---
title: 'Senior/Staff AI Engineer, Quality & Evals (m/f/x) at Cortea AI'
canonical: 'https://feeny.ai/job/senior-staff-ai-engineer-quality-evals-m-f-x-cortea-ai-berlin-pt8krmzyze5t'
type: 'job'
last_seen: '2026-09-09'
---

# Senior/Staff AI Engineer, Quality & Evals (m/f/x) at Cortea AI

- **Company:** Cortea AI
- **Location:** Berlin, Germany
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-09-09
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/cortea/5ce1640d-2e8a-4c5e-a34c-3d434f54cbec

## Job description

## 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 EUR 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 backend, data, and AI systems experience to build the evaluation and observability foundation for production-grade LLM agents used in complex audit workflows.

This role sits at the intersection of backend engineering, data infrastructure, and AI quality. You will build the evaluation systems that power our multimodal retrieval agents and continuously improve critical quality metrics across current and future pipelines.

You’ll work at the edge of applied AI and information retrieval, building multimodal agentic pipelines and solving hard context and agent-harness engineering problems.

This is not a traditional analytics, BI, or dashboarding role. You should expect to write production code, design data architecture, work inside backend systems, and directly improve the quality, cost, reliability, and performance of LLM-based agents.

## WHAT YOU’LL DO

You will help build and operate the technical systems around our AI agents, with a focus on data infrastructure, evaluation, observability, and optimization. You will:

- Build online and offline evaluation systems for LLM agents, including pipelines that use golden datasets, ground-truth data, human review workflows, and experiment results.
- Create automated quality gates so changes to prompts, context, models, or agent logic can be tested before reaching production.
- Analyze large volumes of agent traces and executions in columnar and analytical databases such as BigQuery or ClickHouse to identify failure modes, quality regressions, latency issues, reliability gaps, and cost optimization opportunities.
- Build reliable data retention and replay mechanisms for long-term analysis of production agent behavior.
- Manage observability tools for tracing, monitoring, debugging, and experiment management of our audit agents.
- Team up with backend engineers to improve the speed and reliability of our retrieval and reasoning agents.

YOU WILL FIT INTO THE ROLE IF YOU...

- Have strong Python and/or backend engineering experience.
- Have a solid understanding of how LLM and agent systems are evaluated—including deterministic checks, ground truth, LLM-as-judge, human review, and quality metrics—and can reason about when each approach is appropriate.
- Have deployed and operated systems in the cloud, ideally on GCP.
- Have hands-on experience building end-to-end retrieval or ML pipeline evaluation systems and using LLM observability or experimentation tools such as Braintrust, MLflow, Langfuse, or Weights & Biases.
- Are 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.
- Bring senior-level engineering judgment: you can make architectural decisions, communicate trade-offs, and build systems that other engineers can extend.
- 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:

- Designing data pipelines, ETL/ELT workflows, event-processing systems, or feedback loops for production data.
- 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.

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.
- Attractive compensation: competitive salary plus significant equity.
- Best tools for the job: Generous coding tools budget so you can use the best tools for the job.
- Startup perks: Flexible vacation, team lunches, retreats, central Berlin office.

## INTERVIEW PROCESS

- First Call — Intro to Cortea with Liza https://www.linkedin.com/in/liza-shaban/
- Second Call — Technical interview with Vlad https://www.linkedin.com/in/vlad-tabakov/
- Third Call — Deep dive into our culture with our Co-Founder Philipp https://www.linkedin.com/in/philipp-hoevelmann/
- 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.

[https://app.ashbyhq.com/api/images/user-content/316125b8-3855-479e-a082-a30caf346d45/1ddbeed3-b4e6-4a47-8872-d5cfeee3e842/image.png]

## About Cortea AI

## Company Overview
- **One‑liner**: Cortea builds purpose‑built AI agents that help professional audit firms review work, surface inconsistencies, and produce traceable, defensible outputs while keeping human judgment in control.
- **Entity Type**: Private (Seed stage; raised €12M / $3.4M)
- **Headquarters**: Berlin, Germany (with offices in France and the Netherlands)
- **Founded**: 2024
- **Founders**: Valentin Neumann (CEO, former auditor at KPMG and early‑stage employee at N26) & Philipp Hövelmann (CPO, former CTO at audibene)

## Core Business
- **Industries**: Audit automation, financial technology, enterprise AI
- **Target customers**: B2B – professional audit firms (financial, IT, internal audit, and advisory practices)
- **Mission**: Provide high‑quality, transparent AI so auditors can review work more easily and focus on professional judgment – ultimately changing how trust is created in the global economy.

