Senior Site Reliability Engineer - Large-Scale AI Platforms

Embodied AI; Zürich; Hybrid; CHF 110.000 - 170.000; Vollzeit

Zusammenfassung

DeepJudge is seeking a Site Reliability Engineer to own the reliability of our large-scale AI search platform. You will operate production systems across multi-cloud environments, ensuring fast, available, and trusted services for leading law firms and enterprise users in Zurich and beyond.

You will harden platforms, implement observability, plan for capacity growth, and automate toil with Python and Go. Collaboration with product engineering and infrastructure teams will be key to delivering

Qualifikationen

• 3+ years in SRE, production/platform engineering, or infra-heavy software engineering.
• Experience operating real production systems under reliability expectations.
• Proficient in Python and/or Go for automation and tooling.
• Solid grasp of cloud infrastructure on a major public cloud.
• Hands-on observability with metrics, logs, and traces.
• Familiar with infrastructure-as-code and GitOps workflows.

Aufgaben

• Own availability, latency and performance of production environments: large-scale search and data stores across multi-cloud infra.
• Own cloud infrastructure, networking, IAM, compute and storage, and manage capacity and costs.
• Improve deployment/infrastructure with code: GitOps and IaC across clouds.
• Define/instrument SLOs and dashboards for observability and incident response.
• Reduce toil via automation and internal tooling (Python/Go).
• Provision and standardize new production environments to a defined reliability bar.

Kenntnisse

SRE

Container orchestration

Python

Go

GitOps

Cloud (public)

Observability

Tools

Kubernetes

Jobbeschreibung

DeepJudge is seeking a Site Reliability Engineer to own the reliability of our large-scale AI search platform. You will operate production systems across multi-cloud environments, ensuring fast, available, and trusted services for leading law firms and enterprise users in Zurich and beyond.

You will harden platforms, implement observability, plan for capacity growth, and automate toil with Python and Go. Collaboration with product engineering and infrastructure teams will be key to delivering