Job Summary:
We are seeking a Director of Cloud Operations (CloudOps) to lead and evolve our cloud infrastructure and operational practices across a globally distributed SaaS platform. This is a hands-on leadership role responsible for ensuring the reliability, scalability, and efficiency of our systems running across multiple AWS regions in the United States and Europe.
As part of the senior leadership team, you will partner closely with Engineering, Security, and Product to strengthen operational excellence, enhance system observability, and drive continuous improvement in how we build and run services. You will lead a distributed team of engineers across the US and UK, fostering a high-performing, collaborative, and growth-oriented environment.
This role is ideal for a leader who combines deep technical expertise with a pragmatic approach to improving systems, processes, and team capabilities.
What You’ll Do
Cloud Platform & Reliability
Own the availability, performance, and resilience of our multi-region AWS platform.
Drive improvements in system reliability through well-defined SLIs/SLOs, error budgets, and proactive engineering practices.
Lead efforts to reduce MTTR and improve incident response effectiveness across the organization.
Guide architecture decisions for microservices, Kubernetes (EKS), and serverless workloads to ensure scalability and fault tolerance.
Observability & Incident Management
Advance our observability stra
Opens the company's application page
Listed via
Findwork
findwork.dev
Similar roles
Data Analyst
Harnham - Data & Analytics Recruitment
Senior Data Analyst
Harnham - Data & Analytics Recruitment
Service Charge Data Analyst
Robertson Bell
Data Analyst
R3vamp Limited
Design & Tech
Related reads from TCHNX
Why AI Design Tools Are Quietly Replacing Junior Designers and What Actually Comes Next
AI tools promise efficiency, but London studios are discovering an unexpected paradox: automation creates new bottlenecks requiring precisely the expertise being eliminated. We investigate what's actually happening to entry-level design work.
The Inference Economy: Why AI’s Biggest Cost Shift Is Happening After Training
A major shift in AI economics is reshaping the industry. As training frontier models becomes more expensive and inference becomes dramatically cheaper, companies are being forced to rethink how they build, deploy, price, and monetise intelligent systems.
The Emergence of Small Language Models: Why Efficiency Is Overtaking Scale
As the AI industry confronts computational costs and environmental concerns, a new generation of compact models is proving that bigger isn't always better. Small language models are reshaping enterprise AI deployment.