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Team Passerelle

<div><p>Wir sind das Team Passerelle, eine 2025 in Berlin gegr&uuml;ndete KI-Beratung aus dem gewerkschaftlichen Umfeld. Unser Name ist Programm: <i>Passerelle</i> bedeutet Br&uuml;cke. Wir sind angetreten, um inmitten der gr&ouml;&szlig;ten Transformation der Arbeitswelt genau diese Br&uuml;cke in die Zukunft zu bauen - eine Br&uuml;cke, die echten technologischen Fortschritt erm&ouml;glicht und gleichzeitig bessere Arbeitsbedingungen schafft. All das machen wir unter dem Leitsatz: Gute KI. Gute Arbeit.</p>
<p>
Gegr&uuml;ndet von erfahrenen K&ouml;pfen aus der Tech- und Beratungswelt sowie der angewandten KI-Wissenschaft, verbinden wir strategischen C-Level-Weitblick mit tiefem technologischem Sachverstand. Wir begleiten Organisationen und Institutionen auf ihrem Weg in eine KI-gepr&auml;gte Zukunft, von der strategischen Beratung &uuml;ber die werteorientierte technische Implementierung bis zur nachhaltigen Adoption im Betrieb. Neben unseren Transformationsmandaten entwickeln wir au&szlig;erdem eigene Software-Produkte f&uuml;r digitale Souver&auml;nit&auml;t.</p>
<h2 class="jobSectionHeader"><b>
Aufgaben</b></h2>
<p>
Als Data &amp; AI Engineer schaffst du bei uns die zwingende technische Voraussetzung f&uuml;r jeden erfolgreichen KI-Einsatz: eine belastbare und strukturierte Datenbasis. Dein Schwerpunkt liegt darauf, historisch gewachsene, heterogene Datenlandschaften zu erschlie&szlig;en und f&uuml;r moderne KI-Anwendungen, insbesondere Retrieval-Systeme, nutzbar zu machen.</p>
<p>
Als eine:r der ersten dedizierten Engineering-Hires gestaltest du den Aufbau unserer technischen Umsetzungskraft mit &ndash; eng an der Seite unseres AI Solutions Architect. Dein T&auml;tigkeitsfeld umfasst zwei Bereiche: In unseren Beratungsmandaten analysierst du die bestehende Datenarchitektur, deckst L&uuml;cken auf und legst das Fundament f&uuml;r die KI-Strategie. Parallel dazu entwickelst du die Daten- und Retrieval-Pipelines f&uuml;r unsere eigene KI-Infrastruktur und Software-Produkte.</p>
<p>
**<br>
Deine Aufgaben**</p>
<ul>
<li><b>Datenbestandsaufnahme &amp; Reifegrad:</b> Du erstellst Datenlandkarten &uuml;ber heterogene Best&auml;nde hinweg und bewertest den Reifegrad des digitalen Fundaments. Deine L&uuml;ckenanalysen zu Identifikatoren und Metadaten zeigen pr&auml;zise, wo der Hebel liegt.</li>
<li><b>AI Data Ingestion (KI-Enablement):</b> Du erschlie&szlig;t unstrukturierte Datenquellen (PDFs, Berichte, Publikationen) f&uuml;r die Nutzung in KI-Systemen &ndash; Text-Extraktion, Chunking-Strategien, Metadaten-Generierung, z. B. mit Werkzeugen wie LlamaParse oder Unstructuredio.</li>
<li><b>Datenfundament &amp; Retrieval:</b> Du entwickelst Metadaten- und Identifikatorkonzepte, Datenmodelle und Embedding-Pipelines und baust die Retrieval-Grundlage f&uuml;r RAG-Anwendungen &ndash; inklusive Bef&uuml;llung und Betrieb von Vektordatenbanken (z. B. Qdrant, Weaviate, pgvector). Die Qualit&auml;t dieser Grundlage bewertest du systematisch.</li>
<li><b>Datenschutz &amp; Souver&auml;nit&auml;t:</b> Du gehst verantwortungsvoll mit sensiblen Daten um und stimmst dich eng zu AI-Governance-, Datenschutz, EU AI Act und Souver&auml;nit&auml;tsanforderungen ab. Datensparsamkeit und Schutzw&uuml;rdigkeit denkst du von Anfang an mit.</li>
<li><b>Pipelines f&uuml;r interne Software-Entwicklung:</b> Du baust und betreibst perspektivisch die Ingest- und Retrieval-Pipelines f&uuml;r eigene Software-Produkte &ndash; mit DataOps-Mindset (Versioning, Testing, Observability) und einem Verst&auml;ndnis agentischer Muster inkl. Human-in-the-loop.</li>
</ul><h2 class="jobSectionHeader"><b>Qualifikation</b></h2>
