Top Tech Jobs & Startup Jobs in Toronto

Leads the technical vision and delivery of an enterprise agentic AI program. Oversees architecture, evaluation, deployment, MLOps, reliability, security, and scalability across multiple workstreams. Partners with executives and client stakeholders on roadmaps and high-stakes decisions, aligns data science and engineering teams, establishes technical standards, and mentors senior technical leaders. Requires deep experience in AI/ML, LLMs, agentic systems, AWS, distributed systems, evaluation, and production-scale software engineering.

Designs and delivers complex cloud, data, and AI/ML systems. Responsibilities include building cloud-native microservices, serverless and containerized workloads; implementing infrastructure as code, CI/CD, monitoring, and observability; contributing to data platforms and MLOps; and integrating LLM capabilities. The role collaborates with engineering, data, AI, and product teams, documents architecture, participates in design reviews, establishes best practices, and mentors junior engineers.

Leads end-to-end architecture for complex cloud, data, and AI/ML systems. Defines technical strategy, designs scalable multi-cloud and hybrid solutions, establishes infrastructure-as-code and DevOps standards, drives migrations and modernization, and optimizes performance, cost, security, and reliability. Partners with clients and leadership, documents architecture, mentors engineers, evaluates emerging technologies, and serves as a technical escalation point for complex integration challenges.

Train and operate production machine learning models on Amazon SageMaker using AWS Trainium. Optimize PyTorch code for Trainium compilation, memory, throughput, and distributed training; diagnose hardware, compiler, device, data, and code issues; build cost-aware end-to-end training pipelines; and collaborate directly with client and internal engineering teams to deliver production workloads.