Site Reliability Engineer

About Us:

DeepJudge is Switzerland’s leading AI and ICT scale-up, transforming how law firms and legal departments access and leverage their knowledge. Founded by former Google search engineers with PhDs in AI from ETH Zurich, and backed by top-tier Silicon Valley investors, we are building the intelligence layer that powers the legal industry. Every firm can license the same AI models, but no two firms share the same institutional knowledge. Decades of experience, work product, and precedent are often trapped across systems, underused and inaccessible. DeepJudge makes this expertise instantly available through world-class enterprise search and AI infrastructure, enabling firms to automate workflows, build knowledge-powered applications, and turn experience into a lasting advantage. Our technology is trusted by many of the world’s leading law firms, including Freshfields, Gunderson Dettmer, Holland & Knight, Arent Fox, and Cozen O’Connor. Headquartered in Switzerland with a growing team across North America, we are expanding rapidly and shaping the future of how professional knowledge is discovered and applied. At DeepJudge, we move fast, think rigorously, and care deeply about what we build. We combine cutting-edge research with close collaboration with our clients to deliver solutions that truly make an impact. If you want to be part of a team defining how AI transforms high-stakes knowledge work, this is the place to do it.

Your responsibilities will include:

Owning the availability, latency and performance of our production environments: large-scale search and retrieval services, ingestion and data stores on container-orchestrated infrastructure across multiple public and private clouds Owning the cloud infrastructure across multiple public and private clouds, networking, identity and access, compute and storage, and managing cloud capacity, quotas and cost as the fleet grows Improving deployment and infrastructure through code: GitOps-based configuration and deployment and infrastructure-as-code across our public and private clouds, with safe, previewed, recoverable production changes Defining and instrumenting SLOs and error budgets and building the dashboards, metrics and alerting that make production observable and actionable Reducing operational toil through automation and internal tooling written in Python and / or Go Provisioning and standardizing new production environments to a defined reliability bar

You're a great fit if you:

Have 3+ years in SRE, production / platform engineering, or infrastructure-heavy software engineering, operating real production systems under reliability expectations Are strong at container-orchestration operations in production and comfortable on at least one major public cloud Have solid cloud infrastructure experience on a major public cloud and a working grasp of cloud capacity, quotas, and cost Practice observability hands-on with metrics, logs and traces, and use it to root-cause live incidents Work fluently with infrastructure-as-code and GitOps Can code in Python and / or Go for automation, tooling, and reading and patching service code. Bring sound production judgment and document your work clearly for other engineers Bonus: experience operating a large-scale search or distributed data system, database operations, dedicated / enterprise-deployed software, or AI / enterprise-search infrastructure in regulated domains

Fähigkeiten

DockerPythonGoKubernetesAWSAzure

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