<ul><li><b>Fundierte Data-Engineering-Erfahrung:</b> Mehrj&auml;hrige (3+ Jahre) im Data Engineering oder als Data Platform Engineer &ndash; idealerweise in gewachsenen, heterogenen Datenlandschaften. Exzellentes Python und SQL sowie sicherer Umgang mit dem Modern Data Stack (z. B. dbt, Airflow, Dagster) und ETL-/ELT-Prozessen.</li>
<li><b>KI-Enablement:</b> Praktische Erfahrung mit Embedding-Pipelines und Vektordatenbanken (z. B. Qdrant, Weaviate, Milvus, pgvector), ein Gesp&uuml;r f&uuml;r Retrieval-Strategien und Erfahrung mit der Erschlie&szlig;ung unstrukturierter Daten (z. B. LlamaParse, Unstructuredio).</li>
<li><b>Datenschutz-Bewusstsein:</b> Erfahrung im verantwortungsvollen Umgang mit sensiblen und personenbezogenen Daten sowie Kenntnis der einschl&auml;gigen Anforderungen (insb. DSGVO, EU-AI-Act-Awareness).</li>
<li><b>Pragmatismus bei realer Datenlage:</b> Du f&uuml;hlst dich in unvollst&auml;ndigen, gewachsenen Datenbest&auml;nden wohl und wei&szlig;t, dass ein nutzbares Datenmodell mehr wert ist als ein perfektes. Du priorisierst, wo es z&auml;hlt.</li>
<li><b>Kommunikationsst&auml;rke &amp; Haltung:</b> Du &uuml;bersetzt die Datenrealit&auml;t verst&auml;ndlich f&uuml;r nicht-technische Stakeholder und kommunizierst auf Augenh&ouml;he mit Fachbereichen. Dein Deutsch und Englisch ist verhandlungssicher. Du steuerst dich selbst, denkst l&ouml;sungsorientiert und teilst unsere Werte rund um eine gerechte Arbeitswelt von morgen.</li>
</ul>
<p><b>Sch&ouml;n, wenn du zus&auml;tzlich mitbringst:</b> Erfahrung mit Knowledge Graphs, Semantic Layer oder Text-to-SQL; ausgepr&auml;gtes DataOps-Mindset; Lust an PoCs mitzubauen</p>
<h2 class="jobSectionHeader"><b>
Benefits</b></h2>
<ul><li><b>Echter Impact &amp; Haltung:</b> Ein Arbeitsumfeld, das technologische Innovation mit gesellschaftlicher Verantwortung und nachhaltigen Werten verbindet. Du gestaltest die KI-Transformation an vorderster Front nach europ&auml;ischen, demokratischen Werten.</li>
<li><b>Sichtbarkeit &amp; Netzwerk:</b> Einblicke in hochkar&auml;tige Mandate aus Politik, Wirtschaft und Gewerkschaften</li>
<li><b>Hohe Autonomie:</b> Flache Strukturen, die bewusste Abwesenheit von Mikromanagement und echte Verantwortung f&uuml;r deine Accounts und Themen</li>
<li><b>Flexibles Set-up:</b> Remote-first mit einem Kernteam in Berlin sowie flexiblen Arbeitszeiten, die zu deinem Leben passen.</li>
<li><b>Standards:</b> 30 Tage Urlaub, ein eigenes Weiterbildungsbudget und modernste Arbeitsausstattung</li>
<li><b>Faire Verg&uuml;tung:</b> Ein transparentes Gehaltsband von 80.000 bis 95.000 &euro; brutto p.a. auf Basis einer 40h Woche (je nach Erfahrung)</li>
</ul>
<ul><li><b>Langfristige Perspektive:</b> Die Stelle ist aufgrund unserer agilen Startup-Phase zun&auml;chst auf ein Jahr befristet. Da wir uns im nachhaltigen Aufbau befinden, ist eine langfristige Zusammenarbeit unser klares Ziel. Eine Verl&auml;ngerung oder Entfristung wird bei entsprechender Mandats- und Gesch&auml;ftsentwicklung ausdr&uuml;cklich angestrebt.</li></ul>
<p><i>
Der Kern unserer Arbeit ist die sozialpartnerschaftliche Gestaltung der KI-Transformation - von der fairen Verteilung von Produktivit&auml;tsgewinnen &uuml;ber die digitale Souver&auml;nit&auml;t bis hin zur Frage, wie wir eine gerechte Arbeitswelt von morgen bauen. Wir brennen f&uuml;r diese Themen und wollen diese Br&uuml;cke in die Zukunft nicht nur theoretisch durchdenken, sondern ganz praktisch bauen.</i></p>
<p><i>
Daf&uuml;r suchen wir kluge K&ouml;pfe mit Haltung und Can-Do-Attitude, die um die Ecke denken und keine Angst haben, Annahmen zu hinterfragen. Bewirb dich ausdr&uuml;cklich auch dann, wenn dein Lebenslauf nicht perfekt auf die Beschreibung passt - f&uuml;r uns z&auml;hlen deine Perspektive und dein innerer Antrieb weit mehr als ein l&uuml;ckenloses Profil. Wenn du Lust hast, ein junges Unternehmen mitzupr&auml;gen und der Zukunft der Arbeit deinen Stempel aufzudr&uuml;cken:</i> <b><i>Join us!</i></b></p></div>

