Level

Target

Sr Engineer - Compute Virtualization

Target is hiring a Sr Engineer - Compute Virtualization in Bengaluru, India. Level rates it ; you can apply on Target.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • Level classifies it as a senior role.
  • Level lists 14,000+ other open roles at Target.

AI in this role

About us:

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.

We are looking for a Senior Engineer to design, build, and operate highly available compute and private cloud infrastructure at scale. This role requires strong software engineering fundamentals combined with hands-on expertise in Go, Linux, virtualization, networking, storage, and production operations. Understanding of Kubernetes and docker/containers is a plus.

Education Qualification:
Bachelor's degree in Computer Science, Engineering, or a related field; Master's degree is a plus.
Experience: 5+ years of relevant experience in software development and cloud concepts/infrastructure

What You’ll Bring
5+ years of relevant software/platform engineering experience with a 4 years bachelor’s degree.
Core Technical Skills
• Programming: Strong proficiency in Go (Golang) and solid understanding of data structures, algorithms,
concurrency, and software design.
• Linux & Virtualization: Hands-on experience with Linux/Ubuntu, KVM, libvirt, or comparable server virtualization technologies.
• Containers: Strong working knowledge of Kubernetes and container technologies such as containerd/Docker.
• Distributed Services: Experience building microservices and REST/gRPC APIs.
• Infrastructure: Strong fundamentals in compute, networking, storage, load balancing, high availability, security, and failure recovery.
• Automation: Experience with Ansible or comparable infrastructure automation/configuration-management tools.
• Observability: Hands-on experience with Prometheus/OpenTelemetry, Grafana, InfluxDB, Telegraf, or equivalent observability platforms.
• Testing: Experience building unit, integration, and automated infrastructure/service tests.
• Engineering Practices: Strong knowledge of Git, CI/CD, code reviews, automated testing, and production software-development practices.
• Production Operations: Proven experience deploying, operating, monitoring, and troubleshooting
• Deep knowledge of virtualization, container runtimes, distributed systems, or infrastructure platform engineering.
• Understanding of docker/container

What You’ll Do
• Design and build scalable, resilient compute infrastructure and platform services.
• Develop production-quality services and infrastructure components using Go (Golang).
• Build and operate virtualization platforms using KVM, libvirt, and Linux.
• Develop REST/gRPC APIs and microservices for infrastructure automation and platform capabilities.
• Automate infrastructure provisioning, configuration, testing, and operational workflows using tools such as Ansible.
• Build observability into platforms using Prometheus/OpenTelemetry, Grafana, InfluxDB, and Telegraf.
• Troubleshoot complex production issues across compute, Linux, networking, storage, and virtualization.
• Improve platform availability, performance, scalability, operational readiness, and failure recovery.
• Participate in design reviews, code reviews, incident response, root-cause analysis, and production support.
• Provide technical guidance to engineers and collaborate with partner teams on architecture and platform
decisions

How we rate this

Sr Engineer - Compute Virtualization at Target rates 36 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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