Senior Cloud Reliability Engineer — AI‑Driven Production

EY; McLean (VA); Hybrid; USD 144,000 - 329,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Flexible vacation policy

Job summary

EY is seeking a senior individual contributor in Challenger to build secure, observable, and cost-aware cloud foundations for AI-enabled services. You will serve as the hands-on technical authority for engineering practices guiding architecture, performance, resilience, and cost across multiple use cases.

You will use AI-assisted tooling to accelerate infrastructure, verify results, and mentor teams, with up to 50% travel and hybrid office flexibility in the US.

Qualifications

• Bachelor’s Degree in a relevant field of study.
• 9-12+ years of relevant experience.
• Substantial experience designing and operating cloud, infrastructure, platform, or site reliability capabilities in production.
• A record of solving complex distributed-system problems and explaining why the chosen solution 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.
• Strong coding skills and the ability to validate AI-generated or otherwise automated engineering output independently.
• Experience mentoring engineers and guiding architecture or readiness decisions without relying on formal delivery ownership.
• This role requires up to 50% travel and flexibility to go into the office in a hybrid capacity.

Responsibilities

• Build shared cloud foundations. Create reusable infrastructure, environment patterns, and deployment automation that help teams start quickly and operate consistently.
• Use AI-assisted engineering responsibly. Apply AI tools to accelerate development and investigation while independently reviewing, debugging, testing, and validating the resulting code.
• Guide complex designs. Review architectures, migrations, and releases where trade-offs affect reliability, security, performance, cost, or multiple use cases.
• Strengthen production readiness. Define the evidence required before launch and identify what must change when a service is not ready to operate reliably.
• Set reliability practices. Establish service objectives, observability standards, actionable alerts, and operational reviews that connect system behavior to user outcomes.
• Make cost and capacity visible. Test workload assumptions and use performance, consumption, and demand evidence to guide scaling and architecture decisions.
• Resolve difficult failures. Lead deep investigation across distributed services and integrations, verify root causes against system evidence, and test durable fixes.
• Prove resilience. Design performance tests, failure simulations, recovery exercises, and rollback paths that show how services behave under stress.
• Turn lessons into reusable capabilities. Publish tested reference implementations, guidance, and runbooks that state both the intended use and important limitations.
• Raise engineering capability. Coach engineers, challenge assumptions constructively, and transition proven capabilities to ongoing owners with clear operating responsibilities.

Skills

Deep cloud expertise

Hands-on engineering

Diagnostic judgment

Reliability leadership

AI workload awareness

Technical influence

Education

Bachelor’s Degree in a relevant field of study

Job description

EY is seeking a senior individual contributor in Challenger to build secure, observable, and cost-aware cloud foundations for AI-enabled services. You will serve as the hands-on technical authority for engineering practices guiding architecture, performance, resilience, and cost across multiple use cases.

You will use AI-assisted tooling to accelerate infrastructure, verify results, and mentor teams, with up to 50% travel and hybrid office flexibility in the US.