Data & AI Engineer (m/w/d)

Snowflake

<div><div><p>At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don&rsquo;t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset &mdash; who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.</p><div><p><b>
ABOUT THE ROLE</b></p></div><p>
We are looking for talented Software Engineers to join our Data Platform team. You will design, build, and operate large-scale distributed data systems that power Snowflake's core platform. This role is open to both new college graduates (MSc/PhD) and early career professionals.</p><p></p><div><p><b>
WHAT YOU'LL DO</b></p></div><ul><li><p>
Design and implement scalable, high-throughput data processing systems</p></li><li><p>
Build and maintain real-time and batch data pipelines</p></li><li><p>
Collaborate cross-functionally with product, infrastructure, and data science teams</p></li><li><p>
Contribute to architectural decisions and technical roadmaps</p></li><li><p>
Write clean, tested, production-quality code at scale</p></li></ul><p></p><div><p><b>
WHAT WE'RE LOOKING FOR</b></p></div><p><b>
Required:</b></p><ul><li><p>
BS/MS/PhD in Computer Science, Engineering, or related field (or equivalent experience)</p></li><li><p>
Strong foundation in distributed systems, algorithms, and data structures</p></li><li><p>
Proficiency in Java, Scala, Python, or C++</p></li><li><p>
Experience with large-scale data systems or cloud platforms</p></li></ul><p></p><p><b>
Strongly Desirable:</b></p><ul><li><p>
Experience with <b>Apache Flink</b> and/or <b>Apache Spark</b> for stream or batch processing</p></li><li><p>
Familiarity with <b>AI-augmented software development</b> practices &mdash; using LLMs/Copilot tools to accelerate engineering workflows, prototype solutions, and improve code quality</p></li><li><p>
Experience with Kafka, data lakehouse architectures, or SQL engines</p></li></ul><p>
Snowflake is growing fast, and we&rsquo;re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.</p><p>
How do you want to make your impact?</p><p>
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com</p></div></div>

