Das ist der Job
Our mission is to provide transparency on business conduct risks to drive positive change.
Darum lohnt es sich
With our values of intellectual honesty and humility, operational excellence, and openness and respect, our diverse teams of talented experts are pioneering solutions that enable clients to make better informed decisions. You’ll join a collaborative team that values openness, respect, and work–life balance.
What you can expect Flexible working hours and a hybrid model (with home office days). RepRisk is the world’s most respected Data as a Service (DaaS) company for reputational risks and responsible business conduct.
Combining advanced AI with deep human expertise, and a proven methodology at the core, RepRisk’s solutions bring performance and peace of mind, enabling clients to know more, be sure, and act faster.
Headquartered in Zurich, and with offices in Toronto, New York, London, Berlin, Manila, and Tokyo, we stay close to clients and bring an independent lens to the industry.
United by our shared belief in the power of data, our 400 people are proud to be setting the global standard for business conduct data and driving positive and meaningful change through transparency. We offer a diverse, multicultural, and mission‑driven workplace where your impact truly matters.
Up to 4 weeks per year working abroad, subject to policy and approvals. Paid training and volunteering days, plus charity donation matching. Health supporting discovery, proposing improvements, and showing initiative beyond the assigned scope.
Qualifications Experience: 5+ years of hands‑on software engineering experience, with 2‑3 years building AI agents in production environments, ideally for high‑stakes or regulated industries (finance, legal, healthcare, etc.).
Education: A Master’s degree or higher in Computer Science, Engineering, Statistics, or a related STEM field (or equivalent practical experience). Agentic frameworks: Strong hands‑on experience building agents with LangChain and LangGraph (or equivalent orchestration frameworks) — including planning, memory, tool‑use, and multi‑agent patterns.
MCP expertise: Proven experience building and operating MCP (Model Context Protocol) servers using FastMCP, or on platform providers such as Databricks or Snowflake, with secure schemas, authentication, and role‑based permissions. Python ability to translate them into maintainable production code. Ownership
