DevOps Engineer - Project Delivery Senior Analyst

Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced
DevOps Engineer
you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. If so, consider an opportunity with Deloitte under our Project Delivery Talent Model. Project Delivery Model (PDM) is a talent model that is tailored specifically for long-term, onsite client service delivery.
Work You'll Do/Responsibilities

• Build, maintain, and improve CI/CD pipelines (Tekton) to support consistent build, test, and deployment of data science/ML workloads.
• Containerize applications and model services using Docker; manage images, registries, and runtime configuration.
• Deploy and operate workloads on Kubernetes (jobs/services/ingress, configmaps/secrets, scaling) across dev/test/prod environments.
• Troubleshoot Linux, container, and cluster issues end-to-end; perform root-cause analysis and implement durable fixes.
• Partner with data scientists and engineers to productionize analytics/ML solutions with reliable runtime, monitoring, and repeatable releases.
• Implement basic operational standards (logging/metrics, alerting, runbooks, access controls) to improve reliability and supportability.
• Automate routine platform tasks using scripting and standard tooling; continuously reduce manual effort.
• Document solutions and share knowledge; proactively "navigate for solutions" when requirements or failures are ambiguous.
• Documentation & Knowledge Sharing: Create and maintain comprehensive documentation for cloud architectures, configurations, and operational procedures.
• Independently and collaboratively lead client engagement workstreams focused on improvement, optimization, and transformation of processes including implementing leading practice workflows, addressing deficits in quality, and driving operational outcomes

T
he Team
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Engineering - Industry Solutions teams works with the Customer group to bring a flexible capability and fluid capacity model to the delivery of small technology projects and enhancements.
Required Qualifications

• 3+yrs Hands-on experience with Linux administration and troubleshooting (process, networking basics, permissions, services).
• 3+yrs Docker experience (image builds, debugging, registries, best practices).
• 3+yrs Kubernetes experience (deployments/jobs, services, ingress, configmaps/secrets, troubleshooting and scaling).
• Experience building or operating Tekton pipelines/tasks (or closely related Kubernetes-native CI/CD).
• Demonstrated ability to independently investigate issues, synthesize options, and drive solutions to closure.
• Experience with Git and standard SDLC practices (tickets, code review participation, documentation)
• Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
• Limited immigration sponsorship may be available
• Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve

Preferred Qualifications

• Exposure to ML/data workloads in Kubernetes (batch jobs, model serving, feature/data pipelines).
• Familiarity with Helm/Kustomize, GitOps (Argo CD/Flux), and infrastructure automation (Terraform/Ansible).
• Observability tooling experience (Prometheus/Grafana, ELK/OpenSearch) and incident response practices.
• Scripting in Bash/Python for automation and tooling.