Software Engineer, Data & AI Platform (m/f/x)
On-siteBerlin, State of Berlin, Germany
Job Summary
Build and operate the technical infrastructure for production-grade LLM agents, focusing on data infrastructure, evaluation, and observability. Create automated quality gates for prompt and model changes, then analyze large volumes of agent traces to identify failure modes, latency issues, and cost optimization opportunities. Work with columnar data stores like BigQuery or ClickHouse to design pipelines, ETL workflows, and retention mechanisms for long-term behavior analysis. Develop observability tooling for trace analysis, experiment monitoring, and debugging within our core backend architecture. This role sits at the intersection of backend engineering, data engineering, and AI operations at Cortea, a Berlin startup transforming audits with AI.
Required Qualifications
- strong Python and/or backend engineering experience
- strong SQL skills
- comfortable working with large datasets
- deployed and operated systems in the cloud, ideally on GCP
- practical experience designing data pipelines, ETL/ELT workflows, event-processing systems, or feedback loops for production data
- comfortable working with analytical databases, data warehouses, columnar stores, and high-volume event or trace data
- understand system design, reliability, observability, monitoring, logging, debugging, and operational trade-offs
- can work in complex existing systems and quickly build a mental model of how they operate
- senior-level engineering judgment: you can make architectural decisions, communicate trade-offs, and build systems that other engineers can extend
- comfortable with ambiguity
- able to reason from first principles
- excited to build infrastructure for AI systems that are actively used in production
Desired Qualifications
- Building infrastructure around LLM-based products or agentic systems, including optimizing LLM usage, context windows, reasoning tokens, or model selection
- Working with production traces from complex distributed systems
- Building internal platforms for engineers, domain experts, or operations teams
- Using workflow orchestration systems such as Temporal or similar
- Familiarity with audit, finance, compliance, or other high-accuracy domains
- Experience in an early-stage startup or fast-moving engineering environment
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