Kcura

Lead .NET Engineer - Automation Services

Kcura
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1 month ago
Warsaw, Poland +2 moreStaff+

Responsibilities

  • Lead the design and implementation of platform services, infrastructure automation, and development tooling using .NET and Azure.
  • Define and evolve architectural patterns and standards for cloud-native development, CI/CD, and Infrastructure as Code.
  • Collaborate with Engineering Managers, Staff Engineers, Principal Engineers, and Architects on platform strategy.
  • Mentor engineers through design reviews, code feedback, and technical guidance.
  • Lead initiatives that improve developer productivity, platform resilience, operational efficiency, and engineering excellence.
  • Promote DevOps practices, automation, and observability across the engineering organization.
  • Drive adoption of AI/ML capabilities where they improve developer experience or platform efficiency.
  • Stay current with industry trends and improve tools, practices, and technical decision-making.

Requirements

  • 7+ years of software development experience with strong expertise in C# and .NET.
  • Deep experience with Microsoft Azure, including networking, compute, identity, and automation.
  • Proven ability to lead technical projects and set architectural direction.
  • Hands-on experience with Infrastructure as Code, such as Terraform or Bicep, and CI/CD automation.
  • Strong understanding of containers, Kubernetes, and modern DevOps practices.
  • Strong communication and collaboration skills across engineering, product, and leadership teams.
  • Experience mentoring engineers and supporting technical growth within a team.
  • Preferred: experience implementing AI/ML tools or practices within developer platforms or infrastructure.

Benefits

  • Hybrid or remote work arrangement in Poland.
  • Competitive base salary, annual performance bonus, long-term incentives, and equity program.
  • Benefits, discretionary time off, and parental leave.
  • Opportunities to work on distributed, cloud-native systems processing large volumes of data.
  • Collaborative, inclusive culture focused on knowledge sharing, ownership, and continuous improvement.

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