DevOps / Platform Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

DevOps / Platform Engineer Wrocław Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data-driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT's collaborative mindset, which enables us to solve the most complex challenges. QRT's culture of innovation continuously drives our ambition to deliver high-quality returns for our investors. As a DevOps / Platform Engineer, you will build and operate the infrastructure that powers QRT's internal AI platform. You will be responsible for the Kubernetes and AWS environments supporting model serving, observability, and developer tooling, ensuring they remain reliable, secure, and scalable. Working closely with AI Platform Engineers, Researchers, and Data Scientists, you will own core infrastructure services and help shape how AI capabilities are delivered across the firm. Your future role within QRT: Infrastructure & Cloud - Design and operate infrastructure across AWS and on-premise Kubernetes environments supporting AI and LLM workloads - Manage Kubernetes clusters, including scheduling, multi-tenancy, resource isolation, and GPU-backed workloads - Develop hybrid cloud strategies balancing performance, cost, and data residency requirements - Own AWS infrastructure, including networking, IAM, security, and cost management - Build and maintain infrastructure as code using reusable, version-controlled tooling Platform Operations - Implement and maintain CI/CD and GitOps deployment workflows - Build observability solutions covering system health, utilisation, latency, and platform performance - Automate scaling and capacity management - Enforce authentication, rate limiting,

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