Senior Software Engineer – AI Infrastructure in Canada Creek, Nova Scotia at Jobgether

• Design and build scalable infrastructure systems powering AI agent and model-driven platforms in production environments
• Develop high-performance Rust-based services for model inference, orchestration, and execution workflows
• Architect distributed systems capable of handling large-scale traffic, ensuring reliability, low latency, and high throughput
• Build and improve ML infrastructure, including model deployment, evaluation, monitoring, and lifecycle management
• Define and implement observability, monitoring, and failure recovery mechanisms for complex agent-based systems
• Optimize system performance, including cost efficiency, latency reduction, and throughput improvements
• Collaborate with AI and agent engineering teams to move prototypes into production-grade systems
• Contribute to key architectural and infrastructure decisions in a high-impact engineering environment

Requirements:

• 5+ years of experience in software engineering with a focus on large-scale production systems
• Strong proficiency in Rust and systems-level programming
• Solid understanding of distributed systems, concurrency, and performance optimization techniques
• Experience operating high-traffic or high-throughput services serving large user bases
• Familiarity with machine learning infrastructure, model serving, or MLOps practices in production
• Experience designing observability, monitoring, and reliability frameworks for complex systems
• Strong problem-solving mindset with a focus on ownership and production stability
• Excellent collaboration skills across infrastructure, ML, and product engineering teams
• Nice to have: experience with LLM systems, agent-based architectures, cloud-native infrastructure, or async/high-performance networking systems

Benefits:

• Fully remote work with international team collaboration
• Opportunity to work on cutting-edge AI and distributed systems at scale
• High-impact engineering environment focused on production reliability and performance
• Exposure to advanced AI agent and machine learning infrastructure systems
• Strong engineering culture centered on ownership, autonomy, and technical excellence
• Career growth in a global, fast-evolving technology domain