Senior DevOps / Platform Engineer - AI Platform

Years of Experience: 10+ years

Candidate Current Location: Bangalore only

Job Location: Bangalore

Notice Period: Immediate to 30 days

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.

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.