Hybrid

Customer Reliability Engineer

Berlin, Germany
,
Barcelona, Spain
,
Permanent employee
Full-time
TL;DR

Why this role exists: Land value fast and keep it running. You embed with strategic customers to design, build, and operationalize deployments of our platform and then leave behind all required resources and capabilities so that our customers feel confident and self-sufficient.

Why deepset

At deepset, we’re on a mission to make custom AI solutions accessible to every organization. With Haystack, thousands of developers build advanced LLM applications every day, while our enterprise-ready AI Platform helps companies turn large language models into business value. We’re remote-first, flexible, and built on a culture of trust and ownership. You’ll collaborate with top-tier tech talent, tackle meaningful challenges, and help transform complex AI into solutions that are simple, powerful, and ready for the real world.

What you will do

Design & Land

  • Own technical outcomes from POC → production: integrations, data connectors, workflows, and infra-as-code (Kubernetes/Terraform/Helm).
  • Produce reference architectures and reusable templates; upstream patterns to Product to reduce future “custom” work.
  • Unblock enterprise environments: identity (OIDC/SAML), networking, storage, GPU scheduling, observability hooks.

Run & Harden

  • Define SLOs/Error Budgets with customers; implement end-to-end observability (logs/metrics/traces) and dashboards.
  • Create runbooks/playbooks; lead L3 incident response and RCAs; drive reliability roadmaps to closure.
  • Plan/execute upgrades and security patches in change windows; ensure rollback and post-upgrade verification.
  • Be an active member of the on-call rotation to make sure we deliver excellent customer experience

Partner & Enable

  • Train customer teams on operations and emergency procedures; hand off cleanly to Support/CSM.
  • Prioritize reliability and “productization” backlog with Product/Engineering based on field signal.
  • Document clearly: setup guides, diagrams, SLOs, testing/DR procedures, and “golden path” standards.

Requirements
  • Hands on experience in programming language in Python (needed for improvements, bug fixing and small feature builds)
  • 5+ years across SRE/Platform/Solutions/FDE, with evidence of shipping customer-facing builds and operating production systems.
  • Strong with Kubernetes, containers, Linux, IaC (Terraform/Helm), CI/CD, networking (TLS, DNS, ingress/LB), backup/restore.
  • Observability stacks (Prometheus/Grafana/OpenTelemetry/ELK); scripting (Python/Bash).
  • Enterprise integration experience (SSO, secrets, compliance); confident communicator with execs and engineers under time pressure.
  • Must be resident of the European Union
Nice to have
  • German language skills
Benefits
  • Remote-first setup with flexible hours & tech of your choice
  • 30 days vacation + extra days for family sick leave
  • Competitive salary & stock options for every team member
  • Monthly sports & mental health support allowance with Oliva
  • Annual learning & development budget
  • Monthly team socials & in-person meetups
  • Dog-friendly Berlin HQ
About us

Founded in 2018, deepset builds open and enterprise-grade tools that help teams build AI with purpose. From Haystack, our open-source framework, to the deepset AI Platform, we give developers and organizations the building blocks to solve complex, high impact challenges with AI – with full control, transparency, and sovereignty. Backed by GV and Balderton, we’re growing the world’s production AI community and customer base solving challenges too critical to get wrong.

Visit us to learn more: deepset Website | Haystack Website | GitHub | Linkedin | X deepset (Twitter) | X haystack (Twitter)

About us

Our mission is to build technology that transforms how enterprises harness generative AI, making custom AI solutions accessible to any organization. We transform complex LLM development into intuitive building blocks, helping teams solve mission-critical business challenges while maintaining full control of their AI systems.

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