Full Stack Engineer

TeraCyte is looking for an experienced and self-driven Senior Full Stack Cloud Engineer to take end-to-end ownership of key software components that run across a highly distributed, data-intensive cloud environment. This role blends advanced backend and frontend engineering with responsibility for designing cloud architecture focused on data storage, resource management, scalability, and performance. 

You'll work closely with imaging, AI, and infrastructure teams to ensure robust, efficient, and scalable pipelines, from raw data ingestion to user-facing visualization. 

Responsibilities

• Design and implement scalable backend services using Python for data processing, image analysis, and algorithmic workflows. 
• Own the architecture of cloud-native services with a focus on storage strategy, resource efficiency, and performance optimization. 
• Develop and maintain modern, responsive frontend applications for visualizing and interacting with complex datasets. 
• Collaborate with algorithm and data teams to integrate analytics and AI models into production environments. 
• Build tools and services that enable traceability, reproducibility, and performance insights across the stack. 
• Lead architectural decisions related to cloud environments, balancing cost, speed, and scalability. 

Requirements 

• 5+ years of experience in full stack or cloud engineering roles, preferably in data- or science-heavy environments. 
• Deep understanding of cloud architecture, especially around storage management (e.g., blob storage, data lakes), compute resource optimization, and performance monitoring. 
• Proficient in Python, with strong experience in building backend APIs and services. 
• Solid understanding of image processing and computational pipelines. 
• Skilled in modern frontend frameworks such as React, Vue, or Angular. 
• Familiarity with distributed task frameworks (e.g., Celery) and messaging systems (e.g., RabbitMQ, Redis). 
• Independent and self-motivated with the ability to lead technical initiatives across teams. 

Nice to Have 

• Experience working with high-throughput imaging systems or biomedical datasets. 
• Exposure to MLOps or integration of AI/ML pipelines into production. 
• Knowledge of cost/performance trade-offs in cloud environments (especially Azure). 

If interested, please send email to [email protected]