AI Engineer Python

Overview

In this senior, hands-on role you will design, build and maintain production-grade Python services and internal developer platforms to enable multiple teams. You’ll advance AI-enabled capabilities, including RAG-based search and conversational features over internal knowledge sources, while upholding security, reliability and scalable engineering practices. You will collaborate with product, engineering and science stakeholders to translate complex needs into practical solutions and mentor others. This position offers impact by shaping scalable, observable systems that support sustainable agricultural innovation.

Responsibilities

• Design, build and maintain production-grade Python services, libraries and developer tools
• Apply modern Python practices (packaging, typing, async, API design)
• Create shared libraries and templates to standardize internal development
• Develop AI-enabled capabilities including RAG-based search and conversational interfaces
• Define evaluation approaches balancing usefulness, reliability, security and cost
• Develop and maintain CI/CD pipelines and cloud-native delivery using Docker, Kubernetes and Terraform
• Enforce testing, documentation-as-code, and secure software practices
• Improve performance, scalability and observability of platforms
• Implement monitoring, alerting and operational standards for services
• Conduct code reviews, mentor engineers and raise engineering standards
• Partner with engineering, product and scientific stakeholders to translate needs into scalable solutions

Key requirements

• Significant hands-on experience as a Software Engineer with strong Python production-level proficiency
• Equivalent depth in Java may be considered
• Proven ability to write clean, maintainable, well-tested code and solve complex problems independently
• Strong experience with modern Python practices (packaging, dependencies, typing, async, API development)
• Experience designing reusable libraries or internal platforms used by multiple teams
• Knowledge of software quality practices (automated testing, CI/CD, release engineering)
• Experience with Docker, Kubernetes and Infrastructure as Code (Terraform)
• Experience with observability, monitoring, performance profiling and benchmarking
• Solid secure coding practices and vulnerability management awareness
• Applied understanding of Generative AI and LLM patterns, esp. RAG, with ability to design document search or conversational interfaces
• Strong written and spoken English for cross-functional communication

• Collaboration across technical and non-technical stakeholders
• Mentoring and leadership of cross-team initiatives
• Problem-solving with practical, production-focused mindset
• Python
• Java (equivalent depth)
• Docker

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