AI Platform Engineer

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.