Software Engineer, Data Transformation

Speechify

<div><p>The mission of Speechify is to make sure that reading is never a barrier to learning.</p>
<p>
Over 50 million people use Speechify's text-to-speech products to turn whatever they're reading &ndash; PDFs, books, Google Docs, news articles, websites &ndash; into audio, so they can read faster, read more, and remember more. Speechify's text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.
</p><p>Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting &ndash; Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.</p>
<p><b>
Overview</b></p>
<p>
We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.</p>
<p><b>
What You'll Do</b></p>
<ul>
<li>Be scrappy to find new sources of audio data and bring it into our ingestion pipeline</li>
<li>Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.</li>
<li>Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.</li>
<li>Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team's dataset roadmap to power Speechify's next-generation consumer and enterprise products.</li>
</ul>
<p><b>An Ideal Candidate Should Have</b></p>
<ul>
<li>BS/MS/PhD in Computer Science or a related field.</li>
<li>5+ years of industry experience in software development.</li>
<li>Proficiency with bash/Python scripting in Linux environments</li>
<li>Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)</li>
<li>Experience with web crawlers, large-scale data processing workflows is a plus</li>
<li>Ability to handle multiple tasks and adapt to changing priorities.</li>
<li>Strong communication skills, both written and verbal.</li>
</ul>
<p><b>What we offer</b></p>
<ul>
<li>A fast-growing environment where you can help shape the company and product.</li>
<li>An entrepreneurial-minded team that supports risk, intuition, and hustle.</li>
<li>A hands-off management approach so you can focus and do your best work.</li>
<li>An opportunity to make a big impact in a transformative industry.</li>
<li>Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.</li>
<li>Opportunity to work on a life-changing product that millions of people use.</li>
<li>Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.</li>
<li>Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.</li>
</ul>
<p><b>The Germany Based </b>Salary range for this role is: 30,000-120,000 USD/Year + Bonus + Stock depending on experience.</p>
<p><b>
Think you're a good fit for this job?</b></p>
<p>
Tell us more about yourself and why you're interested in the role when you apply.
<br>
And don't forget to include links to your portfolio and LinkedIn.</p>
<p><b>
Not looking but know someone who would make a great fit?</b></p>
<p>
Refer them!</p>
<p><b>
Speechify is committed to a diverse and inclusive workplace.</b></p>
<p>
Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.</p></div>

Software Engineer, Data Infrastructure & Acquisition - Berlin, Germany

Cortea

<div>
 <strong>
  About Us
  <br/>
  <br/>
 </strong>
 We&rsquo;re
 <strong>
  Cortea
 </strong>
 , a Berlin startup
 <strong>
  transforming audits with AI
 </strong>
 . Manual, document-heavy audits waste expert time while demand keeps rising. Our
 <strong>
  AI-powered software and specialized AI agents
 </strong>
 remove the repetitive work so auditors can focus on judgment.
 <br/>
 <br/>
 Backed by top-tier VCs with &gt;15m funding, with a working product and paying customers, we&rsquo;re rapidly scaling.
 <br/>
 <br/>
 We value
 <strong>
  first-principles thinking, speed, trust, and kindness
 </strong>
 . We build side by side
 <strong>
  in our Berlin office
 </strong>
 .
 <br/>
 <br/>
 <strong>
  Your Role
  <br/>
  <br/>
 </strong>
 We are looking for an
 <strong>
  Engineer with strong data engineering and AI systems experience
 </strong>
 to build the data, evaluation, and observability foundation for production-grade LLM agents used in complex audit workflows.
 <br/>
 <br/>
 This role sits at the intersection of
 <strong>
  backend engineering, data engineering, AI infrastructure, and LLM operations
 </strong>
 . 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.
 <br/>
 <br/>
 This is
 <strong>
  not
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  What You&rsquo;ll Do
  <br/>
  <br/>
 </strong>
 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:
 <br/>
 <br/>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 You will fit into this role if you:
 <br/>
 <br/>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 Nice-to-haves that are a plus:
 <br/>
 <br/>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  No one checks every box. If you&rsquo;ve shipped retrieval systems and like owning evaluations and pipelines, let&rsquo;s talk.
  <br/>
  <br/>
 </strong>
 <strong>
  What we offer
  <br/>
  <br/>
 </strong>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Interview process
  <br/>
  <br/>
 </strong>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  We&rsquo;re an equal-opportunity team and encourage women and underrepresented groups to apply.
  <br/>
  <br/>
 </em>
</div>


