Overview

Applied AI Site Reliability Engineer III

Responsibilities

• Embrace and drive a culture of accountability for reliability, performance, and cost outcomes, measured in service-level objectives and error budgets, not raw uptime. Operate the products, platforms, and environments you support to meet their SLOs within budget, and track incident trends and toil to prioritize the work that most improves reliability—ensuring high-quality, lean operational designs that keep production safe and resilient.
• Develop lean operational solutions through rapid, inexpensive experimentation to meet the reliability needs of the engineering teams and the business. Engage with those teams before, during, and after delivery, co-defining service-level objectives and operational readiness so the right safeguards are in place at the right time, without becoming a bottleneck to delivery.
• Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, hardening reliability through incremental, measurable improvements—progressive resilience testing and SLO refinement—rather than big-bang interventions, and keeping operations supportable and maintainable.
• 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.
• Engage and collaborate with product engineering teams at all organizational levels, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions.
• The successful candidate will possess:
• § Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.

Qualifications

• § A bachelor’s degree in computer science, software engineering, data science, machine learning, or related discipline. Experience is the most relevant factor.
• § 5+ years of software engineering and site reliability engineering experience operating large-scale, distributed, cloud-native systems in production, with experience in most of the following: Python, Go, Bash, Java, C#/.NET, SQL/NoSQL, Kubernetes, Terraform, ArgoCD, as well as CI/CD and observability stacks.
• § 3+ years of 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 such as Azure OpenAI, AWS Bedrock, or Vertex AI—plus container orchestration (Kubernetes, Docker), infrastructure-as-code, networking, and multi-environment management.
• § Prior experience operating AI/ML and agentic workloads in production—their reliability failure modes (drift, train/serve skew, output variance), MLOps/LLMOps, and the AI control plane (model/LLM gateway, guardrails) from the operability and performance side.
• § Prior experience with load and performance testing under simulated production traffic (e.g., LoadRunner, k6, or JMeter), chaos engineering (e.g., Azure Chaos Studio, AWS Fault Injector), capacity planning, autoscaling, and cloud/AI cost engineering (FinOps tooling/dashboards, including GPU/inference and token cost attribution).
• § Prior software engineering experience with the understanding of Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentations, and AI-augmented spec-driven development.
• § Prior experience using methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (e.g. LangFuse, LangSmith, or equivalent multi-agent orchestration tools) etc. to operate high-quality, resilient platforms and products at scale.
• Ability to travel 10%, on average, based on the work you do and products you build.
• Limited immigration sponsorship may be available.
• Our purpose
• Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities.
• Our people and culture
• Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ways of thinking, ideas and perspectives, and bring more creativity and innovation to help solve our clients’ most complex challenges. This makes Deloitte one of the most rewarding places to work.
• Professional development
• At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India.

Benefits

• Recruiting tips
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• Requisition code: 363693