This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Observability Engineer based in Germany.
This role offers the opportunity to build and evolve the observability foundation behind advanced AI platforms.
You will help ensure AI workloads, LLM applications, and cloud infrastructure remain measurable, reliable, and production-ready.
Working at the intersection of AI engineering, cloud platforms, and DevOps, you will design systems that improve visibility, performance, and operational excellence.
You will contribute to monitoring strategies, telemetry pipelines, dashboards, and automation frameworks supporting large-scale AI environments.
The role requires a strong engineering mindset, hands-on technical expertise, and the ability to transform complex operational data into actionable insights.
This is an opportunity to shape the reliability of next-generation AI infrastructure within an innovative and globally distributed environment.
Accountabilities:
As an AI Observability Engineer, you will own the tools, processes, and systems that provide visibility into AI applications, platform services, and infrastructure performance. You will collaborate with engineering teams to improve reliability, detect issues proactively, and establish scalable observability practices.
- Design, implement, and operate observability solutions for AI workloads, including LLM and agent monitoring.
- Configure and maintain AI tracing systems to capture latency, token usage, cost, quality metrics, prompt analytics, model versions, and safety signals.
- Develop internal tooling and automation solutions using Python for instrumentation and data collection.
- Build and maintain dashboards, metrics, and monitoring solutions using Grafana, Prometheus, and cloud observability platforms.
- Instrument AI platforms and workloads to provide visibility into health, usage, performance, cost, and service-level objectives.
- Create actionable telemetry pipelines and operational insights to support platform engineering improvements.
- Manage infrastructure-as-code workflows using Terraform and maintain CI/CD pipelines for observability tooling.
- Support incident investigations, troubleshooting activities, and root-cause analysis.
- Define and improve monitoring strategies around logs, metrics, traces, alerting, SLIs, and SLOs.
- Collaborate with engineering teams to enhance reliability, scalability, and operational maturity across AI systems.
Requirements:
The ideal candidate is an experienced observability, SRE, DevOps, or cloud engineering professional with strong expertise in monitoring AI-driven systems and building reliable production environments.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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