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Senior Software Engineer – AI Platform (m/f/d)

NEXOWARE GmbH
Contract type
Ongoing
Work mode
Hybrid · Germany
Experience
Senior · Not stated

Level inferred from job title

Job description

Build the core of an AI agent platform as a backend engineer in the AI-Platform team, enabling IT service providers to automate their business with intelligent agents.

At a glance

Work mode
Hybrid · Germany
Languages
German

What you'll do

  • Develop and operate the backend services of the AI agent platform as a standalone service
  • Build LLM-based agent pipelines, agentic workflows and the execution engine with focus on reliability and observability
  • Develop APIs, WebSockets and event-driven architectures that route events to the right agents
  • Build management UIs to configure, monitor and test agents
  • Shape architecture decisions and code quality (performance, scalability, system design)
  • Implement scalable solutions with Product Management and Engineering in an agile team

What we're looking for

  • Degree in computer science (Bachelor or Master) or comparable experience
  • Several years of experience in software development on complex product systems
  • Experience with agentic programming and agent-based systems
  • Spring Boot / Java, ideally with Spring Security, AMQP and WebSocket
  • SQL databases, ideally PostgreSQL
  • Python as well as AI and web libraries
  • Hands-on experience with LLM APIs and agent patterns
  • Angular / TypeScript and Docker

Nice to have

  • Pgvector and embedding search
  • Agent frameworks such as LangGraph, Claude Agent SDK or AutoGen
  • LLM observability such as Langfuse or LangSmith
  • Webhook infrastructure and API gateway patterns
  • Event queues such as RabbitMQ, Kafka or comparable

Your team

AI-Platform

A new, standalone platform team within NEXOWARE.

Benefits

  • Reporting line to CTO / Head of Engineering
  • Hybrid working with regular presence at NEXOWARE locations
  • Performance-oriented compensation model

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About NEXOWARE GmbH

What they value

  • Take responsibility for your systems and focus on quality and impact
  • Cope with ambiguity while still bringing pace
  • Prototype quickly and learn from production operation
  • Communicate clearly across disciplines
  • Be curious about AI and help shape how it is used in enterprise software