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

Cortea AI

<div><h1 class="jobSectionHeader"><b>About us</b></h1><p>
We&rsquo;re <b>Cortea</b>, a Berlin startup <b>transforming audits with AI</b>. Manual, document-heavy audits waste expert time while demand keeps rising. Our <b>AI-powered software and specialized AI agents</b> remove the repetitive work so auditors can focus on judgment.</p><p>
Backed by top-tier VCs with &gt;15m funding, with a working product and paying customers, we&rsquo;re rapidly scaling.</p><p>
We value <b>first-principles thinking, speed, trust, and kindness</b>. We build side by side <b>in our Berlin office</b>.</p><p></p><h1 class="jobSectionHeader"><b>
Your Role</b></h1><p>
We are looking for an <b>Engineer with strong data engineering and AI systems experience</b> to build the data, evaluation, and observability foundation for production-grade LLM agents used in complex audit workflows.</p><p>
This role sits at the intersection of <b>backend engineering, data engineering, AI infrastructure, and LLM operations</b>. 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.</p><p>
This is <b>not</b> 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.</p><p></p><h1 class="jobSectionHeader"><b>
What you&rsquo;ll do</b></h1><p>
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:</p><ul><li><p>
Building online and offline evaluation systems for LLM agents, including pipelines that use golden datasets, ground-truth data, human review workflows, and experiment results.</p></li><li><p>
Creating automated quality gates so changes to prompts, context, models, or agent logic can be tested before reaching production.</p></li><li><p>
Analyzing large volumes of agent traces and executions to identify failure modes, quality regressions, latency issues, reliability gaps, and cost optimization opportunities.</p></li><li><p>
Working with columnar data stores and analytical databases such as BigQuery, ClickHouse, or similar technologies.</p></li><li><p>
Building reliable data retention and replay mechanisms for long-term analysis of production agent behaviour.</p></li><li><p>
Creating observability tooling for trace analysis, experiment monitoring, production dashboards, logging, tracing, and debugging.</p></li><li><p>
Working inside our core backend and agent architecture, including building new agents or improving existing agents when needed.</p></li></ul><p></p><h1 class="jobSectionHeader"><b>
Qualifications</b></h1><p>
You will fit into this role if you:</p><ul><li><p>
Have strong Python and/or backend engineering experience.</p></li><li><p>
Have strong SQL skills and are comfortable working with large datasets.</p></li><li><p>
Have deployed and operated systems in the cloud, ideally on GCP.</p></li><li><p>
Have practical experience designing data pipelines, ETL/ELT workflows, event-processing systems, or feedback loops for production data.</p></li><li><p>
Are comfortable working with analytical databases, data warehouses, columnar stores, and high-volume event or trace data.</p></li><li><p>
Understand system design, reliability, observability, monitoring, logging, debugging, and operational trade-offs.</p></li><li><p>
Can work in complex existing systems and quickly build a mental model of how they operate.</p></li><li><p>
Bring senior-level engineering judgment: you can make architectural decisions, communicate trade-offs, and build systems that other engineers can extend.</p></li><li><p>
Are comfortable with ambiguity, able to reason from first principles, and excited to build infrastructure for AI systems that are actively used in production.</p></li></ul><p>
Nice-to-haves that are a plus:</p><ul><li><p>
Building infrastructure around LLM-based products or agentic systems, including optimizing LLM usage, context windows, reasoning tokens, or model selection.</p></li><li><p>
Working with production traces from complex distributed systems.</p></li><li><p>
Building internal platforms for engineers, domain experts, or operations teams.</p></li><li><p>
Using workflow orchestration systems such as Temporal or similar.</p></li><li><p>
Familiarity with audit, finance, compliance, or other high-accuracy domains.</p></li><li><p>
Experience in an early-stage startup or fast-moving engineering environment.</p></li></ul><p><b>
No one checks every box. If you&rsquo;ve shipped retrieval systems and like owning evaluations and pipelines, let&rsquo;s talk.</b></p><p></p><h1 class="jobSectionHeader"><b>
What we offer</b></h1><ul><li><p><b>
High impact &amp; growth:</b> Shape strategy at a scaling AI startup from day one</p></li><li><p><b>
Mission-driven culture:</b> Ambitious team valuing first-principles thinking and bold ideas</p></li><li><p><b>
Attractive compensation:</b> competitive salary plus significant equity</p></li><li><p><b>
Personal development:</b> Learning budget for courses and conferences</p></li><li><p><b>
Startup perks:</b> Flexible vacation, team lunches, retreats, central Berlin office</p></li></ul><p></p><h1 class="jobSectionHeader"><b>
Interview process</b></h1><ul><li><p><b>
First Call</b> &mdash; Intro to Cortea with our Talent Partner Adriana</p></li><li><p><b>
Second Call</b> &mdash; Technical interview with Jendrik</p></li><li><p><b>
Third Call</b> &mdash; Deep dive into our culture with our Co-Founder Philipp</p></li><li><p><b>
On-site Day (Berlin) </b>&mdash; Meet the team and work on a real problem together</p></li></ul><p></p><p><i>
We&rsquo;re an equal-opportunity team and encourage women and underrepresented groups to apply.</i></p></div><div></div>

