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Avenga; Köln; On-site; EUR 90,000 - 150,000; Full time

Job summary

Avenga is seeking a Senior AI Engineer in Germany to build an AI-native enterprise work platform that unifies execution, knowledge, and decision-making. You will design AI-powered capabilities, develop agentic workflows, and leverage LLMs with knowledge systems to automate enterprise processes.

You will own architectural decisions and shape foundational components of a new AI-native product, with initial focus on integrating Jira and Confluence and extending to other enterprise tools over time.

Qualifications

• Strong commercial experience with Python and backend development.
• Hands-on experience building LLM-powered applications and AI agents.
• Understanding of agentic AI, multi-agent systems and agent orchestration.
• Experience with LLM APIs, prompt engineering, context management, tool calling, and RAG.
• Knowledge graphs, vector databases, or other knowledge representations.
• Strong understanding of APIs, integrations, data processing and distributed systems.
• Experience with cloud platforms and modern software engineering practices.
• Ability to work independently and take ownership of solutions.

Responsibilities

• Design and implement AI-powered capabilities and agentic workflows.
• Work with LLMs and knowledge systems to automate complex enterprise processes.
• Define architectural directions and own technical decisions for the product.

Skills

Python

LLM apps

Agentic AI

LLM APIs

Knowledge graphs

APIs & integrations

Cloud platforms

Independent owner

Tools

Jira

Confluence

LangGraph

LangChain

Semantic Kernel

Neo4j

Job description

Avenga is an international engineering firm helping businesses operate with AI at the core. With 6,000+ experts worldwide, we combine engineering expertise with AI-native thinking to turn ambitious ideas into real-world impact across industries, technologies, and markets.

At the core of the role

We are looking for a Senior AI Engineer to help build an AI-native enterprise work operating system that changes how organizations manage execution, knowledge, and decision-making.

The platform is designed to move beyond traditional ticket- and document-centric tools by combining an enterprise registry, connected knowledge graph, and multi-agent workforce. Initially integrating with tools such as Jira and Confluence, the long-term vision is to create a new system of work where AI agents and human teams collaborate around a shared source of truth.

In this role, you will design and implement AI-powered capabilities, develop agentic workflows, work with LLMs and knowledge systems, and turn complex enterprise processes into intelligent, automated experiences. You will have significant ownership over technical decisions and the opportunity to shape the foundations of a new AI-native product.

Core skills you’ll bring

• Strong commercial experience with Python and backend development

• Hands‑on experience building LLM‑powered applications and AI agents

• Strong understanding of agentic AI, multi-agent systems, and agent orchestration

• Experience with LLM APIs, prompt engineering, context management, tool/function calling, and RAG

• Experience working with knowledge graphs, vector databases, or other knowledge representation approaches

• Strong understanding of APIs, integrations, data processing, and distributed systems

• Experience with cloud platforms and modern software engineering practices

• Ability to work independently, make architectural decisions, and take ownership of solutions

Nice-to-have

• Experience with MCP (Model Context Protocol) and AI agent tooling

• Experience integrating enterprise platforms such as Jira, Confluence, Microsoft Teams, or SharePoint

• Experience with LangGraph, LangChain, Semantic Kernel, or similar agent frameworks

• Experience with Neo4j

• Experience with LLM evaluation, observability, and AI reliability

• Experience building enterprise SaaS or workflow automation platforms

The impact you'll create

• Define and evolve the enterprise strategy for AI-native software engineering and AI-driven delivery practices.

• Establish architecture standards, engineering principles, and governance frameworks for responsible AI adoption across the SDLC.

• Drive the adoption of AI across requirements, design, development, testing, deployment, and operations.

• Define and champion AI-DLC practices, turning emerging approaches into scalable engineering standards and repeatable processes.

• Partner with engineering, architecture, security, product, and leadership teams to embed AI into everyday software delivery.

People are at the core of Avenga. We provide equal opportunities regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. We are committed to a respectful environment where everyone can be themselves, share their ideas, and feel that they belong.