AI Platform Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• 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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401(k) match

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Market context

Median wage (BLS OEWS)

$116,543 national median

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.

Schedule

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Weekend work

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Application

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Assessment

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Deadline

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About this role

AI 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. You will build and operate QRT's internal AI application platform, enabling researchers, developers, and data scientists to leverage LLM-powered tools effectively and reliably. Your focus will be on production AI services, including RAG systems, agentic workflows, retrieval infrastructure, and the APIs that make these capabilities available across the firm. You will work closely with Platform Engineering and AI users to deliver scalable, high-quality solutions. You will own AI services used across the firm and help shape how AI capabilities are delivered to researchers and engineers. Your future role within QRT: AI Platform Development - Develop and maintain internal AI services and APIs - Build and improve RAG pipelines, including document ingestion, embeddings, retrieval, and relevance optimisation - Manage vector database performance, scalability, and data freshness - Design clear, well-documented APIs for internal users - Support agentic workflows and the services they depend on Platform Reliability & Quality - Integrate model serving endpoints into application-layer services - Define and monitor service objectives around latency, reliability, and retrieval quality - Implement prompt management, versioning, evaluation, and testing

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