Agentic AI Engineer

• At Mercanis, we are building the Agentic AI Procurement Suite that powers the procurement of tomorrow, digital, transparent, and intelligent
• We are looking for an experienced Agentic AI Engineer to join our growing AI team. In this role, you will design, build, and optimize agentic AI systems that automate complex procurement workflows and power intelligent decision-making across our platform
• You will work with cutting-edge technologies in Python, LangGraph, and AWS, integrating and fine-tuning models from leading providers such as OpenAI, Anthropic, and AWS Bedrock
• Your work will have a direct impact on how organizations streamline their procurement processes and leverage AI for strategic advantage
• Tech stack you will work with:
• Languages: Python
• Frameworks & Tools: LangGraph & related LLM orchestration tools, Docling, LiteLLM, Phoenix
• Infrastructure: AWS (Lambda, S3, ECS, and more)
• Models: OpenAI, Anthropic, AWS Bedrock, and other foundation model providers

Benefits

• One of the best learning experiences in Berlin
• A lot of space for your own ideas with a sparring approach
• Appreciation, joint growth, and lively interaction
• Regular team events - we celebrate birthdays and successes together!
• Healthy snacks and drinks
• Networking opportunities- Bonus: Knowledge of agent-to-agent (A2A) communication patterns and multi-agent system architectures
• Curiosity, adaptability, and a passion for staying ahead in the evolving world of AI
• Bonus: Strong background in measuring, evaluating, and optimizing AI system performance with clear metrics and benchmarking
• Bonus: Experience implementing observability and monitoring solutions for AI systems to track quality and iterate on improvements
• Solid understanding of Large Language Models (LLMs) and their integration with external APIs or structured data
• A collaborative mindset and comfort working remotely with distributed teams
• Proven experience building AI-driven or agentic systems, preferably with LangGraph or similar frameworks
• Familiarity with cloud-based deployment and scaling, ideally using AWS services
• Bonus: Experience with semantic search technologies (vector databases, embeddings, RAG systems)
• Strong problem-solving skills with a focus on maintainable, efficient, and scalable code
• Hands-on experience working with LLM providers such as OpenAI, Anthropic, or AWS Bedrock
• Strong professional experience in Python software development
• Bonus: Experience building or integrating MCP (Model Context Protocol) servers for extending AI capabilities