Senior AI Engineer – Generative AI & Agentic Systems
Agentix Lake GmbH is a Data and AI engineering consultancy based in Hamburg, Germany. We design, build and operate production-grade data platforms and AI systems in our customers’ cloud accounts or on-premises environments. We are an AWS Services Partner and a Certified Services Partner in Anthropic's Claude Partner Network. Our commercial focus is DACH and the Gulf region, alongside selected international opportunities.
Your roleTake enterprise AI applications from technical design into dependable production use. You will own the software, evaluations and operational controls behind generative AI systems that work with customer data, tools and business processes.
Our applied AI engineering services include AI-native applications, enterprise RAG, AI agents, document intelligence and private AI deployment. Examples include investigating data pipeline failures, answering questions using governed business metrics and extracting source-linked information from complex documents.
What you will doDesign and implement Python services connecting large language models to enterprise APIs, data sources and approved tools.
Build retrieval-augmented generation systems, including document ingestion, indexing, retrieval, reranking and source attribution.
Engineer agentic workflows with explicit permissions, reliable state handling, retries, audit trails and approval gates for consequential actions.
Develop document intelligence pipelines that produce validated structured outputs for downstream applications and ERP workflows.
Create evaluation datasets and release criteria; measure answer quality, failure modes, latency and operating cost.
Deploy and operate AI applications in customer-controlled cloud or private environments, with monitoring, incident handling and clear handover documentation.
What you bringA record of delivering production software and LLM applications, with responsibility for architecture, deployment and operational quality.
Strong Python, API design, testing and debugging, plus practical experience with containers, Git and CI/CD.
Hands-on experience with RAG, tool use, structured outputs and evaluation beyond prompt experimentation.
Experience with Amazon Bedrock, Anthropic Claude or comparable model services, and the judgement to select models and deployment patterns for a use case.
The ability to assess data access, untrusted inputs and agent permissions, explain trade-offs to customers and guide engineering decisions in English.
Experience with self-hosted models, GPU infrastructure, vector search, MCP integrations or agent frameworks is valuable. We welcome engineers who can explain when a simpler workflow is the better design.
What you can expectYou will work closely with the founders, own meaningful technical decisions and shape how our team builds, evaluates and operates enterprise AI. The work includes both implementation and collaboration with customer engineering teams.
We welcome applicants of all backgrounds. If the core responsibilities match your experience, we would like to hear from you.
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