Schwarz Digits KG

<p></p><div><div><div><div><ul><li><div><div><h2 class="jobSectionHeader"><b>Standort</b></h2><div><div>
Karl-Liebknecht-Stra&szlig;e 32<br>
10178 Berlin</div></div></div></div></li><li><div><div><p>
</p></div><div><h2 class="jobSectionHeader"><b>Abteilung / Bereich</b></h2><div><div>
IT - Software Engineering</div></div></div></div></li><li><div><div><p>
</p></div><div><h2 class="jobSectionHeader"><b>Einstiegslevel</b></h2><div><div>
Berufserfahrene</div></div></div></div></li><li><div><div><p>
</p></div><div><h2 class="jobSectionHeader"><b>Arbeitsmodell</b></h2><div><div>
Vollzeit/Teilzeit</div></div></div></div></li><li><div><div><p>
</p></div><div><h2 class="jobSectionHeader"><b>Referenznummer</b></h2><div><div>
2794</div></div></div></div></li></ul></div></div></div>
<div><div><div><p>
Schwarz Digits schafft das technologische Fundament f&uuml;r digitale Entscheidungsfreiheit in Europa. Als IT- und Digitalsparte der Schwarz Gruppe entwickeln und verantworten wir einerseits die IT-Infrastrukturen f&uuml;r die Handelssparten Lidl und Kaufland sowie die Schwarz Produktion und PreZero. Gleichzeitig agieren wir als unabh&auml;ngiger Anbieter am externen Markt, um Unternehmen in ganz Europa bei ihrer digitalen Transformation zu unterst&uuml;tzen. Unsere Kernleistungen b&uuml;ndeln wir in den Bereichen Cloud, Cyber Security, Data &amp; AI, Communication und Workspace. Trage auch du zur digitalen Entscheidungsfreiheit in Europa bei.<br>
<br>
Bei uns arbeitest du an der Schnittstelle zwischen Agilit&auml;t und Sicherheit: Du profitierst von den schnellen Entscheidungswegen, genie&szlig;t echte Gestaltungsspielr&auml;ume in deinen Projekten und baust dabei auf das stabile Fundament der Schwarz Gruppe.</p></div></div></div>
<div><div><h3 class="jobSectionHeader"><b>
Deine Aufgaben</b></h3><div><div><ul><li>
Du entwickelst robuste Daten-Pipelines (Python + SQL) f&uuml;r den Betrieb eines Data Warehouse und tr&auml;gst ma&szlig;geblich zur Definition und dem Aufbau eines passenden Datenmodells bei.</li><li>
Du verantwortest den Betrieb unserer Datenplattform, die vielf&auml;ltigen Nutzerkreisen das Treffen von Entscheidungen erm&ouml;glicht.</li><li>
Du &uuml;bernimmst die technische Leitung eines agilen Engineering Teams, das den gesamten Software-Entwicklungs-Lifecycle abdeckt: von Anforderungen, Architektur und Design &uuml;ber Implementierung und Testing bis hin zu Deployment, Operations und Support.</li><li>
Du verantwortest die Architektur, achtest auf Produktqualit&auml;t und identifizierst und reduzierst aktiv technische Schulden.</li><li>
Du hast Kosten, Zeit und Budget der Entwicklung im Blick und triffst datengetriebene und ganzheitliche Entscheidungen.</li><li>
Du leitest ein Core Engineering Team durch den Entwicklungsprozess, etablierst Standards und sorgst f&uuml;r kontinuierliche Prozessverbesserungen.</li><li>
Du bist der erste Ansprechpartner und Sparringspartner f&uuml;r den Product Owner, begleitest die Anforderungsanalyse und tauschst dich mit Key-Usern aus.</li><li>
Du &uuml;bernimmst Verantwortung f&uuml;r die pers&ouml;nliche und fachliche Weiterentwicklung der Software Engineers in deinem Team.</li></ul></div></div></div><div><h3 class="jobSectionHeader"><b>
Dein Profil</b></h3><div><div><ul><li><b>
Erfahrung</b>: Du hast <b>mindestens 4 Jahre professionelle Erfahrung im Data Engineering oder der Softwareentwicklung</b> (au&szlig;erhalb deines Studiums) und bist bereit f&uuml;r eine technische F&uuml;hrungsrolle (oder bringst bereits erste Erfahrungen mit).</li><li><b>
Tech Stack</b>: Du besitzt tiefgreifende, praxiserprobte Kenntnisse im Aufbau und der Verwaltung eines Data Warehouse und der Softwareentwicklung im Backend (Python, o.&auml;.) wie auch im Frontend (Vue, React o. &auml;.).</li><li><b>
Cloud &amp; Architektur</b>: Cloud-native Technologien (Docker, Kubernetes), analytische Datenbanken (BigQuery, Snowflake) und Data Warehousing sind dein t&auml;gliches Handwerkszeug. Du hast ein starkes architektonisches Verst&auml;ndnis (inkl. Design Patterns wie Strategy Pattern, Clean Code, modulare Architekturen).</li><li><b>
