About Our Team
Lenovo is building Quantum, a next‑generation hybrid AI platform that spans Windows, Android, and cloud. As part of this vision, we are expanding the engineering organization supporting Qira, Lenovo’s cross‑device Personal AI.
We are hiring Senior DevOps / Platform Engineers to build and operate the core automation, infrastructure, and service platforms that enable secure, reliable, and high‑velocity delivery of Qira’s AI systems across device, edge, and cloud.
Depending on your background, you may be aligned to Platform Engineering, Observability, Operations, or Service Reliability—based on experience and organizational need.
Qira operates with the speed, ownership, and creativity of a startup, supported by the scale, resources, and technical depth of Lenovo. We are building foundational systems from the ground up—intentionally, pragmatically, and with a culture of engineering excellence.
Location: Open to remote work in the US. The preferred work location is Chicago, IL.
What You Might Work On
As a Senior DevOps / Platform Engineer, you may be responsible for a subset of the following areas depending on team placement:
CI/CD, Automation & Tooling
Designing, implementing, and improving CI/CD pipelines for AI, platform, and application teams.
Building automation and developer tooling to improve productivity and consistency.
Developing infrastructure‑as‑code for cloud and hybrid environments (Terraform, Bicep, etc.).
Platform & Infrastructure Engineering
Implementing scalable, secure, and resilient infrastructure on Azure and Kubernetes.
Building and operating hybrid systems spanning device, edge, and cloud compute.
Enabling reliable platform services that support inference, data pipelines, and high‑performance AI workloads.
Observability & Telemetry
Implementing and enhancing observability systems using OpenTelemetry, Grafana, Prometheus, Loki, and related tooling.
Ensuring platform telemetry is accurate, actionable, and tied to performance and reliability outcomes.
Building dashboards and analytics for service health and operational insight.
Deployment & Release Engineering
Improving deployment workflows, safety, consistency, and traceability.
Supporting progressive delivery patterns including canaries, staged rollouts, and automated rollbacks.
Optimizing CI/CD and deployment tooling for hybrid AI services.
Collaboration & Reliability Culture
Partnering closely with SRE, AI/ML, security, firmware, and product engineering teams.
Contributing to system design discussions with a focus on automation, scalability, and operational best practices.
Helping define and evolve platform engineering standards, patterns, and conventions.
Basic Qualifications
10+ years in DevOps, Platform Engineering, Cloud Engineering, or related fields
Bachelor’s Degree in Computer Science, Engineering, or a related technical field
Strong experience building and operating infrastructure in Azure, AWS, or GCP
Proficiency with CI/CD systems, build automation, and deployment pipelines
Experience with Infrastructure as Code (Terraform, ARM/Bicep, CloudFormation, etc.)
Strong development or scripting skills (Python, Go, Bash, or similar)
Hands-on experience with Docker and Kubernetes
Understanding of observability fundamentals (metrics, logs, tracing)
Preferred Qualifications
Deep experience with Azure cloud architecture and DevOps tooling
Strong hands‑on work with OpenTelemetry (instrumentation, pipelines)
Experience with Grafana, Prometheus, Loki, Tempo, or similar observability tools
Experience supporting AI/ML workloads or GPU‑accelerated compute environments
Familiarity with event‑driven systems and operationalizing data pipelines
Experience contributing to or running on‑call rotations
Passion for automation, developer experience, and infrastructure reliability at scale
What Success Looks Like
CI/CD pipelines are fast, stable, and trusted.
Platform infrastructure becomes more automated, observable, and scalable.
Telemetry and dashboards provide clear visibility into system health.
Deployments are consistent, safe, and repeatable.
Engineering teams move faster thanks to strong platform foundations.
Qira’s hybrid AI platform becomes increasingly reliable, efficient, and easy to operate.
The base salary budgeted range for this position is $190K - $230K. Individuals may also be considered for bonus and/or commission.
Lenovo’s various benefits can be found on www.lenovobenefits.com.
