Senior AI Software Engineer

IDEXX develops veterinary software solutions that use cloud technology to improve animal health and support veterinary practices worldwide. The Senior AI Software Engineer will build AI-driven developer tools, agentic systems, and intelligent workflows that accelerate software development, improve engineering experiences, and advance veterinary software capabilities.

Responsibilities:

• Architect AI-Powered Developer Tools: Design and implement scalable AI systems using modern ML frameworks (e.g., PyTorch, TensorFlow) to automate code generation, debugging, and testing—making development faster, more intuitive, and enjoyable for our teams
• Pioneer Agentic AI Innovations: Advance autonomous AI agents capable of independent decision-making and problem-solving, integrating them into our SaaS platform to deliver real value, like predictive analytics for animal health data or adaptive user experiences
• Enhance Engineering Workflows and Experiences: Collaborate across tribes to identify bottlenecks, prototype AI-enhanced solutions (e.g., natural language interfaces for DevOps tasks), and foster best-in-class practices—while mentoring junior engineers and influencing strategic roadmaps

Requirements:

• 5+ years of software engineering experience, with at least 2+ years focusing on Developer Experience or developer tooling
• Deep understanding of software development workflows, CI/CD, source control (Git), testing, and automation
• Hands-on experience integrating AI/ML models into engineering processes (e.g., LLMs like OpenAI, Anthropic, open-source LLMs)
• Proficiency in backend development (e.g., Python, Go, Node.js) and scripting languages
• Experience building plugins or extensions for developer tools (e.g., VS Code, GitHub Apps, CLI tools)
• Strong communication skills and empathy for developer pain points
• Bias for action — you turn insights into working solutions quickly and iteratively
• Experience building with AI platforms (OpenAI, Hugging Face, LangChain, etc.)
• Experience working in platform engineering, productivity engineering, or DevOps
• Prior contributions to open-source developer tools
• Familiarity with observability and performance tooling
• Background in machine learning, natural language processing, or prompt engineering