DevOps Software Engineer

Chloris Geospatial • Boston, MA

1d • Hybrid

About The Position

Chloris is looking for a talented DevOps Engineer to support the deployment of Chloris’ innovative technology for measuring carbon stock for the voluntary carbon markets. Specifically, we are looking for someone who:
Has experience with cloud computing technologies and bringing containerized software to production
Is passionate about empowering other engineers by improving workflows and reducing the time from development to production
Isn’t afraid to roll up their sleeves to tackle new challenges
Is excited about the opportunity to join a mission-oriented and high-potential start-up, anchored in pioneering science and focused on delivering best-in-class data and technology for nature-based solutions.
The DevOps Engineer will report to the CTO and will work closely with the Big Data, Web Platform, and Data Science Teams.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent
• 3 - 5 years of professional software engineering experience
• 2+ years of experience deploying and managing infrastructure in an AWS cloud environment.
• Experience working with a container orchestration service (Kubernetes preferred)
• Experience with IaC tools such as Terraform, Cloudformation, Helm
• Experience building and managing CICD pipelines (GitHub Actions, GitLab CICD, Jenkins)
• Experience with Linux system administration
• Proficiency in Python, Bash, and Docker
• Excellent problem-solving, analytical, and communication skills

Responsibilities

• Design, build, and maintain cloud infrastructure on AWS to support Chloris's production applications and internal tooling for data scientists and analysts
• Develop and manage CI/CD pipelines to automate the path from development to production for containerized applications
• Manage and optimize Kubernetes clusters powering distributed computing workloads, including our Dask-based geospatial processing system
• Support data science and engineering teams by building and maintaining infrastructure for ML training workflows, data pipelines, and large-scale geospatial processing
• Implement and manage monitoring, logging, and alerting systems to ensure reliability and performance across production services
• Improve developer experience by streamlining workflows, reducing friction in local and cloud development environments, and maintaining clear infrastructure documentation

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level