Lead Applied AI Site Reliability Engineer II - PxE ERM

About the role

The Lead Applied AI Site Reliability Engineer II plays a critical role in ensuring the reliability, performance, and operational integrity of high-visibility products and platforms. This position requires a hands-on approach to managing production environments, setting production standards, and driving operational excellence.

Responsibilities

• Outcome-Driven Accountability: Drive reliability, performance, and cost outcomes measured in service-level objectives and error budgets, ensuring high-quality, lean operational designs that keep production safe and resilient.
• Technical Leadership and Advocacy: Serve as the technical advocate for production reliability and operability, ensuring systems are admissible, performant, safe to run, and can degrade gracefully when failure occurs. Set production standards, lead observability, performance, and resilience testing, and operational tooling, and own the admission of systems into production.
• Engineering Craftsmanship: Maintain accountability for the operational integrity of production and pre-production environments, and for the production standards that systems are admitted against. Own SLOs and error budgets; build and operate production observability; run performance, ambient-noise, and chaos testing to verify readiness; and guard environments against drift.
• Customer-Centric Engineering: Develop lean operational solutions through rapid, inexpensive experimentation to meet the reliability needs of the engineering teams and the business. Engage with teams before, during, and after delivery, co-defining service-level objectives and operational readiness.
• Advanced Technical Proficiency: Possess deep expertise in site reliability and modern production engineering, cloud platform ownership, observability, performance and capacity engineering, chaos engineering, and cloud/AI cost engineering, together with applied AI fluency to operate AI and agentic workloads reliably.
• Domain Expertise: Quickly acquire domain knowledge of the products and platforms you operate, translating reliability needs, reference architectures, and operational requirements into service-level objectives, runbooks, and production tooling.
• Effective Communication and Influence: Exhibit exceptional communication skills, capable of articulating complex technical concepts clearly and compellingly. Inspire and influence teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives.

Qualifications

• A bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline.
• 6+ years of software engineering and site reliability engineering experience operating large-scale, distributed, cloud-native systems in production.
• Experience in defining and owning SLIs, SLOs, and SLAs; error budgets; incident command and on-call; building and operating production observability; environment integrity and drift prevention; and segregation-of-duties controls in partnership with security and risk.
• Experience with cloud-native engineering and cloud platform ownership on any of the cloud hyperscalers such as Azure, AWS, or GCP, including their AI/ML services and container orchestration.
• Experience with reliability and operational standards, SLO discipline, runbooks, and performance and resilience budgets, including actively leading, mentoring, and guiding team members in the adoption and continuous improvement of these standards.
• Prior experience operating AI/ML and agentic workloads in production, their reliability failure modes, MLOps/LLMOps, and the AI control plane.
• Experience with load and performance testing under simulated production traffic, chaos engineering, capacity planning, autoscaling, and cloud/AI cost engineering.
• Experience with methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks.
• Ability to work in your local office at a minimum of 3 days per week.

Benefits

Deloitte offers a comprehensive benefits package, including health insurance, retirement plans, and paid time off.

Pay

$113,100 to $232,300 annually.

Schedule

Flexible schedule to accommodate remote work and office attendance.