Senior Applied AI SRE - Production Reliability & Observability

Relha LLC; Northern (KY); Hybrid; USD 130,000 - 180,000; Full time

Job summary

Deloitte seeks an Applied AI Site Reliability Engineer III to strengthen reliability, performance, and cost efficiency across AI platforms and production environments. You will lead observability design, implement automated reliability checks, and collaborate with cross‑functional teams to uphold production standards.

Required are 5+ years in software/SRE, 3+ years in cloud-native engineering across AWS/Azure/GCP, and experience with AI/ML workloads in production and MLOps.

Qualifications

• 5+ years of software engineering and site reliability experience in large-scale, cloud-native systems.
• 3+ years of SRE/production engineering owning SLIs, SLOs and incident response.
• 3+ years of cloud-native engineering on Azure/AWS/GCP including Kubernetes, IaC and multi-environment management.
• Experience operating AI/ML workloads in production and knowledge of MLOps/LLMOps.

Responsibilities

• Own reliability, performance, and cost outcomes with SLOs and error budgets.
• Lead observability design, performance testing, and operational tooling for production systems.
• Maintain production readiness including runbooks, automation, and incident postmortems.
• Collaborate with cross-functional teams to ensure safety, reliability, and cost efficiency.
• Drive continuous improvement through disciplined release and governance practices.

Skills

Python

Go

Bash

Java

C#/.NET

SQL/NoSQL

Kubernetes

Terraform

ArgoCD

CI/CD

Observability

Education

Bachelor’s degree in CS/Software/Data/ML

Tools

OpenTelemetry

Prometheus

Grafana

Datadog

Dynatrace

CloudWatch/Azure Monitor/GCP Operations

Job description

Deloitte seeks an Applied AI Site Reliability Engineer III to strengthen reliability, performance, and cost efficiency across AI platforms and production environments. You will lead observability design, implement automated reliability checks, and collaborate with cross‑functional teams to uphold production standards.

Required are 5+ years in software/SRE, 3+ years in cloud-native engineering across AWS/Azure/GCP, and experience with AI/ML workloads in production and MLOps.