📋 Description

• Build and maintain infrastructure and tooling for training, evaluating, deploying, serving, and
• Develop and operate production backend services, APIs, and pipelines supporting recommendations
• Improve CI/CD pipelines, automated testing, release processes, rollback strategies, and environment
• Establish comprehensive observability across application health, model behavior, agent quality
• Build reproducibility and lifecycle management practices for models, prompts, datasets
• Support experimentation and measurement infrastructure that enables ML and product teams to

🎯 Requirements

• Strong software engineering background with experience building, deploying, and operating
• Proven experience with backend services, cloud infrastructure, CI/CD, automated testing
• Strong proficiency in Python and the ability to work effectively across backend services
• Good understanding of reliability, performance, maintainability, scalability, and infrastructure
• Ability to collaborate effectively with ML and product teams and independently drive ambiguous
• Strong ownership mentality, attention to detail, and a practical approach focused on simplifying

🎁 Benefits

• Opportunity to take foundational ownership of an AI platform and its engineering standards.
• Broad technical scope spanning backend engineering, cloud infrastructure, MLOps, GenAI
• Direct opportunity to influence how ML and GenAI capabilities are brought into production.
• High level of autonomy and ownership in a growing technology environment.
• Opportunity to work closely with ML, product, and engineering teams on high-impact systems.
• Fully remote work environment.