
AI Engineer Python
Syngenta Group24 days ago
Madrid, SpainSenior
Responsibilities
- Lead development of the platform’s modern Python layer, including packaging, types, async programming, shared libraries, and service templates.
- Develop AI-assisted engineering practices with rigorous evaluation and integrate emerging AI/ML tools and frameworks for developer productivity.
- Establish platform standards using Docker, Kubernetes, Terraform, quality engineering, documentation-as-code, and agent-consumable interfaces.
- Optimize Python application performance through profiling, benchmarking, and architectural improvements.
- Implement security practices, vulnerability assessments, secure coding standards, monitoring, observability, and alerting.
- Mentor junior engineers, conduct code reviews, collaborate across engineering, product, and scientific teams, and lead technical initiatives.
Requirements
- Demonstrable experience with modern Python, shared libraries, service templates, AI-assisted engineering, quality engineering, documentation-as-code, and internal platform development.
- Demonstrable experience with Docker, Kubernetes, and Terraform.
- Proven experience with Python performance optimization, profiling, and benchmarking.
- Knowledge of security best practices, vulnerability assessments, and secure coding standards.
- Experience implementing and maintaining monitoring, observability, and alerting solutions.
- Strong communication skills, ability to influence technical and non-technical stakeholders, and fluent written and spoken English.
- Preferred: experience in agriculture, life sciences, scientific computing, regulated enterprise environments, multi-team platforms, distributed international organizations, mentoring, or leading technical initiatives.
- Preferred: familiarity with emerging AI/ML tools and frameworks in development environments.
Benefits
- Meaningful work supporting scientific innovation and sustainable agriculture.
- Complex, modern, high-scale platform and systems challenges with technical decision-making autonomy.
- Collaboration with global engineering, R&D, and product communities.
- Opportunities to broaden influence through challenging work, visible outcomes, and a global network.