A day in the life

This role helps Cloud and Systems Engineering modernize enterprise operations by redesigning repetitive workflows into reliable automation, self-service capabilities, and AI-assisted operating patterns. They will work across cloud infrastructure, systems administration, identity, endpoints, networking, and end-user computing to improve reliability, speed, and engineering leverage. The role partners with engineering teams to evaluate where agentic automation, deterministic automation, or human-in-the-loop controls are the right fit for enterprise-scale operations. They will introduce standards, reusable components, and measurement practices that reduce manual requests and improve operational outcomes across the broader technology estate.

Key responsibilities include:

• Redesign high-friction operational workflows using AI, automation, and platform engineering patterns that reduce manual work and improve reliability.
• Build agentic and event-driven workflows for provisioning, remediation, change execution, incident support, and support deflection with appropriate safety controls.
• Establish standards for safe AI use in cloud operations, including observability, human-in-the-loop controls, auditability, and rollback practices.
• Design and deliver self-service infrastructure capabilities using standardized modules, golden paths, reusable components, code, APIs, and internal platforms.
• Design, operate, and troubleshoot AWS and Azure infrastructure using infrastructure-as-code, serverless, event-driven, and cloud-native architectures.
• Automate identity, access, endpoint, and end-user computing workflows across systems such as Entra ID, Intune, SAML/OAuth, Cognito, and AWS WorkSpaces.
• Influence engineering teams by introducing new patterns, standards, operating model improvements, and metrics that communicate the impact of automation and AI adoption.

Building blocks for success

Required:

• Experience designing and operating infrastructure across AWS and Azure.
• Experience with AWS services such as EC2, Lambda, RDS, S3, DynamoDB, and IAM.
• Experience using infrastructure-as-code, including Terraform or CloudFormation.
• Experience building or supporting CI/CD pipelines, such as Azure DevOps or similar platforms.
• Proficiency with Python scripting or programming.
• Ability to troubleshoot complex issues across cloud, networking, identity, APIs, and distributed systems.
• Experience with identity and endpoint management systems, including SAML, OAuth, Entra ID or Azure AD, and Intune.
• Experience designing or building AI-assisted or agentic workflows for engineering or operational use cases.
• Ability to evaluate when AI, deterministic automation, or combined approaches are appropriate for safe enterprise operations.
• Experience applying Git workflows, including branching, pull requests, and code review.

Preferred:

• 7+ years of experience in infrastructure, DevOps, cloud engineering, or platform engineering.
• Experience with Bash or PowerShell.
• Experience with agentic AI frameworks, LLM orchestration, or AI-driven workflow tools such as OpenAI Agents SDK, LangChain, n8n, or MCP.
• Experience with internal developer platforms, self-service tooling, or platform engineering practices.
• Experience with ServiceNow or similar ITSM/workflow platforms.
• Demonstrates willingness and capability to leverage emerging technology, automation, and AI tools to improve efficiency, quality, and speed. Exercises sound judgment, creative thinking, and accountability for outcomes.

Hiring Salary Range of: $121,000 - $159,000. Salary and whole compensation package (bonus target & LTI (Long Term Incentives)) to be determined by the candidate's location, education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.