, or service.
Hands-on experience designing agentic systems deployed in production that include orchestration, tool integration, retrieval augmented generation (RAG), context assembly, agent memory, model selection, routing, and failure handling.
Hands-on production experience with at least one agent framework, such as LangGraph, Google Agent Development Kit (ADK), Claude Agent Software Development Kit (SDK), or Amazon Bedrock AgentCore, and foundation-model application programming interfaces (APIs) for prompt and context engineering, structured outputs, tool use, prompt versioning, or model evaluation.
Hands-on experience integrating deployed AI solutions with enterprise platforms through APIs or event-driven architectures and addressing identity, consent, real-time data, security, privacy, and data-residency requirements.
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Preferred:

Experience designing conversational or agentic customer experiences that include brand-safety controls, trust controls, response-latency measurement, and customer-experience measurement.
Assess and benchmark software products, models, and technology options.
Experience measuring discoverability in AI-powered answer and discovery experiences.
Experience applying AI coding or design agents and agentic software development lifecycle (SDLC) practices with documented delivery-speed or quality measures.
Experience taking prototypes or pilots into production with adoption and operating plans.
Experience with customer data, identity resolution, and consent management for personalization and AI-driven decisions.
Experience presenting AI architecture choices and trade-offs to chief technology officers (CTOs), chief data officers (CDOs), or chief marketing officers (CMOs).

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $141,200 to $278,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#Customer_US

#AMC_US

Recruiting for this role ends on January 27, 2027

Work you'll do

As a Customer AI Solution Architect, you will be responsible for designing and delivering AI-enabled customer experiences from discovery through production. You will…

Architect agentic customer experiences for marketing, commerce, sales, and service, including customer assistants, conversational commerce, personalization, sales enablement, and support experiences.
Design agentic systems that address orchestration, planning, tool use, state management, retrieval, memory, model selection, routing, failure handling, and cost management; determine when agentic approaches add value over deterministic workflows.
Integrate AI solutions with front-office platforms and enterprise services using composable, headless, application programming interface (API)-led, and event-driven architectures; account for identity, consent, real-time data, security, and experience latency.
Embed oversight and safeguards through human approvals, escalation and override paths, scoped permissions, prompt-injection defenses, personally identifiable information (PII) handling, audit logging, and privacy and data-residency controls.
Lead architecture and security reviews with client stakeholders, resolve design issues, and coach technical teams on reference architectures, reusable patterns, and engineering standards.
Lead and manage a Deloitte team of developers and engineers: set technical direction, plan and assign work, run design and code reviews, manage delivery quality and risk, and develop team members through coaching and feedback.
Lead rapid prototypes and production delivery using AI-accelerated engineering practices; establish practices for AI evaluation, regression testing, observability, drift and latency monitoring, cost tracking, and continuous integration and continuous delivery (CI/CD); and partner with stakeholders to prioritize use cases, define AI-enabled and AI-native experiences, and connect delivery to business and customer outcomes.

A successful candidate would possess these skills:

Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead and manage technical teams, projects, or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to mentor and provide clear guidance to others

The Team

Qualifications

Required:

6+ years of experience architecting and delivering high-performance enterprise technology solutions (for example, web, mobile, commerce, CRM, or integration platforms), including work that predates generative AI.
Hands-on experience designing and delivering two or more artificial intelligence (AI) solutions or agentic systems deployed in production and used by real customers or employees, in one or more of marketing, commerce, sales, or service.
Hands-on experience designing agentic systems deployed in production that include orchestration, tool integration, retrieval augmented generation (RAG), context assembly, agent memory, model selection, routing, and failure handling.
Hands-on production experience with at least one agent framework, such as LangGraph, Google Agent Development Kit (ADK), Claude Agent Software Development Kit (SDK), or Amazon Bedrock AgentCore, and foundation-model application programming interfaces (APIs) for prompt and context engineering, structured outputs, tool use, prompt versioning, or model evaluation.
Hands-on experience integrating deployed AI solutions with enterprise platforms through APIs or event-driven architectures and addressing identity, consent, real-time data, security, privacy, and data-residency requirements.
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Preferred:

Experience designing conversational or agentic customer experiences that include brand-safety controls, trust controls, response-latency measurement, and customer-experience measurement.
Assess and benchmark software products, models, and technology options.
Experience measuring discoverability in AI-powered answer and discovery experiences.
Experience applying AI coding or design agents and agentic software development lifecycle (SDLC) practices with documented delivery-speed or quality measures.
Experience taking prototypes or pilots into production with adoption and operating plans.
Experience with customer data, identity resolution, and consent management for personalization and AI-driven decisions.
Experience presenting AI architecture choices and trade-offs to chief technology officers (CTOs), chief data officers (CDOs), or chief marketing officers (CMOs).

