Software Engineer - Infrastructure

Role overview Develop infrastructure and data platform capabilities that help production services run reliably and scale. The work combines cloud engineering, data integration, container orchestration, and support for compute and secure execution environments used by AI agents and predictive modeling workloads.

Responsibilities - Design and build scalable ETL and ELT processes for data integration. - Provision and scale compute, model-serving, and secure execution environments for production AI agents. - Improve an on-demand predictive modeling platform using Python. - Deploy and manage containerized services with Docker and Kubernetes. - Solve cloud-native engineering challenges using major cloud platforms. - Expand automated testing across unit, integration, scaling, health-check, and performance needs. - Support platform security and industry-standard compliance practices.

Requirements - Two to four years of software engineering experience and a bachelor’s or master’s degree in computer science or engineering. - Advanced experience with Python, cloud services, or ETL/ELT pipelines. - Understanding of software design patterns and testing practices. - Familiarity with streaming data processing and real-time analytics. - Knowledge of data governance, security, and compliance practices.

Nice to have Experience with Kubernetes or managed Kubernetes services such as EKS or AKS.

Benefits and work setup The source lists a Massachusetts base salary range of $134,000–$158,000 USD for full-time work. Total compensation includes base pay, bonus or commission, equity, and benefits such as health, dental, life insurance, a 401(k), and paid time off. A flexible hybrid work model is described. Visa sponsorship is not offered.