Abrar Admin

Cortea

<div>
 
 About Us
 
 
 
 We&rsquo;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 &gt;15m funding, with a working product and paying customers, we&rsquo;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&rsquo;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:
 
 
 <ul>
 <li>
 Building online and offline evaluation systems for LLM agents, including pipelines that use golden datasets, ground-truth data, human review workflows, and experiment results.
 </li>
 <li>
 Creating automated quality gates so changes to prompts, context, models, or agent logic can be tested before reaching production.
 </li>
 <li>
 Analyzing large volumes of agent traces and executions to identify failure modes, quality regressions, latency issues, reliability gaps, and cost optimization opportunities.
 </li>
 <li>
 Working with columnar data stores and analytical databases such as BigQuery, ClickHouse, or similar technologies.
 </li>
 <li>
 Building reliable data retention and replay mechanisms for long-term analysis of production agent behaviour.
 </li>
 <li>
 Creating observability tooling for trace analysis, experiment monitoring, production dashboards, logging, tracing, and debugging.
 </li>
 <li>
 Working inside our core backend and agent architecture, including building new agents or improving existing agents when needed.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 You will fit into this role if you:
 
 
 <ul>
 <li>
 Have strong Python and/or backend engineering experience.
 </li>
 <li>
 Have strong SQL skills and are comfortable working with large datasets.
 </li>
 <li>
 Have deployed and operated systems in the cloud, ideally on GCP.
 </li>
 <li>
 Have practical experience designing data pipelines, ETL/ELT workflows, event-processing systems, or feedback loops for production data.
 </li>
 <li>
 Are comfortable working with analytical databases, data warehouses, columnar stores, and high-volume event or trace data.
 </li>
 <li>
 Understand system design, reliability, observability, monitoring, logging, debugging, and operational trade-offs.
 </li>
 <li>
 Can work in complex existing systems and quickly build a mental model of how they operate.
 </li>
 <li>
 Bring senior-level engineering judgment: you can make architectural decisions, communicate trade-offs, and build systems that other engineers can extend.
 </li>
 <li>
 Are comfortable with ambiguity, able to reason from first principles, and excited to build infrastructure for AI systems that are actively used in production.
 
 
 </li>
 </ul>
 Nice-to-haves that are a plus:
 
 
 <ul>
 <li>
 Building infrastructure around LLM-based products or agentic systems, including optimizing LLM usage, context windows, reasoning tokens, or model selection.
 </li>
 <li>
 Working with production traces from complex distributed systems.
 </li>
 <li>
 Building internal platforms for engineers, domain experts, or operations teams.
 </li>
 <li>
 Using workflow orchestration systems such as Temporal or similar.
 </li>
 <li>
 Familiarity with audit, finance, compliance, or other high-accuracy domains.
 </li>
 <li>
 Experience in an early-stage startup or fast-moving engineering environment.
 
 
 </li>
 </ul>
 
 No one checks every box. If you&rsquo;ve shipped retrieval systems and like owning evaluations and pipelines, let&rsquo;s talk.
 
 
 
 
 What we offer
 
 
 
 <ul>
 <li>
 High impact &amp; growth: Shape strategy at a scaling AI startup from day one
 </li>
 <li>
 Mission-driven culture: Ambitious team valuing first-principles thinking and bold ideas
 </li>
 <li>
 Attractive compensation: competitive salary plus significant equity
 </li>
 <li>
 Personal development: Learning budget for courses and conferences
 </li>
 <li>
 Startup perks: Flexible vacation, team lunches, retreats, central Berlin office
 
 
 </li>
 </ul>
 
 Interview process
 
 
 
 <ul>
 <li>
 First Call &mdash; Intro to Cortea with our Talent Partner Adriana
 </li>
 <li>
 Second Call &mdash; Technical interview with Jendrik
 </li>
 <li>
 Third Call &mdash; Deep dive into our culture with our Co-Founder Philipp
 </li>
 <li>
 On-site Day (Berlin) &mdash; Meet the team and work on a real problem together
 
 
 </li>
 </ul>
 
 We&rsquo;re an equal-opportunity team and encourage women and underrepresented groups to apply.
 
 
 
</div>

Software Engineer, Data & AI Platform (m/f/x)

Join Cortea and explore 1   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Cortea

About Company

Software Engineer, Data & AI Platform (m/f/x)