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Principal Software Engineer (Cluster Infrastructure & Deployment)

Principal Software Engineer (Cluster Infrastructure & Deployment)

northstar hr consultants
12-14 Years
  • Posted 6 hours ago
  • Be among the first 10 applicants

Job Description

Job Title - Principal Software Engineer

(Cluster Infrastructure & Deployment - Distributed Storage Systems)

Job Location - Pune, Maharashtra

Must Have Skills - Experience developing Kubernetes CRDs, Go / Python for building system tools, control planes, and automation scripts, Linux system administration and Linux scripting skills.

Position Overview -

Our client is looking for a Principal Software Engineer to join our core engineering team to lead the architecture, deployment, and management of our distributed storage clusters leveraging modern container orchestration technologies and AI-assisted development practices.

Role & Responsibilities

The Principal Software Engineer will serve as the technical go-to expert for cluster infrastructure, automated provisioning, and orchestration platforms across our distributed

storage ecosystem.

Your primary responsibilities will include:

  • Architecting, deploying, and managing enterprise-grade Kubernetes clusters to orchestrate distributed storage infrastructure across cloud and bare-metal environments.
  • Designing and implementing Kubernetes Custom Resource Definitions (CRDs) and custom operators/controllers to automate the lifecycle and management of complex storage systems.
  • Developing robust control plane software, automation frameworks, and management tooling primarily using Go and Python.
  • Applying fundamental computer science principles to solve complex cluster orchestration, networking, and scalability challenges.
  • Collaborating with systems architects to ensure seamless integration between the underlying storage architecture and high-level deployment frameworks.
  • Actively integrating cutting-edge AI tools (e.g., GitHub Copilot, integrated IDE features) into engineering workflows to boost productivity and code quality.
  • Providing technical leadership, mentoring engineers, setting operational standards, and driving architectural reviews for cluster infrastructure.

Qualifications & Requirements

Education & Experience

  • Bachelor's, Master's, or Ph.D. degree in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field.
  • 12+ years of hands-on professional experience in systems automation, platform engineering, or infrastructure engineering.
  • Proven track record of designing, building, and maintaining production-grade Kubernetes environments at scale.

Technical Skills (Must-Haves)

  • Solid foundation in Computer Science fundamentals (data structures, algorithms, operating systems, and computer network architecture).
  • Deep expertise in Kubernetes: configuring, setting up, bootstrapping, securing, and managing production K8s clusters.
  • Hands-on experience developing Kubernetes CRDs and custom resources/operators for complex storage or infrastructure workloads.
  • Excellent programming skills in Go and Python for building system tools, control planes, and automation scripts.
  • Strong Linux system administration and Linux scripting skills.
  • Familiarity with modern dev toolchains and AI-assisted development tools (e.g., VSCode, GitHub, Copilot).

Technical Skills (Good-to-Have)

  • Knowledge of cloud and virtualization management platforms such as OpenStack or VMware vSphere / VMs.
  • Familiarity with distributed storage systems (e.g., Ceph, S3, Lustre) from an operational and deployment perspective.

Soft Skills & Leadership

  • Strong leadership capability to establish technical strategy and mentor engineering teams.
  • Eagerness to integrate AI tools into the daily development workflow to maximize engineering throughput.
  • Excellent problem-solving skills, system-level analytical thinking, and attention to detail.
  • Ability to thrive and drive execution in a fast-paced, collaborative startup environment.

More Info

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Key Skills

AI-assisted development tools

Kubernetes CRDs