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Senior AI Engineering

Role overview

Qualifications

  • Practical Python skills with APIs, JSON, and Git
  • Good understanding of large language models
  • Curiosity in how AI applications are built
  • Good English communication skills

Responsibilities

  • Help develop Python applications that connect large language models to data, APIs, and tools
  • Build and improve retrieval-augmented generation (RAG) workflows
  • Support document intelligence pipelines that extract structured information
  • Implement and test agent workflows, including tool use and human approval steps

Key facts

Hard skills

Other skills

  • Communication
  • Detail Oriented

About the company

datavent.io logo

datavent.io

  • Data Analytics & Business Intelligence
  • TPE
  • 2–10
We start with one use case, fixed in scope, and take it live in 6–8 weeks through our Production Sprint. From there we extend it into a production data and AI platform and keep that platform running. What we do: • Production Sprint: one AI use case in production in 6–8 weeks • Data & AI Platform Build: lakehouse and warehouse modernisation, ETL/ELT and migration from legacy systems • Production AI Systems: RAG, document intelligence and AI agents on governed enterprise data • On-prem RAG & AI Agents: open-source LLMs on servers in your own environment • Managed Data & AI Platform: ongoing operation with engineer-reviewed changes • Intelligent DataOps: a self-healing pipeline agent that diagnoses failures and proposes each fix as a pull request for an engineer to approve Selected results: • Pipeline issue resolution cut from 6–8 hours to 30 minutes • New-customer onboarding on a multi-tenant analytics platform cut from four weeks to five minutes • 70% less manual documentation work with document intelligence on an on-prem GPU server Everything we build runs in your cloud account or data centre, on your stack, with no proprietary lock-in. Your team can own and operate it. AgentixLake is an AWS Partner and an Anthropic Certified Solutions Partner, serving clients in the DACH and Gulf regions.

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Job description

AgentixLake GmbH · Hamburg, Germany
Remote within UAE
https://www.linkedin.com/company/agentixlake/

Help turn AI ideas into systems people can rely on.

An AI application needs more than a convincing first answer. It needs relevant data, useful tools, measurable quality, and reliable software behind it.

At AgentixLake, you’ll help build that software. We’re looking for a Working Student in AI Engineering who enjoys Python and wants to develop practical applications using large language models.

About AgentixLake

AgentixLake is a Hamburg-based data and AI engineering company. We build production-grade data platforms and AI systems on our customers’ cloud and on-premises infrastructure.

Our projects include AI agents that investigate data pipeline failures, assistants that answer questions using governed business data, and document intelligence systems that extract structured information from complex manuals.

We are an AWS and Anthropic Certified Services Partner.

What you’ll work on

Working alongside experienced engineers, you will:

  • Help develop Python applications that connect large language models to data, APIs, and tools.

  • Build and improve retrieval-augmented generation (RAG) workflows, including document processing, chunking, embeddings, and retrieval.

  • Support document intelligence pipelines that extract structured, source-linked information from complex documents.

  • Implement and test agent workflows, including tool use and human approval steps.

  • Create evaluation datasets and compare answer quality, retrieval performance, latency, and cost.

  • Add tests, logging, and documentation to make AI applications easier to operate and improve.

What you bring

  • Practical Python skills with APIs, JSON, and Git.

  • Good understanding of large language models and curiosity in how AI applications are built.

  • A careful approach to testing: you understand when a system works, when it fails, and why.

  • Good English communication skills.

Show us what you got: a university or personal project involving LLMs, RAG, embeddings, or AI agents; experience with Amazon Bedrock, Claude, vector databases, FastAPI, Docker, or an AI application framework.

What you can expect

  • Exposure to the full application lifecycle, from experimentation and evaluation to deployment and monitoring.

  • A small team where your questions, ideas, and contributions matter.

Follow our journey

Follow AgentixLake on LinkedIn https://www.linkedin.com/company/agentixlake/ for updates, engineering insights, and future opportunities.

Apply

We welcome applicants of all backgrounds. You do not need to meet every listed requirement to apply.

Learn more at https://agentixlake.com/

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