DevOps Engineer - IBM Quantum

We are seeking an experienced DevOps Engineer to further operational excellence initiatives within IBM Quantum. In this role, you will drive improvements to the developer experience by designing and evolving CI/CD pipelines, build and test infrastructure, deployment workflows, and internal tooling that enable teams to deliver software quickly and reliably. You will break down complex operational challenges, automate manual processes, and establish best practices for infrastructure as code, environment management, and release automation.   This role emphasizes technical leadership, ownership of critical developer-facing platforms, and consistent delivery of business value through faster feedback loops, higher deployment confidence, and improved internal process reliability.    As a DevOps Engineer, you’ll be responsible for creating and improving on existing operational practices within the IBM Quantum Platform team, including CI/CD pipelines, development tooling, local development enablement, and more.  You will also be expected to contribute to the development of new features and functionality for the Quantum Platform at times operational needs require less attention.   Our work plays a fundamental role in transforming complex quantum research into scalable, real‑world solutions that define the next era of computing. Joining this team as a DevOps Engineer means stepping into a high‑impact role where you'll directly improve the development the day-to-day overhead of your peers, reduce team toil, and shape best practices for the future.     Experience in DevOps or developer platform engineering, supporting multiple software teams in production environments.   Hands on expertise building and operating CI/CD pipelines, including build, test, and deployment automation for distributed systems.   Strong background in cloud and infrastructure tooling, using infrastructure as code (e.g., Terraform, CloudFormation) and containerized workloads.   Proven ability to improve developer workflows and tooling, reducing friction and increasing delivery speed and reliability.  Hands-on experience with Kubernetes, Docker, and containerized deployments.    Experience designing internal developer platforms or selfservice tooling at scale.   Familiarity with observability and reliability practices, including monitoring, logging, and incident response. Contributions to open-source or inner-source projects. Familiarity with AI-powered observability platforms or tools capable of detecting anomalies, performance regressions, or unusual workload patterns. Experience exploring or adopting new AI technologies that enhance developer productivity, service reliability, or operational efficiency. United States Infrastructure & Technology Hybrid Professional Yorktown Heights, US