Staff Architect / Tech Lead | NDA

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Architect / Tech Lead | NDA based in Switzerland.

This role sits at the intersection of architecture, data engineering, and AI-enabled product development within a greenfield initiative aimed at building a next-generation AI-powered Data Intelligence Platform. You will take a leading role in defining the technical foundation of a brand-new system designed to capture, structure, and scale organizational knowledge through intelligent agents and advanced data workflows. The environment is highly collaborative and fast-moving, bringing together engineering, product, and consulting expertise to solve complex enterprise challenges. You will operate as a key technical authority, shaping architecture decisions while remaining hands-on in implementation. This position offers significant influence over system design, engineering standards, and long-term technical direction. It is well-suited for someone who thrives in ambiguity and enjoys building scalable systems from the ground up.

In this role, you will own the technical architecture and engineering direction of a new AI-driven data platform while actively contributing to implementation, system design, and technical leadership.

• 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

Requirements

This role requires deep technical expertise in backend engineering, data systems, and cloud architecture, combined with strong leadership and the ability to operate effectively in complex, evolving environments.

• 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

Benefits

• 12-month contract with potential for extension
• Fully remote work within Europe-based time zones
• Opportunity to lead the architecture of a greenfield AI-powered enterprise platform
• High-impact role with significant technical ownership and decision-making authority
• Collaboration with experienced engineering, product, and consulting teams
• Exposure to cutting-edge AI, data engineering, and agent-based system design
• Hands-on involvement in both architecture and implementation work
• Opportunity to shape long-term product direction and engineering standards