US E-Consulting Services - PROJECT - Software Engineer II - DevOps Engineer - AI&E - Engineering as a Service - Project (366733)

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

• As a DevOps Engineer, you will architect, automate, and manage secure cloud infrastructures and deployment pipelines for financial services clients. In this client-facing technical role, you will bridge the gap between software development and IT operations to accelerate software delivery and ensure enterprise-grade system reliability. You will leverage modern Infrastructure as Code (IaC) principles, container orchestration, and Continuous Integration/Continuous Deployment (CI/CD) automation to build highly scalable, resilient environments. By standardizing deployment workflows and embedding security best practices, you will empower engineering teams to deliver high-quality financial applications rapidly and safely.
• CI/CD Automation & Orchestration: Design, build, and maintain robust Continuous Integration/Continuous Deployment (CI/CD) pipelines using Jenkins and/or Tekton to fully automate software delivery lifecycles for client applications.
• Containerization & OpenShift/Kubernetes Management: Architect and manage highly available containerized environments. Deploy, configure, and scale applications utilizing Kubernetes and Red Hat OpenShift across complex enterprise architectures.
• Infrastructure as Code (IaC): Provision, manage, and scale cloud infrastructure and platform resources automatically by utilizing IaC methodologies, specifically leveraging Terraform and Helm.
• Cloud Architecture & Strategy: Partner with client stakeholders and engineering teams to design secure, scalable, and fault-tolerant cloud architectures within hybrid or multi-cloud environments.
• OS & Server Administration: Administer, configure, and troubleshoot Linux-based server environments, with a strong emphasis on Red Hat Enterprise Linux (RHEL) administration and tuning.
• Cross-Functional Collaboration: Act as the technical liaison between development, QA, and security teams to resolve deployment bottlenecks, enforce architectural standards, and drive a culture of continuous improvement.
• Documentation & Knowledge Sharing: Create and maintain comprehensive documentation for cloud architectures, configurations, and operational procedures. Mentor junior engineers and contribute to knowledge sharing within the team. Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
• 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

The 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 - EaaS teams works with the Customer group to bring a flexible capability and fluid capacity model to the delivery of small technology projects and enhancements.

Qualifications

Required

• 3+yrs of dedicated professional experience in DevOps engineering, cloud architecture, or site reliability engineering, with a proven track record of delivering infrastructure solutions in a client-facing or enterprise environment.
• CI/CD Automation Proficiency: Extensive, hands-on experience building and optimizing automated deployment pipelines utilizing Jenkins and/or Tekton.
• Container Orchestration: Strong technical expertise in configuring, scaling, and managing containerized applications using Kubernetes and OpenShift.
• Infrastructure as Code (IaC): Deep practical experience writing and maintaining infrastructure code utilizing Terraform and managing Kubernetes package deployments via Helm.
• Cloud Architecture: Demonstrated experience designing, provisioning, and supporting scalable cloud architectures (e.g., Amazon Web Services [AWS], Microsoft Azure, or Google Cloud Platform [GCP]).
• Operating Systems: Robust administration and troubleshooting skills operating within Red Hat Enterprise Linux (RHEL) environments.
• Communication Skills: Consistently demonstrates clear and concise written and verbal communication skills, with the ability to articulate complex infrastructure concepts to both technical teams and client stakeholders.
• Hybrid role - 3 times a week to be in office in a secured room facility
• 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

• DevSecOps & Security Scanning: Hands-on experience integrating automated security and vulnerability scanning tools directly into CI/CD pipelines (e.g., CheckMarx, Snyk, SonarQube) to ensure secure delivery.
• Monitoring & Observability: Strong experience setting up and managing comprehensive alerting and telemetry dashboards utilizing Prometheus, Grafana, and the ELK Stack (Elasticsearch, Logstash, Kibana).