Site Reliability Engineer

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Additional Information

About Robin Robin is on a mission to rebuild the legal industry - starting with making contracts simple for everyone. We are a pioneer in Legal AI, built on proprietary models, licensed data, and deep partnerships with Anthropic and AWS. Since 2019, we've expanded our footprint to 4 continents and have been supporting many of the world's most successful businesses, including GE, Pfizer, KPMG, and UBS. What will you do as an SRE? As an SRE at Robin AI, you'll help build and maintain our cloud infrastructure and applications that powers our cutting-edge Legal AI platform. You'll collaborate with engineering teams to establish robust monitoring, incident response, and deployment strategies that ensure high availability and reliability of our proprietary models and services, maintaining optimal SLOs for our global customer base. Your day-to-day responsibilities: You will be responsible for ensuring the Robin systems are highly available and scalable. Standardise and implement observability practices in our service-based architecture through logging, traces, metrics and monitors Design, deploy, and operate infrastructure to support Robin's product teams as we expand into new regions. Adding automation around manual operational tasks Collaborate with development team leads to optimise build, test, and deployment processes Participating in and improving our on-call and incident handling processes to ensure 24/7 system reliability Ideally, you should have the following qualifications: 3+ years of experience in DevOps or Site Reliability Engineering roles Proficiency in at least one backend programming language (We use Python) Strong knowledge of AWS services (ECS, S3, RDS, Lambda, etc.), managed by Terraform Comfortable troubleshooting across the full stack, starting from the browser, through the networking components, into the containerised applications and then onto data stores. Knowledge of observability frameworks and tools (We use OpenTelemetry, Cloudwatch & DataDog) Excellent problem-solving and communication skills Experience with AI/ML infrastructure deployments is a plus

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