## Products & Services
- **AI Agents for Audit**: A suite of agents grounded in ISA, IFRS, HGB, IDW, and other audit standards. Key capabilities:
  - **Evidence Testing**: Automates manual testing, evidence review, and sample checks with full traceability.
  - **Financial Data Validation**: Validates figures against source documents and builds an audit trail ready for sign‑off.
  - **Disclosure & Compliance Checklists**: Runs automated completeness checks against IFRS, HGB, local GAAP, and IDW disclosure requirements.
  - **Risk Analysis & Audit Planning**: Identifies risk areas earlier and builds defensible audit plans aligned with ISA 315.
  - **Audit Team Collaboration**: Assigns tasks, tracks progress, and keeps milestones on schedule.
  - **File Requests**: Tracks requests, submissions, and engagement files to prevent gaps.
- **Platform Type**: SaaS – fully web‑based, uses a “white‑box” approach so every AI decision provides a verifiable logic path.
- **Security & Compliance**: Designed to meet ISO 27001, SOC 2 Type II, GDPR, and professional secrecy obligations; no client data is used to train models.

## Market Standing
- **Valuation / Market Cap**: Not disclosed (private company)
- **Key Metric**: Total funding **€12M / $3.4M** (Seed round, April 2025)
- **Notable Investors**:
  - Lead: **Cherry Ventures**
  - Co‑participants: **Dawn Capital**, **Mosaic Ventures**, **Discovery Ventures**
  - Notable angels: Larry Bradley (former Global Head of Audit, KPMG), Mehdi Ghissassi (Director Product, DeepMind), Jens Rassloff (Chairman Parloa), and others.
- **Growth Signals**:
  - Headcount grew **+63.6% YoY** to 12 employees (2024→2025).
  - **8 open positions** as of mid‑2025 (Senior Auditor, Chief of Staff, Fullstack Engineer, AI Product Manager, Founding Product Engineer, AI Audit Engineer, Data Engineer, Software Engineer).
  - Active in multiple geographies (Germany, France, Netherlands).

## Competitive Advantages
- **White‑Box AI**: Unlike black‑box models, Cortea’s agents provide a transparent, verifiable logic path – critical for regulated audits.
- **Domain‑Deep Team**: Founders and advisors include former KPMG auditors, BCG partners, and DeepMind PMs; methodology is built into the product from day one.
- **Methodology‑First**: Every agent speaks the language of ISA, IFRS, IDW, and local standards – results are professionally defensible.
- **Enterprise‑Grade Security**: ISO 27001, SOC 2 Type II, GDPR, and strict professional secrecy – no client data ever used for training.
- **AI‑Native Culture**: The company itself is built to operate like an AI‑first team – small, fast, shipping weekly, not quarterly.

## Strategic Focus
- **Deepen Audit‑AI Integration**: Continue expanding agent capabilities (evidence testing, disclosure checklists, risk planning) to cover the full audit lifecycle.
- **Scale Go‑to‑Market**: Use the fresh seed funding to build sales and customer success, especially in DACH, France, and the Netherlands.
- **Maintain Quality & Trust**: Stay “methodology first” and keep human judgment central – the auditor reviews, approves, and signs every conclusion.
- **Attract Top Talent**: Hiring aggressively for engineering, product management, and audit‑specialist roles to accelerate product development.

## Why Work Here
- **Culture**: “Builders, not managers” – bias for action, ship this week, not next quarter. Small team (12 people), high ownership, direct feedback, low ego.
- **Remote / Hybrid / Office**: Roles are advertised as **on‑site in Berlin** (e.g., Marketing, Engineering). However, the company already has distributed presence (France, Netherlands), so some flexibility may be possible – confirm during application.
- **Notable Perks / Engineering Culture**:
  - Everyone uses AI to multiply their own output – an “AI‑native” company, not just an AI product.
  - Deep work environment: “We love going deep” – they look for people who have gone unusually deep on a problem, regardless of domain.
  - High‑performance + warmth: Ambitious but not arrogant, human at heart.
  - Build with rigor and care – the work directly shapes how trust is created in the global economy.

## Sources
1. [Cortea Careers Page](https://cortea.ai/careers)
2. [Cortea Company Page](https://www.cortea.ai/company)
3. [Cortea Homepage](https://cortea.ai/)
4. [Cortea LinkedIn](https://de.linkedin.com/company/cortea-ai)
5. [Cortea Jobs on Ashby](https://jobs.ashbyhq.com/cortea)

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