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Tech Lead AI-assisted Search; m​/w​/d

in 73614, Schorndorf, Baden-Württemberg, Deutschland
Unternehmen: Würth IT GmbH
Vollzeit position
Verfasst am 2026-10-16
Berufliche Spezialisierung:
  • Software Entwicklung
    Künstliche Intelligenz Ingenieur, Maschinelles Lernen
Gehalts-/Lohnspanne oder Branchenbenchmark: 90000 - 130000 EUR pro Jahr EUR 90000.00 130000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: Tech Lead AI-assisted Search (m/w/d)
Location: Schorndorf

Let’s do IT! Let’s do IT! Are you usually the person who finds a solution to every problem? Or do solutions seem to find you? However you look at it, you enjoy tackling technical challenges, are interested in the details and come up with creative ideas. Then we have a truly large-scale opportunity for you. Würth is one of the world’s largest B2B distributors, with several hundred companies, a product range comprising hundreds of thousands of items, and customers ranging from construction sites to engineering departments.

The hybrid, AI-assisted search solution you will help shape must understand the specialist language of a screw-fixing professional on a construction site in Warsaw just as well as the engineering terminology used in the Würth catalogue - across languages, levels of language proficiency and countries.

Specifically, You Will
  • take responsibility as Tech Lead Search for the technical quality and architecture of our product retrieval and embedding capabilities based on Open Search.
  • review and guide how our developers work on search components in Python and Java, establish pragmatic standards and help determine the appropriate level of solution depth for each use case.
  • drive the rollout of our search solutions in a multilingual, multichannel and multi-application environment - from a strong technical prototype to a search solution used in production across different shops, languages and sales channels worldwide. You will maintain a clear view of when a result is ready to move to the next stage.
  • develop a clear Infrastructure-as-Code strategy for our search applications based on AWS and Cloud Formation. This strategy should integrate seamlessly with the environment provided by the Platform Team. You will also work hands‑on on key retrieval and encoding components and take them into production.
  • build an understanding of operating production ML pipelines for our custom models, such as learning‑to‑rank and search understanding, and identify synergies between search and these related areas as they become increasingly important.

Bring IT on! Do your fingers fly across the keyboard when you code? Excellent. We provide reliable equipment and the opportunity for you to contribute your expertise to the team.

You
  • have completed a degree in computer science, business informatics or a comparable qualification combined with relevant professional experience.
  • have already assumed technical responsibility for an engineering team as a Tech Lead - from providing technical guidance and conducting reviews to deciding when a result is ready to move to the next stage.
  • have practical, in-depth experience with retrieval and search infrastructure, ideally Open Search or Elasticsearch, vector search, and indexing and encoding pipelines. You can independently assess technical decisions in this field - this is your core area of expertise.
  • have experience leading technical teams from strong prototypes to search solutions used in production, ideally in an international, multilingual environment with multiple channels and applications. You know how to define scope intelligently and recognise the right time to move to the next stage.
  • have a deep understanding of backend architectures and distributed systems, as well as practical development experience with Python and/or Java.
  • have strong knowledge of AWS and sufficient expertise in Infrastructure as Code, ideally Cloud Formation, to design and share responsibility for a robust IaC strategy for your applications.
  • ideally have a basic understanding of production ML pipelines for custom models, including training, deployment and monitoring - for example, with Databricks. This is a plus, not a requirement, as search remains your primary area of responsibility.
  • communicate…
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