Cloud Engineer and Site Reliability (SME) - Senior Manager

EY • Hartford, DC

19d • $144,000 - $374,000 • Hybrid

About The Position

EY is hiring a senior individual contributor to serve as a hands-on technical authority for cloud engineering and site reliability practices supporting AI-enabled services. The role focuses on helping move services from experimentation into secure, observable, recoverable, cost-aware, dependable production use. The position applies AI-assisted engineering tools while independently validating their output, and guides complex architecture, performance, resilience, recovery, and cost decisions across multiple use cases.

The role is part of Challenger, an EY program developing new AI-enabled services. Challenger Core builds and maintains shared technology, methods, and risk and quality guardrails. The successful candidate will develop reusable cloud foundations, production-readiness practices, reliability standards, and tested reference implementations; investigate complex failures; and coach engineers while helping transition proven capabilities to ongoing owners.

The position may be based anywhere in the country, requires up to 50% travel, and calls for flexibility to work in an office in a hybrid capacity. EY lists a base salary range that varies by location: $172,800–$359,000 for New York City, Boston, Washington, DC metro areas, Washington State, and Southern California; $180,000–$374,000 for Bay Area California offices; and $144,000–$329,100 for other U.S. offices, including Sacramento. Individual compensation depends on factors including education, experience, knowledge, skills, and geography.

Requirements

• Bachelor’s degree in a relevant field of study.
• 9–12+ years of relevant experience.
• Substantial experience designing and operating production cloud, infrastructure, platform, or site reliability capabilities.
• A record of solving complex distributed-system problems and explaining why selected solutions will work.
• Hands-on expertise with infrastructure as code, modern runtime platforms, networking, identity, and delivery automation.
• Experience defining service objectives and using observability, capacity planning, and recovery testing to improve live systems.
• Evidence of investigating difficult failures, supporting incident response, and converting lessons into durable remediation.
• Strong coding skills and the ability to independently validate AI-generated or otherwise automated engineering output.
• Experience mentoring engineers and guiding architecture or readiness decisions without relying on formal delivery ownership.
• Ability to travel up to 50% and flexibility to work in an office in a hybrid capacity.

Nice To Haves

• Experience operating model-serving, retrieval, or agent workloads with demanding reliability and performance needs.
• Experience designing portable patterns across cloud, hybrid, or multi-region environments.
• Experience connecting capacity, latency, throughput, and cost to service design and scaling decisions.
• Experience in regulated or confidential environments with formal security, resilience, or evidence requirements.
• Practical contributions to cloud-native, infrastructure, SRE, observability, automation, or open-source communities.

Responsibilities

• Create reusable cloud infrastructure, environment patterns, and deployment automation.
• Use AI tools to accelerate engineering and investigation, then review, debug, test, and validate the resulting work independently.
• Review architectures, migrations, and releases where trade-offs affect reliability, security, performance, cost, or multiple use cases.
• Define evidence required for production launch and identify necessary changes when a service is not operationally ready.
• Establish service objectives, observability standards, actionable alerts, and operational reviews tied to user outcomes.
• Test workload assumptions and use performance, consumption, and demand evidence to guide capacity, scaling, and architecture decisions.
• Lead deep investigations of failures across distributed services and integrations, verify root causes with system evidence, and test durable fixes.
• Design performance tests, failure simulations, recovery exercises, and rollback paths to demonstrate service behavior under stress.
• Publish tested reference implementations, guidance, and runbooks that explain intended use and limitations.
• Coach engineers, challenge assumptions constructively, and transition proven capabilities to ongoing owners with clear operating responsibilities.

Benefits

• Medical coverage
• Dental coverage
• Pension plans
• 401(k) plans
• Flexible vacation policy
• Paid holidays
• Winter and summer breaks
• Personal and family care time off
• Other leaves of absence to support physical, financial, and emotional well-being

What This Job Offers

• Job Type: Full-time
• Career Level: Senior