Cloud Performance Engineering - Site Reliability Engineer
nameApply today and find plenty of reasons to SMILE!
The Cloud Site Reliability Engineer (SRE) is responsible for ensuring the reliability, scalability, and performance of production-grade services deployed across multiple cloud vendors and infrastructure platforms for Smile Digital Health, its clients, and partners.
This role designs and automates performance testing frameworks, integrates them into CI/CD pipelines, and uses observability tools to proactively detect and resolve bottlenecks. Working closely with engineering, product, and security teams, the SRE ensures systems meet strict SLAs for performance and availability while driving continuous optimization across multiple cloud platforms.
Responsibilities:
Collaborate with our Security Operations teams to help define and implement best practices around Cloud Service Provider configuration for Azure and other cloud providers.
Develop, implement and coordinate a multi-tenant approach around service offerings for DB, Container platform, Authentication, Certificates, and Product Registries etc.
Design and maintain performance testing strategies, framework, and environments in the cloud.
Develop and maintain cost/utilization tracking and attribution processes for all Cloud Service Providers.
Create documentation around Cloud Service Provider offerings detailing use cases, best practices, and implementation details.
Develop and maintain technical relationships with our core Cloud Service Providers.
Implement and maintain a secure and scalable infrastructure platform for delivering Cloud Services applications.
Ensure that internal and external SLA’s meet and exceed expectations, and ensure that system centric KPIs are continuously monitored and improved.
Create tools for automating deployment, monitoring and op
Opens the company's application page
Listed via
Himalayas
himalayas.app
Similar roles
Design & Tech
Related reads from TCHNX

Why Do AI-Generated Algorithmic Interfaces Feel Wrong?
AI-optimized interfaces may be mathematically efficient, but they often violate the psychological principles humans expect. I examine why algorithmic design creates friction, even when the data suggests it shouldn't.

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.

How Passive Data Collection is Reshaping UX Research
As users grow weary of surveys and interviews, researchers are turning to ambient behavioural signals from keystroke dynamics to micro-interactions to understand product experience without asking a single question.