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Senior Data / AI Infrastructure Engineer

HRvizer

BerlinOn-siteFull-Time1w ago

Description

HRvizer is currently supporting a fast-growing AI startup in Berlin in hiring a Senior Engineer to join their core technical team.

The company operates in the AI automation space, building production-grade LLM-based systems that help reduce manual, document-heavy workflows in complex, knowledge-intensive environments.

They are well-funded, already live with paying customers, and currently scaling their engineering organization.

The Role

We are looking for a Senior Engineer with strong backend and data infrastructure experience to build the foundation for evaluation, observability, and performance optimization of LLM-powered systems.

This role sits at the intersection of:

  • Backend engineering
  • Data engineering
  • AI/LLM infrastructure
  • Observability & reliability systems

You will work directly on production systems that monitor, evaluate, and improve AI agents at scale.

What you will do:

  • Build evaluation frameworks for LLM agents (offline + online testing, datasets, human feedback loops)
  • Design automated quality gates for changes in models, prompts, and agent logic
  • Analyse large-scale production traces to identify failures, regressions, latency, and cost issues
  • Work with analytical databases (BigQuery, ClickHouse or similar)
  • Build data replay, retention, and debugging systems for production behaviour
  • Develop observability tooling (logging, tracing, dashboards, monitoring)
  • Contribute to backend and agent infrastructure where needed

Requirements

  • Strong experience in Python and/or backend engineering
  • Advanced SQL skills and experience with large datasets
  • Experience working in cloud environments (GCP preferred)
  • Experience building data pipelines, ETL/ELT, or event-driven systems
  • Strong understanding of system design, reliability, and observability
  • Ability to work in complex systems and ambiguous environments
  • Strong engineering judgment and architectural thinking

Nice to have

  • Experience with LLMs, agentic systems, or AI infrastructure
  • Experience working with distributed system traces
  • Experience building internal platforms or developer tools
  • Familiarity with workflow orchestration tools (e.g. Temporal)
  • Background in audit, finance, or compliance environments
  • Experience in early-stage startups or scale-ups

What’s offered

  • High-impact role in a fast-scaling AI company
  • Strong ownership from day one
  • Competitive salary + equity
  • Learning & development budget
  • Flexible work culture + team events

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