Senior platform Engineer

ABOUT CFMFounded in 1991, we are a global quantitative and systematic asset management firm applying a scientific approach to finance to develop alternative investment strategies that create value for our clients.We value innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.ABOUT THE TEAM  The Quant Platform team is the shared engineering foundation for CFM's Quant Engineering division, bringing together Portfolio and Prediction engineering capabilities into one platform. We build common services, scalable foundations, and production-grade tooling that make research easier to industrialize, safer to operate, and faster to scale across cloud, large-scale computing, and future AI-enabled research needs. The open position is within Quant Platform, with a specific focus on Observability, Reliability & Autonomous Ops. The role will help raise the operational maturity of critical quant platforms by improving telemetry, automating incident response and runbooks, reducing toil, and strengthening production change, security, resilience, and FinOps practices. YOUR ROLE  We are looking for a senior individual contributor to raise the reliability, automation, and cloud-native maturity of our platform. You will own hard problems end-to-end, set engineering standards, and mentor through your work rather than through a reporting line.  You will help move the platform from reactive, ticket-driven operations toward automated, observable, self-service infrastructure that engineers can rely on without thinking about it.  KEY RESPONSIBILITIES  Drive observability adoption across critical Quant Platform services by defining meaningful telemetry, dashboards, alerts, and operational signals that improve production visibility. Establish and evolve reliability practices for platform services, including Service Level Objectives, error budgets, incident reviews, and data-driven improvement plans. Automate incident response, runbooks, recovery workflows, and L3 support patterns so recurring operational issues are handled consistently and with minimal manual intervention. Reduce operational toil systematically by instrumenting invisible failure modes, eliminating repetitive manual tasks, and making platform operations more self-service. Design and implement self-healing and autonomous operations capabilities that improve platform resilience and shorten time to detection, diagnosis, and recovery. Strengthen production change management, security controls, resilience practices, and FinOps discipline for cloud and hybrid platform services. Act as a technical reference for observability, reliability engineering, autonomous operations, and operational excellence across Quant Engineering. YOUR SKILLS  Essential  8+ years of professional engineering experience in production environments.  Extensive hands-on track record as a platform, infrastructure, or reliability engineer, operating systems at scale.  Deep, current expertise with AWS cloud-native architecture.  Strong Infrastructure-as-Code (Terraform, CDK, or equivalent) and GitOps practice.  Solid CI/CD experience (GitLab CI, GitHub Actions, Jenkins, or similar), you think of pipelines as a product.  Real SRE / observability experience: SLOs, monitoring, alerting, incident management, and the discipline to improve systems with data.  Sound distributed systems and containerization fundamentals.  Fluency in Python or a comparable language for automation and tooling.  A genuine senior-IC mindset: you want to go deep technically, set standards, and mentor.  Strongly desirable  Experience in a latency-sensitive or data-intensive environment — trading, fintech, or high-scale SaaS.  Familiarity with distributed computing and HPC environments, including workload orchestration, scheduling, and performance-aware infrastructure.  Exposure to ML or data platforms  model serving, feature stores, training/experiment infrastructure (Ray, SageMaker, or equivalent).  Practical use of AI coding agents (e.g. Claude Code, Copilot) in real engineering workflows, ideally beyond the workstation.  A product-oriented view of internal platforms: your users are engineers and researchers, and their experience is the point.  Awareness of security and compliance in cloud environments.  WHAT WE OFFER  A role at the technical heart of one of Europe's leading quantitative asset managers, in a firm that treats engineering and research as peers.  Genuine hands-on ownership and the autonomy of a senior IC track delivering impact without the obligation to manage.  A modern hybrid stack (AWS + on-premises) and an organization actively investing in cloud, automation, and AI-augmented engineering.  A small, serious, high-caliber team.  EQUAL OPPORTUNITIES STATEMENT We are continuously striving to be an equal opportunity employer and we prohibit any discrimination based on sex, disability, origin, sexual orientation, gender identity, age, race, or religion. We believe that our diversity, breadth of experience, and multiple points of view are among the leading factors in our success. CFM is a signatory of the Women Empowerment Principles.FOLLOW US Follow us on Twitter or LinkedIn or visit our website to find out more about CFM.