#Customer_US

#AMC_US

Recruiting for this role ends on January 27, 2027

Work you'll do

As a Customer AI Solution Architect, you will be responsible for designing and delivering AI-enabled customer experiences from discovery through production. You will…

Architect agentic customer experiences for marketing, commerce, sales, and service, including customer assistants, conversational commerce, personalization, sales enablement, and support experiences.
Design agentic systems that address orchestration, planning, tool use, state management, retrieval, memory, model selection, routing, failure handling, and cost management; determine when agentic approaches add value over deterministic workflows.
Integrate AI solutions with front-office platforms and enterprise services using composable, headless, application programming interface (API)-led, and event-driven architectures; account for identity, consent, real-time data, security, and experience latency.
Embed oversight and safeguards through human approvals, escalation and override paths, scoped permissions, prompt-injection defenses, personally identifiable information (PII) handling, audit logging, and privacy and data-residency controls.
Lead architecture and security reviews with client stakeholders, resolve design issues, and coach technical teams on reference architectures, reusable patterns, and engineering standards.
Lead and manage a Deloitte team of developers and engineers: set technical direction, plan and assign work, run design and code reviews, manage delivery quality and risk, and develop team members through coaching and feedback.
Lead rapid prototypes and production delivery using AI-accelerated engineering practices; establish practices for AI evaluation, regression testing, observability, drift and latency monitoring, cost tracking, and continuous integration and continuous delivery (CI/CD); and partner with stakeholders to prioritize use cases, define AI-enabled and AI-native experiences, and connect delivery to business and customer outcomes.

A successful candidate would possess these skills:

Ability to work independently and collaborate as part of a team
Effective written and verbal communication skills
Meticulous attention to detail and quality of work product
Ability to build and sustain professional relationships
Ability to lead and manage technical teams, projects, or workstreams
Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
Strong interpersonal skills and professional demeanor
Ability to meet deadlines
Ability to mentor and provide clear guidance to others

The Team

Qualifications

Required:

6+ years of experience architecting and delivering high-performance enterprise technology solutions (for example, web, mobile, commerce, CRM, or integration platforms), including work that predates generative AI.
Hands-on experience designing and delivering two or more artificial intelligence (AI) solutions or agentic systems deployed in production and used by real customers or employees, in one or more of marketing, commerce, sales, or service.
Hands-on experience designing agentic systems deployed in production that include orchestration, tool integration, retrieval augmented generation (RAG), context assembly, agent memory, model selection, routing, and failure handling.
Hands-on production experience with at least one agent framework, such as LangGraph, Google Agent Development Kit (ADK), Claude Agent Software Development Kit (SDK), or Amazon Bedrock AgentCore, and foundation-model application programming interfaces (APIs) for prompt and context engineering, structured outputs, tool use, prompt versioning, or model evaluation.
Hands-on experience integrating deployed AI solutions with enterprise platforms through APIs or event-driven architectures and addressing identity, consent, real-time data, security, privacy, and data-residency requirements.
Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.

Preferred:

Experience designing conversational or agentic customer experiences that include brand-safety controls, trust controls, response-latency measurement, and customer-experience measurement.
Assess and benchmark software products, models, and technology options.
Experience measuring discoverability in AI-powered answer and discovery experiences.
Experience applying AI coding or design agents and agentic software development lifecycle (SDLC) practices with documented delivery-speed or quality measures.
Experience taking prototypes or pilots into production with adoption and operating plans.
Experience with customer data, identity resolution, and consent management for personalization and AI-driven decisions.
Experience presenting AI architecture choices and trade-offs to chief technology officers (CTOs), chief data officers (CDOs), or chief marketing officers (CMOs).

#Customer_US

#AMC_US

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