Staff Software Engineer - Back and Frontend

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.

**Staff Software Engineer - Back and Frontend**

**Key Responsibilities:**

• Establish and enforce the technical direction and architectural decisions for analytics, insights, prediction services, and their product integrations.

• Engage directly in the codebase to develop, review, prototype, and investigate complex technical problems with rigor and precision.

• Establish and maintain rigorous engineering quality standards, including sound design principles, comprehensive testing protocols, thorough documentation, and exacting code review practices.

• Collaborate with Product Managers, engineers, and stakeholders to define priorities, identify constraints, and identify technical risks at the earliest stages.

• Provide authoritative technical leadership across relevant teams through decisive decision-making, practical guidance, and credible hands-on technical involvement.

• Contribute to the development of cross-functional engineering standards and disseminate proven technical patterns across Staff Engineers and teams.

• Participate actively in technical discussions and governance processes, providing rigorous analysis of risks, trade-offs, and system maintainability.

• Drive resolution of critical technical challenges while maintaining alignment with broader product objectives and business context.

• Direct performance optimization initiatives, scalability improvements, and system reliability enhancements across backend and frontend services.

• Mentor and develop junior and mid-level engineers through rigorous code reviews, technical discussions, and structured knowledge-sharing sessions.

• Assess emerging technologies and frameworks relevant to analytics and AI-assisted engineering, providing evidence-based recommendations for adoption.

• Lead incident response and post-mortem processes to systematically improve system resilience and operational excellence.

• Assume full technical ownership of the Knowledge Management area, including technology selection, integration patterns, data access architecture, API design, and AI-assisted document ingestion and retrieval systems.

• Execute hands-on engineering work (50–60% of time), coding and reviewing in Python or Java, owning the most complex and highest-risk technical initiatives while rigorously evaluating AI-generated code.

• Define and enforce the engineering quality bar for the area, establishing test coverage expectations, documentation standards, agent-consumable interface compliance, and code review rigor.

• Align technical standards and best practices across engineering groups through active cross-functional engagement and pattern-sharing.

• Serve as the primary technical counterpart to Product Management, translating roadmap priorities into precise technical delivery estimates, surfacing technical risks proactively, and engaging with regulatory specialists as required.

**Required Qualifications**

• Demonstrated expertise in software engineering with proven success building and operating production systems at scale.

• Mastery of system design with the ability to evaluate technical trade-offs and assume full accountability for architectural decisions in production environments.

• Hands-on engineering capability with proficiency in coding, code review, prototyping, and technical investigation—not advisory-level engagement.

• Expert-level backend engineering skills in Python or Java, including architecture-level understanding of data access patterns, API design, document ingestion pipelines, and text embedding model integration for retrieval-oriented workloads.

• Expert-level system architecture capability with demonstrated ability to design systems, evaluate trade-offs, and make accountable architectural decisions in production environments.

• Advanced technical leadership demonstrated through credibility, clear direction, and active codebase presence without requiring formal line authority.

• Proficiency in both backend and frontend technologies, with documented depth in at least one domain. Working knowledge of React or Angular sufficient to review frontend work and make full-stack architectural decisions.

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