AI Engineer Python

Syngenta

Madrid

Presencial

EUR 85.000 - 120.000

Jornada completa

hace 36 horas
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Descripción de la vacante

Syngenta is seeking an AI Engineer — Python to enhance the Python layer of our internal developer platform: templates, shared libraries, runtime standards and quality tooling. This is an opportunity to work at the intersection of advanced technology and agricultural R&D, partnering with engineers, product leaders and scientific stakeholders on capabilities with real-world impact.

Help accelerate the digital capabilities that support more sustainable agriculture and scientific innovation.

Formación

  • Experience with modern Python packaging, types and asynchronous code.
  • Experience with shared libraries and service templates.
  • Experience in AI-assisted engineering with rigorous evaluation.
  • Experience in CI/CD, Docker, Kubernetes and Terraform.
  • Experience in test and quality engineering.
  • Experience in documentation-as-code and agent-consumable interfaces.
  • Experience with internal platform thinking and influencing stakeholders.
  • Strong communication skills and fluency in English.
  • Proven experience in performance optimization, profiling and benchmarking of Python apps.
  • Knowledge of security best practices and secure coding standards.
  • Experience implementing monitoring, observability and alerting solutions.

Responsabilidades

  • Lead and apply deep expertise in Modern Python to deliver durable, scalable outcomes.
  • Lead and apply deep expertise in Shared libraries and service templates.
  • Lead and apply deep expertise in AI-assisted engineering with rigorous evaluation.
  • Lead and apply deep expertise in CI/CD, Docker, Kubernetes and Terraform.
  • Lead and apply deep expertise in Test and quality engineering.
  • Lead and apply deep expertise in Documentation-as-code and agent-consumable interfaces.
  • Mentor junior engineers and conduct thorough code reviews.
  • Optimize performance and scalability of Python applications through profiling and architectural improvements.
  • Implement and enforce security best practices, including vulnerability assessments.
  • Establish monitoring, observability and alerting standards for platform reliability.
  • Evaluate and integrate emerging AI/ML tools to enhance productivity.
  • Collaborate across engineering, product and scientific teams to translate needs into solutions.
  • Set a high bar for quality and responsible use of AI-assisted engineering.

Conocimientos

Modern Python
Shared libraries
AI-assisted engineering
CI/CD
Docker
Kubernetes
Terraform
Test & quality engineering
Documentation-as-code
Security best practices
Observability & monitoring
Strong communication
English fluency

Herramientas

Docker
Kubernetes
Terraform

Descripción del empleo

Company Description

Syngenta Crop Protection is a leader in agricultural innovation, bringing breakthrough technologies and solutions that enable farmers to grow productively and sustainably. We offer a leading portfolio of crop protection solutions for plant and soil health, as well as digital solutions that transform the decision-making capabilities of farmers. Our 17,900 employees serve to advance agriculture in more than 90 countries around the world. Syngenta Crop Protection is headquartered in Basel, Switzerland, and is part of the Syngenta Group.

Company Description

Syngenta Crop Protection is a leader in agricultural innovation, bringing breakthrough technologies and solutions that enable farmers to grow productively and sustainably. We offer a leading portfolio of crop protection solutions for plant and soil health, as well as digital solutions that transform the decision-making capabilities of farmers. Our 17,900 employees serve to advance agriculture in more than 90 countries around the world. Syngenta Crop Protection is headquartered in Basel, Switzerland, and is part of the Syngenta Group.

Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us and help shape the future of agriculture.

Job Description

We are looking for an AI Engineer — Python to enhance the Python layer of our internal developer platform: templates, shared libraries, runtime standards and quality tooling. This is an opportunity to work at the intersection of advanced technology and agricultural R&D, partnering with engineers, product leaders and scientific stakeholders on capabilities with real-world impact. Help accelerate the digital capabilities that support more sustainable agriculture and scientific innovation.

What You’ll Do
  • Lead and apply deep expertise in Modern Python: packaging, types and async to deliver durable, scalable outcomes.
  • Lead and apply deep expertise in Shared libraries and service templates to deliver durable, scalable outcomes.
  • Lead and apply deep expertise in AI-assisted engineering with rigorous evaluation to deliver durable, scalable outcomes.
  • Lead and apply deep expertise in CI/CD, Docker, Kubernetes and Terraform to deliver durable, scalable outcomes.
  • Lead and apply deep expertise in Test and quality engineering to deliver durable, scalable outcomes.
  • Lead and apply deep expertise in Documentation-as-code and agent-consumable interfaces to deliver durable, scalable outcomes.
  • Mentor junior engineers and conduct thorough code reviews to maintain high engineering standards across the platform.
  • Optimize performance and scalability of Python applications through profiling, benchmarking and architectural improvements.
  • Implement and enforce security best practices, including vulnerability assessments and secure coding standards.
  • Establish monitoring, observability and alerting standards to ensure platform reliability and performance visibility.
  • Evaluate and integrate emerging AI/ML tools and frameworks to enhance developer productivity and platform capabilities.
  • Collaborate across engineering, product and scientific teams to translate complex needs into practical solutions.
  • Set a high bar for quality, documentation and thoughtful use of AI-assisted engineering throughout the organization.
Qualifications

**What You Bring**

Required Qualifications
  • Demonstrable experience in Modern Python: packaging, types and async
  • Demonstrable experience in Shared libraries and service templates
  • Demonstrable experience in AI-assisted engineering with rigorous evaluation
  • Demonstrable experience in CI/CD, Docker, Kubernetes and Terraform
  • Demonstrable experience in Test and quality engineering
  • Demonstrable experience in Documentation-as-code and agent-consumable interfaces
  • Demonstrable experience in Internal platform thinking
  • Strong communication skills and the ability to influence across technical and non-technical stakeholders
  • Fluent English, written and spoken
  • Proven experience with performance optimization, profiling and benchmarking of Python applications
  • Knowledge of security best practices, including vulnerability assessments and secure coding standards
  • Experience implementing and maintaining monitoring, observability and alerting solutions
Preferred Qualifications
  • Experience in agriculture, life sciences, scientific computing or a regulated enterprise environment
  • Experience building platforms, products or services used by multiple internal teams
  • Experience working in distributed, international engineering organizations
  • Demonstrated experience mentoring junior engineers or leading technical initiatives
  • Familiarity with emerging AI/ML tools and frameworks in development environments
Additional Information

Why Syngenta?

  • Meaningful impact: help build technology that supports scientific innovation and sustainable agriculture.
  • Complex, modern challenges: work on high-scale platforms and systems with room for technical judgement.
  • Collaborative environment: partner with global engineering, R&D and product communities.
  • Growth: broaden your influence through challenging work, visible outcomes and a global network
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