Qualit&auml;t &amp; Operations</b>: Automatisiertes Testing, CI/CD, IT-Sicherheit und Best Practices im Deployment sind f&uuml;r dich nicht verhandelbar. Erfahrung mit hoch skalierbaren, Daten-intensiven Systemen ist ein gro&szlig;es Plus.</li><li><b>
Agiles Mindset &amp; Leadership</b>: Du hast eine hohe Eigeninitiative, arbeitest stark datengetrieben und hast Freude daran, Wissen zu teilen und dein Team auf das n&auml;chste Level zu heben.</li><li><b>
Sprachen</b>: Sehr gute Englischkenntnisse; Deutschkenntnisse sind ein Plus (oder die Bereitschaft, diese auszubauen).</li><li><b>
Ausbildung</b>: Abgeschlossenes IT-Studium oder eine vergleichbare Ausbildung mit fundierter Praxiserfahrung.</li></ul></div></div></div></div>
<div><h2 class="jobSectionHeader"><b>Unsere Benefits</b></h2><p></p><div><div><div><p>
</p></div></div></div></div><p></p><div><h2 class="jobSectionHeader"><b>Dein Ansprechpartner</b></h2><div><div><h3 class="jobSectionHeader"><b>
Lara Schlimgen</b></h3><p>
Recruiterin</p><ul><li>
E-Mail:recruiting@mail.schwarz</li></ul></div></div></div>
<div><h2 class="jobSectionHeader"><b>Dein Bewerbungsprozess im &Uuml;berblick</b></h2><div><div><div><div>
1</div><h3 class="jobSectionHeader"><b>
Bewerbung</b></h3></div><div>
Wir lieben die Einfachheit. Bewirb dich schnell und unkompliziert digital, gerne auch ohne Registrierung.</div></div><div><div><div>
2</div><h3 class="jobSectionHeader"><b>
Checkup</b></h3></div><div>
Gemeinsam mit dem zust&auml;ndigen Fachbereich werfen wir einen Blick in deine Unterlagen.</div></div><div><div><div>
3</div><h3 class="jobSectionHeader"><b>
Kennenlernen</b></h3></div><div>
Bei einem ersten Kennenlernen liegt der Fokus sowohl auf deiner Pers&ouml;nlichkeit als auch auf deiner fachlichen Eignung.</div></div><div><div><div>
4</div><h3 class="jobSectionHeader"><b>
Vertragsangebot</b></h3></div><div>
Haben wir uns gegenseitig &uuml;berzeugt? Dann ist dein Arbeitsvertrag digital per Mail auf dem Weg zu dir.</div></div><div><div><div>
5</div><h3 class="jobSectionHeader"><b>
Willkommen</b></h3></div><div>
Dein erster Arbeitstag bei uns steht an und dein individuelles Onboarding im Team startet. Wir freuen uns auf dich!</div></div></div></div>
<div><div><div><h2 class="jobSectionHeader"><b>Diese Stellen k&ouml;nnten auch interessant sein</b></h2></div><p></p><div><p>
</p><div><div><div><p>BerufserfahreneBad Friedrichshall
</p><h3 class="jobSectionHeader"><b>Initiativbewerbung IT Entwicklung</b><b>(m/w/d)</b></h3></div></div></div><div><div><div><p>
BerufserfahreneBad Friedrichshall
</p><h3 class="jobSectionHeader"><b>SAP ABAP Developer - EWM (m/w/d)</b><b>(m/w/d)</b></h3></div></div></div><div><div><div><p>
BerufserfahreneBad Friedrichshall
</p><h3 class="jobSectionHeader"><b>SAP ABAP Developer (m/w/d)</b><b>(m/w/d)</b></h3></div></div></div><div><div><div><p>
BerufserfahreneBad Friedrichshall
</p><h3 class="jobSectionHeader"><b>Solution Architect ServiceNow (Risk Assessment) (m/w/d)</b><b>(m/w/d)</b></h3></div></div></div><div><div><div><p>
BerufserfahreneBad Friedrichshall
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BerufserfahreneBad Friedrichshall
</p><h3 class="jobSectionHeader"><b>(Senior) AI-Assisted Software Engineer (m/w/d) - Fokus Backend (Go / Kotlin)</b><b>(m/w/d)</b></h3></div></div></div><div><div><div><p>
BerufserfahreneBad Friedrichshall
</p><h3 class="jobSectionHeader"><b>SAP ALM Spezialist (m/w/d) - Schwerpunkt Focused Run und Cloud ALM</b><b>(m/w/d)</b></h3></div></div></div><div><div><div><p>
BerufserfahreneBad Friedrichshall
</p><h3 class="jobSectionHeader"><b>Fullstack Engineer Health &amp; Performance (m/w/d)</b><b>(m/w/d)</b></h3></div></div></div><div><div><div><p>
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</p><h3 class="jobSectionHeader"><b>SAP ABAP Developer - Gro&szlig;- und Au&szlig;enhandel (m/w/d)</b><b>(m/w/d)</b></h3></div></div></div><div><div><div><p>
BerufserfahreneBad Friedrichshall
</p><h3 class="jobSectionHeader"><b>Software Engineer - Fullstack (m/w/d)</b><b>(m/w/d)</b></h3></div></div></div></div></div></div></div><p></p>

