The DevOps Engineer I designs, modernizes, and supports core cloud infrastructure and the pipelines used to deliver it. The position works with proprietary platforms and current third-party tools, including AI-assisted coding tools for research, drafting, and routine technical tasks. Primary focus areas are system reliability, delivery pipeline quality, and a secure operating baseline.
Compensation
Competitive compensation Medical, Dental and Vision benefits after a short waiting period 401k matching program Generous paid time off program with an additional company break during the holidays Annual Volunteer Time Off (VTO) and a donation matching program Life Insurance Employee Assistance Program (health & well-being on and off the job) Rewards and Recognition Maternity and Parental Leave Training program and ongoing support throughout your entire Spring Venture Group career Diverse, inclusive & welcoming culture Optional enrollment options include HSA/FSA, AD&D, Spousal/Dependent life insurance, Short Term/Long Term Disability, Travel Assist, and Legal plans
Responsibilities
Deliver infrastructure initiatives and engineering requests to required quality standards
Monitor, troubleshoot, maintain, and improve automated build, packaging, and deployment processes
Implement automated infrastructure capabilities, including backups, security scanning, and system monitoring
Apply DevOps and Site Reliability Engineering practices to improve process quality across the change lifecycle
Collaborate with the DevOps Manager, DevOps Team Leads, senior engineers, and software development teams
The Principal Cloud Infrastructure Engineer will serve as a technical leader responsible for designing, building, and operating mission-critical cloud platforms across a global enterprise environment.
Compensation
Annual US salary range of $133,000–$213,000, depending on work location, job-related knowledge, skills, and experience.
Responsibilities
Lead the design, deployment, and operation of global cloud services across AWS and Azure, including secure, scalable cloud-native platforms and AWS Landing Zones.
Develop AI and data analytics architecture solutions aligned with business requirements.
Drive Infrastructure as Code (IaC) adoption using tools such as Terraform and CloudFormation to automate provisioning and configuration at scale.
Implement security-by-design principles, including identity and access management, encryption, and zero-trust practices, while maintaining alignment with security frameworks such as ISO 27000.
Establish monitoring and observability capabilities using tools such as Prometheus, Grafana, and Amazon CloudWatch to support performance, reliability, and uptime.
Requirements
Bachelor's degree or higher in Computer Science, Information Technology, or a related technical field
Nice to have: AWS Certified DevOps Engineer
Nice to have: AWS Solutions Architect
Nice to have: Microsoft Certified: Azure Administrator
Maintain, secure, and optimize enterprise cloud infrastructure across Microsoft Azure and Amazon Web Services (AWS), providing Level 2 operational support, troubleshooting infrastructure incidents, and ensuring availability and performance.
Responsibilities
Provide Level 2 support for Azure infrastructure incidents and service requests
Administer Azure resources (VMs, storage accounts)
Monitor Azure infrastructure using Azure Monitor and Log Analytics
As an Applied AI Site Reliability Engineer III, you will actively engage in your engineering craft, taking a hands-on approach to the reliability, performance, and operational integrity of high-visibility products and platforms and the environments they run in.
Compensation
A reasonable estimate of the current range is $102,500 to $188,900.
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.
Serve as the technical advocate for production reliability and operability, ensuring systems are admissible, performant, safe to run, and able to degrade gracefully when failure occurs.
Maintain accountability for the operational integrity of production and pre-production environments, and for the production standards that systems are admitted against.
Develop lean operational solutions through rapid, inexpensive experimentation to meet the reliability needs of the engineering teams and the business.
Work collaboratively with empowered, cross-functional partners: engineering, platform engineering, security and risk, data governance, and engineering leadership and architecture.
Requirements
Bachelor’s degree in computer science, software engineering, data science, machine learning, or related discipline
Nice to have: AI-augmented spec-driven development
A hands-on senior engineering role where you’ll solve complex problems, build scalable cloud-based software and have genuine influence over how we design and deliver our products.
Responsibilities
Design and deliver complex, scalable systems, including high-traffic APIs, multi-service integrations and data-processing solutions.
Own large features and components end-to-end, from technical design and development through to deployment and production support.
Build modern applications using C#, .NET Core, ASP.NET Web APIs and contemporary frontend technologies.
Influence architecture and technology decisions, helping the team choose solutions that balance scalability, maintainability and business needs.
Build and improve cloud-native solutions across Azure or AWS.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $102,500 to $188,900.
Responsibilities
Operate the products, platforms, and environments to meet SLOs
Lead design of observability, performance and resilience testing
Own admission of systems into production
Maintain operational integrity of production and pre-production environments
Build and operate production observability dashboards and alerting
Requirements
Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $113,100 to $208,300
Responsibilities
Operate production systems to meet SLOs and error budgets
Design and implement observability, performance, and resilience testing
Own admission of systems into production
Lead blameless postmortems and continuous improvement
Collaborate with cross-functional teams to set production standards
Requirements
Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline
A leadership-level engineering role focused on the reliability, performance, and operational integrity of high-visibility ServiceNow platforms, specifically integrating applied AI and agentic workloads.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $113,100 to $208,300.
Responsibilities
Embrace a culture of accountability for reliability, performance, and cost outcomes measured in SLOs and error budgets
Serve as technical advocate for production reliability and operability
Set production standards and lead design of observability, performance, resilience testing, and operational tooling
Maintain accountability for operational integrity of production and pre-production environments
Build and operate production observability (dashboards, SLO-driven alerting)
Requirements
Bachelor’s degree in computer science
software engineering
data science
machine learning
Nice to have: ServiceNow Certified System Administrator (CSA)
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