AI Native Cloud and Platform Architect - Senior Manager

EY; Irvine (CA); Híbrido; USD 144.000 - 329.000; Jornada completa

Descripción de la vacante

EY seeks a senior AI platform architect to shape a scalable platform across cloud and hybrid environments, owning the vision, architecture, and non-functional standards for production AI workloads. You will drive portable model access, automated delivery, and evidence‑based releases while balancing cost, reliability, and performance.

You will mentor engineers and SREs, guide build‑versus‑buy decisions, and collaborate with security, risk, and finance partners in a hybrid, travel‑heavy role.

Formación

• Bachelor’s Degree in a relevant field.
• 9–12+ years of relevant experience.
• Substantial experience designing and operating cloud, infrastructure, SRE, or platform capabilities, including production AI workloads.
• A record of building a shared platform adopted by multiple product teams, with measurable improvement in speed, reliability, or cost.
• Deep experience in at least one major cloud and portable patterns for hybrid or multi-cloud constraints.
• Hands-on depth in orchestration, networking, identity, infrastructure as code, delivery automation, APIs, and production observability.
• AI operations: release controls, evaluation, capacity, service objectives, and incident learning.
• Architecture judgment: build-versus-buy decisions with clear implications.
• Cross-functional leadership: leading programs and mentoring teams.

Responsabilidades

• Set the platform direction. Own the AI platform vision, reference architecture, roadmap, and non-functional standards across cloud, hybrid, and edge environments.
• Run the platform as a product. Define service tiers, golden paths, prioritize the roadmap, and measure adoption and time to value.
• Enable portable model access. Design gateways and stable contracts that support model choice and controlled experimentation.
• Architect elastic foundations. Shape compute, storage, and network for AI workloads with cost and resilience in mind.
• Automate the path to production. Create repeatable patterns with progressive release, rollback, and evidence.
• Define trusted agent runtimes. Establish secure execution patterns for tools, identities, approvals, isolation, and replay.
• Engineer for reliability. Set service objectives and observability standards for measurable platform health.
• Make economics visible. Connect usage and quality signals to improve unit economics without hurting reliability.
• Guide strategic choices. Lead build-versus-buy and portability decisions with stakeholders.
• Build capability. Mentor platform engineers and SREs to turn emerging tech into reusable patterns.

Conocimientos

Systems architecture

AI platform depth

Platform product mindset

Operational excellence

Trust by design

Influential leadership

Travel and on-site requirements

Educación

Bachelor’s Degree in a relevant field

Descripción del empleo

Location: Anywhere in Country

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

The opportunity

The next generation of AI services needs a platform that can absorb rapid change without passing every new model, runtime, and control challenge to delivery teams. You will architect that foundation, bringing portable model access, dependable agent execution, automated release evidence, deep observability, and elastic infrastructure into one coherent product.

This is a high-impact role for a systems thinker who wants to stay close to code, telemetry, capacity, and users. You will shape durable patterns across cloud and hybrid environments, align senior stakeholders on practical trade-offs, and make the trusted route from an idea to a production outcome the route teams naturally choose.

About Challenger

Challenger is a new EY program focused on building the firm’s next generation of services. It pursues opportunities where AI enables a fundamentally different service and way of delivering it, including rethinking existing offerings and developing new ones.

Small, dedicated teams build and test ideas in real conditions. Solutions that demonstrate clear business value and operational readiness transition to the business for adoption and scale.

Challenger Core develops and maintains the shared technology, methods, and risk and quality guardrails that support this work. Each team contributes reusable tools and practices, helping make the next service faster and less costly to build.