Engineering Lead - Supply Chain Data Platform (m/w/d)

<div><div><p>At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don&rsquo;t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset &mdash; who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.</p><p>
Imagine you are part of a team of talented software engineers to shape the future of Snowflake&rsquo;s AI Data Cloud. We&rsquo;re looking for talented and driven software engineers that are passionate about pushing the boundaries of speed and scale. We keep a high bar in engineering as we want to release new versions of Snowflake at fast cadence to all our customers across the globe.</p><p>
If this resonates with you, read on and apply!</p><p>
Our mission is to provide low-latency and highly consistent access to Snowflake&rsquo;s metadata in a secure way. We keep data safe through geo replication and offer immutable snapshots over long periods of time. Most prominently, we build high-scale APIs that power different types of workload from analytics warehouse and Unistore up to AI and container functions. Almost any internal service interfaces with Metadata APIs. Therefore, our services run at a large scale, supporting trillions of requests per day. Additionally, we own the representation of Metadata to users through the means of Infoschema, SHOW commands and Snowflake APIs.</p><p>
Link to article about Metadata team</p><div><p><b>
AS A SOFTWARE ENGINEER - METADATA, YOU WILL:</b></p></div><ul><li><p>
Solve real business needs at large scale by applying your software engineering and analytical problem solving skills.</p></li><li><p>
Design, develop, and support a highly-parallel and fault-tolerant database system including a decentralized caching system of terabytes of metadata.</p></li><li><p>
Design and implement core infrastructure features including APIs, DDL transactions and logs as well as advanced features built on top of the metadata, such as cloning, time travel and snapshots.</p></li><li><p>
Analyze and understand performance and scalability bottlenecks in the system and solve them.</p></li><li><p>
Ensure operational readiness of the services and meet the commitments to our customers regarding availability and performance.</p></li></ul><p>
We are looking for strong system engineers who are interested in solving some of the most challenging problems in distributed systems, performance and scalability, and passionate about building system software with high quality.</p><div></div><div><p><b>
OUR IDEAL SOFTWARE ENGINEER WILL HAVE:</b></p></div><ul><li><p>
2+ years industry experience designing, building and supporting large scale systems in production.</p></li><li><p>
Strong computer science fundamentals including data structures, algorithms, and distributed systems.</p></li><li><p>
Systems programming skills including concurrency, consistency, caching, etc. Fluency in Java (or other similar procedural object-oriented language) is preferred.</p></li><li><p>
Broad experience with identifying and implementing creative solutions to real customer problems.</p></li><li><p>
Knowledge of database internals is a big plus.</p></li><li><p>
BS in Computer Science; Masters or PhD Preferred.</p></li></ul><p>
Snowflake is growing fast, and we&rsquo;re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.</p><p>
How do you want to make your impact?</p><p>
Snowflake is growing fast, and we&rsquo;re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.</p><p>
How do you want to make your impact?</p><p>
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com</p></div></div>

Software Engineer Metadata

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Software Engineer Metadata