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Avenga
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FrontendSenior

Senior AI Engineer

PythonLLMRAGknowledge graphsVector DatabaseMCPLangGraphLangChainSemantic KernelNeo4jJiraConfluenceMicrosoft TeamsSharePoint
Work Type
-
Job Type
-
Location
Worldwide
Salary
Not specified

About the Position

Avenga is an international engineering firm helping businesses operate with AI at the core. 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.

Responsibilities

  • Design and implement AI-powered capabilities, develop agentic workflows, work with LLMs and knowledge systems, and turn complex enterprise processes into intelligent, automated experiences.
  • 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.

Requirements

  • 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
  • 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 graph databases such as Neo4j
  • Experience with LLM evaluation, observability, and AI reliability
  • Experience building enterprise SaaS or workflow automation platforms

Who to contact

Senior AI Engineer
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