About Us
We’re
Cortea
, a Berlin startup
transforming audits with AI
. Manual, document-heavy audits waste expert time while demand keeps rising. Our
AI-powered software and specialized AI agents
remove the repetitive work so auditors can focus on judgment.
Backed by top-tier VCs with >15m funding, with a working product and paying customers, we’re rapidly scaling.
We value
first-principles thinking, speed, trust, and kindness
. We build side by side
in our Berlin office
.
Your Role
We are looking for an
Engineer with strong data engineering and AI systems experience
to build the data, evaluation, and observability foundation for production-grade LLM agents used in complex audit workflows.
This role sits at the intersection of
backend engineering, data engineering, AI infrastructure, and LLM operations
. You will work hands-on in our backend and agent architecture, building the systems that help us evaluate, monitor, debug, optimize, and continuously improve AI agents in production.
This is
not
a traditional analytics, BI, or dashboarding role. You should expect to write production code, design infrastructure, work inside backend systems, and directly improve the quality, cost, reliability, and performance of LLM-based agents.
What You’ll Do
You will help building and operating the technical infrastructure around our AI agents, with a focus on data infrastructure, evaluation, observability, and optimization. Your work will include:
-
Building online and offline evaluation systems for LLM agents, including pipelines that use golden datasets, ground-truth data, human review workflows, and experiment results.
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Creating automated quality gates so changes to prompts, context, models, or agent logic can be tested before reaching production.
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Analyzing large volumes of agent traces and executions to identify failure modes, quality regressions, latency issues, reliability gaps, and cost optimization opportunities.
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Working with columnar data stores and analytical databases such as BigQuery, ClickHouse, or similar technologies.
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Building reliable data retention and replay mechanisms for long-term analysis of production agent behaviour.
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Creating observability tooling for trace analysis, experiment monitoring, production dashboards, logging, tracing, and debugging.
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Working inside our core backend and agent architecture, including building new agents or improving existing agents when needed.
Qualifications
You will fit into this role if you:
-
Have strong Python and/or backend engineering experience.
-
Have strong SQL skills and are comfortable working with large datasets.
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Have deployed and operated systems in the cloud, ideally on GCP.
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Have practical experience designing data pipelines, ETL/ELT workflows, event-processing systems, or feedback loops for production data.
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Are comfortable working with analytical databases, data warehouses, columnar stores, and high-volume event or trace data.
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Understand system design, reliability, observability, monitoring, logging, debugging, and operational trade-offs.
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Can work in complex existing systems and quickly build a mental model of how they operate.
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Bring senior-level engineering judgment: you can make architectural decisions, communicate trade-offs, and build systems that other engineers can extend.
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Are comfortable with ambiguity, able to reason from first principles, and excited to build infrastructure for AI systems that are actively used in production.
Nice-to-haves that are a plus:
-
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.
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Building internal platforms for engineers, domain experts, or operations teams.
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Using workflow orchestration systems such as Temporal or similar.
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Familiarity with audit, finance, compliance, or other high-accuracy domains.
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Experience in an early-stage startup or fast-moving engineering environment.
No one checks every box. If you’ve shipped retrieval systems and like owning evaluations and pipelines, let’s talk.
What we offer
-
High impact & growth: Shape strategy at a scaling AI startup from day one
-
Mission-driven culture: Ambitious team valuing first-principles thinking and bold ideas
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Attractive compensation: competitive salary plus significant equity
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Personal development: Learning budget for courses and conferences
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Startup perks: Flexible vacation, team lunches, retreats, central Berlin office
Interview process
-
First Call — Intro to Cortea with our Talent Partner Adriana
-
Second Call — Technical interview with Jendrik
-
Third Call — Deep dive into our culture with our Co-Founder Philipp
-
On-site Day (Berlin) — Meet the team and work on a real problem together
We’re an equal-opportunity team and encourage women and underrepresented groups to apply.