AI Platform Engineer

Reposted 2 Days Ago
Be an Early Applicant
Wrocław, Dolnośląskie, POL
In-Office
Mid level
Financial Services
The Role
The AI Platform Engineer will design, deploy, and maintain AI infrastructure, manage Kubernetes operations, optimize AWS services, and develop CI/CD workflows while supporting engineering users and collaborating with stakeholders.
Summary Generated by Built In

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 frameworks
  • Build resilient systems with fallback and degradation mechanisms

Operations & Observability

  • Implement monitoring, tracing, logging, and quality metrics across AI services
  • Manage service lifecycle activities, including deployment, rollout, versioning, and deprecation
  • Participate in operational support and incident response

Your present skillset:


  • 4+ years of experience in software or platform engineering, with exposure to AI/ML or LLM-based applications
  • Strong Kubernetes experience and familiarity with containerised environments
  • Good knowledge of AWS, networking fundamentals, IAM, and cloud infrastructure
  • Hands-on experience building and operating production RAG systems
  • Experience with vector databases and retrieval systems
  • Strong Python skills and experience building production APIs and services
  • Understanding of LLM fundamentals, including prompting, context management, token constraints, and output reliability
  • Strong communication skills and the ability to collaborate across technical and non-technical teams

Nice to Have

  • Experience with agentic AI systems and workflow orchestration
  • Familiarity with LLM evaluation frameworks and quality measurement
  • Exposure to model serving platforms and inference optimisation
  • Understanding of embedding model trade-offs and retrieval performance
  • Experience with data engineering or AI-related data pipelines
  • AWS or Kubernetes certifications

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.


Skills Required

  • 4 or more years of experience in Cloud Engineering, DevOps or Platform Engineering
  • Strong Kubernetes experience including cluster operations and workload scheduling
  • Strong AWS experience including networking, IAM, EKS, EC2 and cost management
  • Proficiency in Python and infrastructure as code tooling such as Terraform
  • Experience building and operating continuous integration and deployment pipelines

Qube Research & Technologies Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Qube Research & Technologies and has not been reviewed or approved by Qube Research & Technologies.

  • Wellbeing & Lifestyle Benefits Office amenities such as free meals, social events, and wellness-focused workspaces are highlighted in multiple locations. Cycle-to-work schemes and onsite classes in Europe further enhance day-to-day quality of life.
  • Leave & Time Off Breadth Two paid volunteer days and corporate donation matching were introduced firmwide. Some locations also cite generous annual leave allowances with options to buy additional days.
  • Healthcare Strength Private medical coverage and life insurance are called out for the UK. Job listings reference health insurance in various regions, though specifics differ by office.

Qube Research & Technologies Insights

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The Company
HQ: London
774 Employees

What We Do

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. We currently have multiple open positions on our website, please get in touch! Our commitments: https://www.qube-rt.com/commitments

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