Staff Architect / Tech Lead
New
Switzerland, Europe-based time zonesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years of software engineering experience, including at least 2+ years in Staff Engineer, Principal Engineer, Tech Lead, or Architect roles
- Required Skills
- AWSDockerPythonETLGCPAzureFastAPIDatabricks
Requirements
- 8+ years of software engineering experience, including at least 2+ years in Staff Engineer, Principal Engineer, Tech Lead, or Architect roles
- Strong proficiency in Python, ideally with frameworks such as FastAPI or similar backend technologies
- Proven experience designing and scaling distributed systems, backend architectures, and data-intensive platforms
- Strong background in data engineering, including ETL pipelines, data processing workflows, and large-scale data systems
- Hands-on experience with Databricks and modern data engineering ecosystems
- Experience working with cloud platforms such as AWS, Azure, or GCP in production environments
- Familiarity with containerization technologies such as Docker and modern deployment practices
- Understanding of AI/LLM-based systems, agent architectures, or intelligent automation solutions
- Strong communication skills with the ability to engage effectively with both technical and non-technical stakeholders
- Ability to operate in ambiguous environments and translate high-level requirements into structured technical designs
Responsibilities
- Define and own the end-to-end architecture for a new AI and data intelligence platform, ensuring scalability, maintainability, and performance
- Design and implement backend services, data pipelines, and integration patterns across cloud-native environments
- Provide technical leadership and hands-on guidance to engineers, ensuring high-quality execution and alignment with architectural vision
- Review code, design proposals, and engineering outputs to maintain strong technical standards across the team
- Collaborate with product stakeholders to translate business requirements into robust, scalable technical solutions
- Build and evolve data platform components including ETL pipelines, data models, and AI-enabled workflows
- Contribute directly to the development of complex features, especially around AI agents and system integration
- Drive engineering best practices including testing, documentation, observability, and system reliability
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