Site Reliability Engineer

3 weeks ago

Manila, Philippines Cambridge University Press & Assessment Full time

Overview Site Reliability Engineer (AI Operations) - 6426 Work setup: Hybrid (open to 2x a week in the office) Work schedule: 10AM to 6PM Manila time Employment type: Permanent Pay range: Php 60,000 to Php 81,000 We are recruiting for a Site Reliability Engineer to be part of our Education Technology Team. As a Site Reliability Engineer (AI Operations), you'll be pioneering operational excellence for AI systems that are transforming how millions learn worldwide. Discover a world of endless possibilities with Cambridge University Press & Assessment, a distinguished global academic publisher and assessment organization proudly affiliated with the prestigious University of Cambridge. Responsibilities Drive innovation in AI operations by implementing observability solutions for LLM deployments, workflow automation platforms (e.g. n8n), and AI services across AWS Bedrock and Azure OpenAI Establish governance frameworks that ensure our AI services are ethical, compliant, and safe for educational use Transform our approach to cost optimisation for AI workloads through intelligent caching, model selection, and resource allocation strategies Collaborate with teams to operationalise AI features, sharing expertise to help developers build production-ready, scalable AI solutions Be continuously learning about emerging AI operational tools like Portkey and LiteLLM, bringing new approaches to improve reliability and efficiency Strengthen our impact by implementing sustainable AI practices that consider the environmental footprint of compute-intensive workloads Qualifications Education & Experience: 3–5 years in Site Reliability Engineering or related roles, with proven application of operational excellence in emerging technologies. Degree or equivalent experience in Computer Science, Engineering, or related field. Cloud & Infrastructure: Strong experience with cloud platforms, particularly AWS, including Infrastructure as Code (Terraform, CDK, CloudFormation) and cloud-native services. Automation & Delivery: Skilled in delivering change through automation with strong scripting abilities (Python, Bash, etc.) and hands-on experience with CI/CD pipelines (GitHub Actions, Jenkins, Bitbucket Pipelines). Monitoring & Reliability: Practical experience with monitoring and observability systems (Datadog, New Relic, Grafana, ELK/EFK stack) to ensure performance, availability, and incident response in distributed systems. API & Distributed Systems: Knowledge of API management, rate limiting, scalability, and the complexities of distributed architectures, particularly for AI-related workloads. AI & Emerging Tech: Familiarity with Large Language Models, cloud AI services, or workflow automation tools. Willingness to learn and apply new approaches to maximize impact in education technology. Ways of Working: Enthusiastic about exploring possibilities with AI while maintaining operational rigor. Collaborative, curious, and aligned with the vision of using technology to unlock potential in learners worldwide. Additional notes This is more than a technical role - it's an opportunity to define how AI operates in educational technology, ensuring it's deployed responsibly and effectively. You'll be at the forefront of establishing best practices that could influence how the entire education sector approaches AI operations. #J-18808-Ljbffr

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