Your Key Responsibilities

• Set the platform direction. Own the AI platform vision, reference architecture, roadmap, and non-functional standards across cloud, hybrid, and approved edge environments.
• Run the platform as a product. Understand developer needs, define clear service tiers and golden paths, prioritize the roadmap, and measure adoption and time to value.
• Enable portable model access. Design gateways and stable contracts that support model choice, policy-aware routing, resilience, and controlled experimentation without hiding important trade-offs.
• Architect elastic foundations. Shape the compute, storage, and network capabilities needed for AI workloads, balancing performance, regional constraints, resilience, and cost.
• Automate the path to production. Create repeatable delivery patterns that promote code and AI assets together, with progressive release, rollback, and evidence built into the process.
• Define trusted agent runtimes. Establish secure execution patterns for tools, identities, approvals, isolation, recovery, and replay so agent behavior remains controlled and understandable.
• Engineer for reliability. Set service objectives, observability standards, recovery patterns, and resilience exercises that make platform health measurable and operationally useful.
• Make economics visible. Connect usage, performance, and quality signals so teams can improve unit economics without weakening reliability or user outcomes.
• Guide strategic choices. Lead build-versus-buy and portability decisions with engineering, product, security, risk, procurement, and finance partners.
• Build capability. Mentor platform engineers and SREs, strengthen architecture practices, and help teams turn emerging technology into reusable production patterns.

Skills And Attributes For Success

• Systems architecture: Deep understanding of distributed systems and cloud-native architecture, with sound judgment about where abstraction creates value or hidden coupling.
• AI platform depth: Strong knowledge of model serving, inference gateways, AI lifecycle automation, evaluation integration, and agent runtime patterns.
• Platform product mindset: Ability to turn developer needs into intuitive self-service capabilities, durable interfaces, and an adoption-focused roadmap.
• Operational excellence: Practical command of observability, SRE, performance, capacity, resilience, recovery, and incident learning.
• Trust by design: Ability to embed security, policy, delivery assurance, and traceable evidence into platform architecture and engineering workflows.
• Influential leadership: Clear communication, pragmatic decision-making, and the ability to align executives and technical teams around complex trade-offs.

To qualify you must have

• Bachelor’s Degree in a relevant field of study.
• 9-12+ years of relevant experience.
• Relevant experience: Substantial experience designing and operating cloud, infrastructure, SRE, or platform capabilities, including responsibility for production AI workloads.
• Platform delivery: A record of building a shared platform adopted by multiple product teams, with measurable improvement in speed, reliability, or cost.
• Cloud architecture: Deep experience in at least one major cloud and strong judgment about portable patterns for hybrid or multi-cloud constraints.
• Hands-on engineering: Practical depth in orchestration, networking, identity, infrastructure as code, delivery automation, APIs, and production observability.
• AI operations: Experience operating model-serving and AI lifecycle capabilities, including release controls, evaluation, capacity, service objectives, and incident learning.
• Architecture judgment: Demonstrated ability to make build-versus-buy decisions and explain the operational, commercial, and technical consequences.
• Cross-functional leadership: Experience leading complex programs, influencing senior stakeholders, and raising engineering capability through mentoring.
• Travel and On-site requirements: This role requires up to 50% travel and flexibility to go into the office in a hybrid capacity.

Ideally, you’ll also have

• Inference at scale: Experience operating high-volume or latency-sensitive inference and optimizing accelerator capacity across regions or environments.
• Agent platforms: Experience with agent runtimes, tool gateways, sandboxed execution, or policy-aware multi-agent environments.
• Cost and performance: Practical FinOps and performance-engineering experience for AI or other compute-intensive workloads.
• Industry contribution: Contributions to cloud-native, observability, AI platform, interoperability, open-source, standards, or research communities.
• Broader perspective: Experience translating emerging capabilities across multiple providers or technology ecosystems into stable enterprise patterns.

We welcome exceptional candidates from product, service design, operations, transformation, policy, domain, and entrepreneurial backgrounds; no particular degree or certification is required.

What We Offer You

• We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job is:
  • New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $172,800 to $359,000
  • Bay Area California offices – $180,000 to $374,000
  • All other offices locations in the US, including Sacramento – $144,000 to $329,100
• Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
• Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.

At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment and an inclusive culture. Learn more at ey.com/us/careers.

EY | Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

All in to shape the future with confidence.

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