Lenovo is building Quantum, a next‑generation hybrid AI platform that spans Windows, Android, and cloud. As part of this vision, we are expanding the engineering organization supporting Qira, Lenovo’s cross‑device Personal AI.
We are hiring Senior DevOps / Platform Engineers to build and operate the core automation, infrastructure, and service platforms that enable secure, reliable, and high‑velocity delivery of Qira’s AI systems across device, edge, and cloud.
Depending on your background, you may be aligned to Platform Engineering, Observability, Operations, or Service Reliability—based on experience and organizational need.
Qira operates with the speed, ownership, and creativity of a startup, supported by the scale, resources, and technical depth of Lenovo. We are building foundational systems from the ground up—intentionally, pragmatically, and with a culture of engineering excellence.
Location: Open to remote work in the US. The preferred work location is Chicago, IL.
What You Might Work On
As a Senior DevOps / Platform Engineer, you may be responsible for a subset of the following areas depending on team placement:
CI/CD, Automation & Tooling
Designing, implementing, and improving CI/CD pipelines for AI, platform, and application teams.
Building automation and developer tooling to improve productivity and consistency.
Developing infrastructure‑as‑code for cloud and hybrid environments (Terraform, Bicep, etc.).
Platform & Infrastructure Engineering
Implementing scalable, secure, and resilient infrastructure on Azure and Kubernetes.
Building and operating hybrid systems spanning device, edge, and cloud compute.
Enabling reliable platform services that support inference, data pipelines, and high‑performance AI workloads.
Observability & Telemetry
Implementing and enhancing observability systems using OpenTelemetry, Grafana, Prometheus, Loki, and related tooling.
Ensuring platform telemetry is accurate, actionable, and tied to performance and reliability outcomes.
Building dashboards and analytics for service health and operational insight.
Deployment & Release Engineering
Improving deployment workflows, safety, consistency, and traceability.
Supporting progressive delivery patterns including canaries, staged rollouts, and automated rollbacks.
Optimizing CI/CD and deployment tooling for hybrid AI services.
Collaboration & Reliability Culture
Partnering closely with SRE, AI/ML, security, firmware, and product engineering teams.
Contributing to system design discussions with a focus on automation, scalability, and operational best practices.
Helping define and evolve platform engineering standards, patterns, and conventions.
Basic Qualifications
10+ years in DevOps, Platform Engineering, Cloud Engineering, or related fields
Bachelor’s Degree in Computer Science, Engineering, or a related technical field
Strong experience building and operating infrastructure in Azure, AWS, or GCP
Proficiency with CI/CD systems, build automation, and deployment pipelines
Experience with Infrastructure as Code (Terraform, ARM/Bicep, CloudFormation, etc.)
Strong development or scripting skills (Python, Go, Bash, or similar)
Hands-on experience with Docker and Kubernetes
Understanding of observability fundamentals (metrics, logs, tracing)
Preferred Qualifications
Deep experience with Azure cloud architecture and DevOps tooling
Strong hands‑on work with OpenTelemetry (instrumentation, pipelines)
Experience with Grafana, Prometheus, Loki, Tempo, or similar observability tools
Experience supporting AI/ML workloads or GPU‑accelerated compute environments
Familiarity with event‑driven systems and operationalizing data pipelines
Experience contributing to or running on‑call rotations
Passion for automation, developer experience, and infrastructure reliability at scale
What Success Looks Like
CI/CD pipelines are fast, stable, and trusted.
Platform infrastructure becomes more automated, observable, and scalable.
Telemetry and dashboards provide clear visibility into system health.
Deployments are consistent, safe, and repeatable.
Engineering teams move faster thanks to strong platform foundations.
Qira’s hybrid AI platform becomes increasingly reliable, efficient, and easy to operate.
The base salary budgeted range for this position is $190K - $230K. Individuals may also be considered for bonus and/or commission.
Lenovo’s various benefits can be found on www.lenovobenefits.com.