Role
You will own and evolve the agentic layer that powers our products. That means designing and building the multi-agent orchestration systems, RAG pipelines, tool-use architectures, and workflow engines that sit at the core of what we build.
This is a senior engineering role with real production stakes. You will make foundational architecture decisions, shape engineering standards, and work directly with product and leadership from day one. It is not a research role. It is a building role.
Key Responsibilities:
Design and implement multi-agent architectures using Agno, LangChain, and LangGraphBuild and maintain scalable backend services and APIs in Python and FastAPIOwn agent orchestration logic: task routing, tool use, state management, and human-in-the-loop integrationDesign and implement RAG pipelines over domain-specific data, with strict requirements for accuracy, traceability, and complianceMake production-grade decisions on LLM integration, prompting strategies, and reliability patternsSet engineering standards for code quality, testing, and deployment of agentic systemsDrive end-to-end feature ownership from design through to productionMentor engineers and actively shape the engineering culture as the team growsCollaborate closely with product and leadership to influence the technical roadmapRequirements
You bring technical strength, curiosity, and a drive to build meaningful AI systems. Here is what helps you succeed in this role:
A strong Python engineer who has shipped production systems, not just prototypesHands-on with agentic frameworks (LangChain, LangGraph, Agno, or similar)Fluent in LLMs in production: prompting, tool use, orchestration, failure modesExperience building production RAG systems: retrieval architectures, vector databases, embedding strategies, and evaluation frameworksExperience with agent evaluation frameworks and observability tooling ( LangSmith or similar): tracing agent behavior, debugging multi-agent interactions, and ensuring reliability in productionComfortable with cloud environments (AWS, GCP, or Azure) and distributed system designExperienced with MLOps practices: CI/CD, monitoring, deployment pipelinesAutonomous, low ego, and serious about what you buildExcited about working in a domain where the quality of your work has real-world consequencesNice to have:
Experience in life sciences, regulated industries, or GxP-compliant environmentsExperience with multi-agent systems and workflow orchestrationWe know that great candidates might not check every box. If you’re excited about this role and believe you could contribute, we’d love to hear from you.
Benefits
What we offer
A competitive compensation packageA flexible working culture because your work-life balance matters to usA position that enables you to have an impact on 1’000s of people, and the whole company's growth.An international, knowledgeable, and passionate team with a strong collaborative mindsetEmployee Stock Ownership PlanWhy Join Us
Work with autonomous agents, orchestration runtimes, and knowledge retrieval systemsBuild technology that transforms how life-science experts research, decide, and createShape architecture, culture, and direction from the very beginningCollaborate with world-class engineers and researchers who share a deep passion for AIHybrid setup with high trust, autonomy, and flexibilityCompetitive compensation and the chance to be part of a company defining a new AI category
Lausanne, Vaud, Switzerland