DE
Full time
🤖 AI / ML
DevOps Engineer II (Applied AI Site Reliability Engineer) at Deloitte
Listed by DevShelfHub
India (USI)
Hybrid
Mid-level · 4–8 yrs
About the Role
Deloitte is hiring an Applied AI Site Reliability Engineer II to drive reliability, performance, and operational integrity of high-visibility products and platforms. This role is part of US Deloitte Technology Product Engineering, delivering innovative digital solutions to businesses and internal operations.
This role requires 4+ years of software engineering and SRE experience operating large-scale, distributed, cloud-native systems in production.
What you'll do
- You will keep production safe, performant, and cost-effective while supporting admission of systems into production.
- Embrace accountability for reliability, performance, and cost outcomes measured in SLOs and error budgets
- Serve as technical advocate for production reliability, operability, and graceful degradation
- Maintain operational integrity of production and pre-production environments
- Build and operate codified, version-controlled observability dashboards and SLO-driven alerting
- Run performance, ambient-noise, and chaos testing to verify readiness
- Guard environments against drift and enforce segregation-of-duties controls
- Create technical specifications, runbooks, and shared playbooks
- Lead blameless postmortems that turn incidents into systemic fixes
- Develop lean operational solutions through rapid experimentation
- Co-define service-level objectives and verify operational readiness with product teams
- Operate AI/ML and agentic workloads reliably including drift, train/serve skew, and cost anomalies
What we're looking for
- Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline
- 4+ years software engineering and SRE experience operating large-scale, distributed, cloud-native systems in production
- Experience with Python, Go, Bash, Java, C#/.NET, SQL/NoSQL, Kubernetes, Terraform, ArgoCD, CI/CD, and observability stacks
- 2+ years SRE or production engineering: SLIs, SLOs, SLAs, error budgets, incident command, on-call
Skills & Technologies
Required
Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline
4+ years software engineering and SRE experience operating large-scale, distributed, cloud-native systems in production
Experience with Python, Go, Bash, Java, C#/.NET, SQL/NoSQL, Kubernetes, Terraform, ArgoCD, CI/CD, and observability stacks
2+ years SRE or production engineering: SLIs, SLOs, SLAs, error budgets, incident command, on-call
Production observability: OpenTelemetry, Prometheus, Grafana, Datadog, CloudWatch, Azure Monitor, Splunk
2+ years cloud-native engineering on Azure, AWS, or GCP including AI/ML services
Operating AI/ML and agentic workloads in production with MLOps/LLMOps experience
Load and performance testing (k6, JMeter), chaos engineering, capacity planning, FinOps
Benefits & Perks
- Health Insurance
- Flexible Leave Policy
- Learning Budget
- EPF / NPS
Why This Role is Good for Experienced Professionals
- This role offers SRE leadership for AI and agentic workloads alongside cloud-native platform engineering at global scale.
- Drive culture of accountability for reliability, performance, and cost through SLOs and error budgets
- Serve as technical advocate for production reliability and operability
- Build and operate production observability with SLO-driven alerting
- Run performance, ambient-noise, and chaos testing to verify readiness
- Operate AI/ML and agentic workloads including MLOps/LLMOps failure modes
- Apply cloud platform ownership on Azure, AWS, or GCP including AI/ML services
- Lead blameless postmortems and write high-quality reliability automation
- Co-define service-level objectives with engineering teams
- Hands-on infrastructure-focused engineering with continuous learning
- Collaborate with platform engineering, security, and product teams
About Deloitte
US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model focused on value and outcomes. Product Engineering delivers innovative digital solutions and serves as the engine that drives Deloitte's success.
- Industry
- Technology
- Company Size
- 500+
- Website
- deloitte.com
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Job Details
- Type
- Full time
- Level
- Mid-level
- Experience
- 4–8 years
- Location
- India (USI)
- Work Mode
- Hybrid
- Category
- AI / ML
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