Senior Site Reliability Engineer

Role Overview

• Design, build, and operate reliable and scalable systems by defining and monitoring SLOs/SLIs, working directly on production infrastructure, and collaborating closely with software engineers on system design and reliability improvements
• Actively develop automation for infrastructure and operational workflows to eliminate toil and reduce MTTR, participate in and lead incident response, and drive blameless post-incident reviews with concrete follow-ups implemented in code and tooling
• Continuously analyze and optimize system performance and cost, provide data, insights, and recommendations to inform capacity planning, and support security best practices through hands-on vulnerability remediation and threat mitigation

Requirements

• SRE & Cloud Engineering: Hands-on experience with SRE practices in production, strong AWS expertise, Kubernetes, networking, DNS, and Infrastructure as Code (Pulumi preferred, Terraform a plus)
• Automation & Software Engineering: Demonstrate strong software engineering fundamentals with an emphasis on code quality and maintainability. This includes solid Python proficiency and deep knowledge of the Python ecosystem (testing, debugging, packaging) and a consistent focus on writing clean, well-structured, and maintainable code
• Reliability, Data & Operations: add stakeholder engagement and mentoring e.g. lead incident response and RCAs, improve system reliability, and engage stakeholders to propose solutions, share learnings, and mentor others
• Nice-to-Have: Experience operating in highly regulated industries (e.g. Insurance, Banking, Healthcare), managing sensitive data, and supporting secure networking setups, including exposure to security technologies such as Cloudflare.
• Strong understanding of microservices architectures, their principles and trade-offs, with the ability to troubleshoot and maintain distributed systems and supporting technologies (RabbitMQ, Kafka, PostgreSQL, Redis).
• Hands-on experience with Datadog for platform and application monitoring, performance optimisation, and solid fundamentals in database structures and operational troubleshooting. Hands-on experience with PySpark and familiarity with MLOps practices including model registries, versioning, retraining workflows, and deployment lifecycles.

Tech Stack

• AWS
• Cloud
• Distributed Systems
• DNS
• Kafka
• Kubernetes
• Microservices
• Postgres
• PySpark
• Python
• RabbitMQ
• Redis
• Terraform

Benefits

• Work Your Way: Enjoy full flexibility – work from home, the office or a mix of both. Plus, work from anywhere for up to 30 days a year.
• Grow with us: Get access to learning resources, mentorship and a growth plan tailored to you.
• Thrive and perform: Enjoy private healthcare, gym discounts, wellbeing programs and mental health support.