Principal Platform Engineer (Python)

Our client is a leading global investment management company headquartered in London. It manages over $228 billion in assets and serves institutional investors, pension funds, wealth managers, and other sophisticated clients worldwide. The firm specializes in quantitative investing, alternative investments, systematic trading strategies, and technology-driven asset management. Data science, machine learning, and AI are core components of its investment and research processes.As part of our collaboration we will focus on two foundational capabilities required to enable safe and scalable AI adoption across the enterprise: Agentic Security and AI-Ready Data Foundations.We build the data foundations and evaluation frameworks that make AI useful, reliable and safe inside regulated financial firms. The value of an AI agent depends not only on the models behind it, but also on the quality of the structured and unstructured data it consumes and the accuracy, relevance and traceability of the outputs it produces. Your job is to measure that quality, identify where it breaks down and turn the findings into practical improvements.This is an *engineering* role, not an analytical one. You will build the agentic workflows that reason over the firm's research content, and the ingestion, evaluation and guardrail tooling that makes their output trustworthy enough for investment professionals to act on. None of this tooling exists today - you would be building it from scratch.Requirements7+ years of experience in DevOps, Platform, or Systems Engineering.Strong Linux knowledge, including networking, storage, permissions, processes, and OS-level troubleshooting.Production-level Python for automation, integrations, tooling, and platform/migration support.Hands-on experience with Terraform and Ansible in production environments.Experience with infrastructure and workload migrations, including OS, application, or platform migrations.Good understanding of Kubernetes, including cluster upgrades, migrations, and workload movement.Experience with CI/CD tools such as GitLab CI, GitHub Actions, or Jenkins.Familiarity with observability tools such as Prometheus and Grafana.Practical understanding of secrets management, access control, and infrastructure security.Software engineering mindset with the ability to read, maintain, and extend production code.Strong troubleshooting, ownership, and collaboration skills.English: B2 or higher.Responsibilities:Designing, building, and maintaining the Python services, libraries, and command-line tooling that make up the internal infrastructure platform.Working with the engineering teams who consume the platform to understand their workflows and turn recurring pain points into platform features.Replacing manual infrastructure operations with codified, self-service workflows, so that environments are reproducible, reviewable, and safe to change.Building observability into the platform through metrics, structured logging, and alerting, so failures surface before consuming teams report them.Owning production issues in the platform end to end, from triage and root cause analysis through the code or configuration change that prevents a recurrence.Managing and scaling the compute and storage the platform provisions across on-premises hardware, balancing performance against cost as usage grows.Building security into the platform by default: secrets management, least-privilege access, dependency hygiene, and an auditable history of every infrastructure change.Evaluating new tools, libraries, and patterns, and folding the ones that earn their place into the platform roadmap.