AI Engineer (Agentic AI & Automation)
Based in SwitzerlandFull-Time
Salary not disclosed
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Job Details
- Languages
- English
- Required Skills
- PythonJavaGoSoftware Engineering
Requirements
- Strong software engineering background with professional experience in Python, Go, Java, or comparable programming languages.
- Extensive hands-on experience designing and deploying agentic AI systems using frameworks such as LangGraph, CrewAI, AutoGen, or similar technologies.
- Deep understanding of modern AI reasoning techniques, including ReAct, Plan-and-Solve methodologies, multi-agent collaboration, and autonomous workflow orchestration.
- Proven expertise building AI-powered developer tools, repository-aware automation, advanced prompting strategies, and coding assistants.
- Experience developing reliable AI systems with strong attention to execution quality, safety, scalability, and enterprise-grade performance.
- Passion for identifying manual processes and transforming them into intelligent, autonomous solutions.
- Strong analytical thinking, problem-solving skills, and the ability to rapidly prototype innovative automation concepts.
- Excellent verbal and written English communication skills with the ability to collaborate effectively across technical teams.
Responsibilities
- Design, develop, and maintain autonomous multi-agent AI systems capable of planning, reasoning, and executing complex engineering workflows.
- Build AI-powered development tools that automate code generation, refactoring, code reviews, and other software engineering tasks across the development lifecycle.
- Create intelligent testing solutions that automatically generate, execute, and improve integration and end-to-end tests based on application changes.
- Develop agentic workflows for production monitoring, automated incident detection, root-cause analysis, and remediation recommendations.
- Integrate AI agents securely with APIs, databases, repositories, and enterprise tools through scalable function-calling architectures.
- Implement reliable agent memory, state management, and execution frameworks that support long-running autonomous processes.
- Establish robust safety mechanisms, execution guardrails, and governance controls to ensure secure and predictable AI behavior.
- Identify repetitive engineering activities and rapidly prototype automation solutions that improve developer productivity and operational efficiency.
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