Software Engineer AI Enablement

IDEXX’s Data & AI Center of Excellence is seeking a Software Engineer to join our AI Enablement Team. This role focuses on building and operating the software, platforms, and cloud infrastructure that power our Clinical and Generative AI solutions.

This is a hybrid role, requiring 2 days per week and 8 days per month in our Westbrook, ME office.

As a Software Engineer, you will design, build, and maintain well-structured Python applications, services, and data pipelines, and the AWS infrastructure they run on. You’ll own your code from design through deployment, using infrastructure as code and CI/CD to deliver reliable, scalable, and maintainable systems. You’ll work closely with data scientists, data engineers, and product teams, turning their needs into production-grade software.

No machine learning background is required; strong engineering fundamentals are what matter most.

IDEXX Data and AI Center of Excellence (COE) develops and delivers data and AI assets and solutions to enhance IDEXX products, services, internal operations, and business practices. It is a large team of talented engineers, architects, data scientists, and analysts driving cutting-edge AI innovation in veterinary care.

Software Engineering Design, build, and maintain Python applications, APIs, and services that run reliably in production.

Apply established software design patterns and clean code principles; contribute to architectural discussions.

Build and maintain data processing pipelines using Spark on Databricks.

Write automated tests and participate in code reviews to ensure quality and adherence to engineering best practices.

Improve the performance, scalability, and reliability of existing systems.

Dev Ops and Cloud Infrastructure Provision and manage AWS infrastructure using infrastructure as code (e.g., Terraform, AWS CDK, or Cloud Formation).Build and maintain CI/CD pipelines for automated testing, deployment, and release.

Containerize and deploy applications using Docker and AWS services.

Implement monitoring, logging, and alerting to keep systems healthy and observable.

Balance cost, time, and technical capability when implementing solutions.

Collaboration and Teamwork Contribute to an internal development platform that helps teams across the enterprise adopt AI capabilities.

Partner with data scientists, data engineers, and product teams to turn requirements into robust software.

Identify reusable components and infrastructure that reduce duplicated effort across teams.

Collaborate with and learn from senior team members; share knowledge with peers.

Work independently on well-defined problems, escalating ambiguous or high-impact decisions as needed.

What You Need to Succeed3–5 years of professional software engineering experience.

Strong programming skills in Python, with a solid grasp of object-oriented design and common design patterns.

Hands-on experience with infrastructure as code (Terraform, AWS CDK, Cloud Formation, or similar).

Experience with AWS services such as EC2, S3, Lambda, IAM, and ECS/EKS.

Experience with CI/CD tooling (e.g., Git Hub Actions, Git Lab CI, Jenkins) and containerization with Docker.

Working knowledge of Spark and Databricks, or a strong willingness to learn them quickly.

Solid understanding of testing practices, version control (Git), and Agile methodologies.

Familiarity with SQL and data engineering concepts.

Good analytical and problem-solving skills, adaptable to evolving technologies.

Good communication skills to work effectively with engineers, data scientists, and stakeholders.

Nice to Have Exposure to AI/ML applications or supporting data science teams.

Experience with Delta Lake, AWS Sage Maker, or Kubernetes.

Familiarity with additional programming languages.

What you can expect from…