Top AWS Jobs in Toronto

As a Principal Machine Learning Engineer, you'll design and implement core ML systems for AI agents, collaborating with cross-functional teams and overseeing the full lifecycle of products from data strategy to deployment.

The Senior Growth Platform Engineer will design and build scalable backend systems, APIs, and growth infrastructure to enhance experimentation and targeting capabilities for retailers.

Build and operate scalable backend services and APIs for an AI-powered developer platform. Own architecture, end-to-end delivery, performance tuning, observability, and mentoring of engineers while collaborating with product and cross-functional teams.

Lead design and delivery of large-scale backend platform services for AI-driven workflows. Drive architecture, cross-team initiatives, reliability, observability, and operational excellence. Mentor engineers and raise engineering standards to improve developer productivity, performance, resilience, and cost efficiency across the platform.

Design and optimize training and inference systems for LLMs and multimodal models, architect AI integrations into media production (PAM/MAM, studios), evolve GPU infrastructure, lead MLOps/LLMOps, mentor engineers, and ensure secure, low-latency, highly available AI services for 24/7 media workflows.

Design and build an AWS-based lakehouse and scalable enterprise data platform. Create governed data products and automated Python/SQL pipelines. Establish standards for data quality, governance, security, observability, and CI/CD. Partner with engineering, product, finance, and business teams to enable analytics and AI and define the platform's long-term vision.

Lead a team of up to 10 engineers to deliver AI workflow solutions for R&D. Drive technical vision, ensure quality, establish standards, recruit and develop staff, manage vendors, and collaborate with product and scientific stakeholders to execute the team's roadmap.

Lead and grow a small engineering team to deliver scalable, secure microservices-based applications. Drive technical design, coaching, AI adoption in SDLC, ensure compliance, prioritize goals, and collaborate cross-functionally to meet timelines and improve engineering quality.

Lead technical direction for backend, AI orchestration, and identity systems for CoCounsel. Design authentication/authorization, multi-tenant isolation, large-scale AI workflows, observability, SLOs, and reliability. Partner with product, security, and ML teams; mentor engineers and own end-to-end delivery of production-grade legal AI systems.

Lead security and compliance architecture for CoCounsel, implementing SOC 2, ISO, HIPAA, and FedRAMP controls; build compliance-as-code, data protection (encryption, key management, tenant isolation), IAM, observability, and audit tooling; partner with security, legal, and engineering; mentor teams and ensure production-scale, provable compliance and incident readiness.

Lead design and implementation of full‑stack, cloud‑native applications; analyze complex business and system processes; coach mid‑level developers; drive application architecture, coding standards, testing, and deployment; integrate Gen‑AI capabilities and ensure regulatory and policy compliance.

Lead and grow a team of DBAs and data engineers to ensure reliable, scalable, and secure data infrastructure. Oversee heterogeneous databases, define cloud and containerization strategies, drive IaC and automation, support data pipelines and ETL/ELT, and implement high availability and disaster recovery practices.

Design, build, and maintain scalable full-stack web applications using Python, .NET and modern frontend frameworks. Develop REST APIs, integrate AI/ML or LLM capabilities, work with relational/NoSQL databases, deploy to cloud environments, optimize performance, and ensure security and quality through testing, code reviews, and collaboration with cross-functional teams.

The Senior Data Engineer will scale the data ecosystem, construct data models, build systems for KPI tracking, and ensure data safety.

The Data Analyst will analyze large datasets, collaborate with stakeholders, develop data processes, and support data-driven decision-making to improve business efficiency.

Manage and coach a software development team, define engineering practices, drive delivery and architecture decisions, ensure application quality, security and scalability, recruit and evaluate staff, and coordinate cross-functional project execution and maintenance.

Design, build, and maintain cloud and hybrid data platforms for cybersecurity analytics. Lead platform architecture, implement IaC and automation, scale petabyte systems, run SRE practices, develop deployment/observability tooling, mentor engineers, and own platform reliability and performance.

Lead enterprise infrastructure automation and Platform Engineering strategy for self-hosted datacenters. Define IaC roadmaps using Ansible and Terraform, integrate Generative AI tools, establish architectural governance and automated security/compliance guardrails, architect core datacenter technologies and storage, drive observability (Splunk/Grafana) and OS lifecycle management, and provide technical leadership and mentorship to Automation and Systems Engineers.

Build and maintain Quora's ML platform and ranking infrastructure to serve large-scale ML models. Work on GPU model serving, distributed systems, developer tooling, feature store modernization, and on-call rotation to ensure high availability, performance, and cost efficiency.

Design, build, and deploy AI-powered legal applications using LLMs, RAG, and agentic AI. Partner with legal stakeholders to translate workflows, build document ingestion and vector search pipelines, ship production-grade features, implement governance/security controls, and mentor/legal users while aligning solutions with enterprise architecture and monitoring quality and evaluation metrics.

Senior backend engineer responsible for building and scaling microservice-based backend systems, driving technical initiatives, collaborating with product and sales, prioritizing customer needs, improving infrastructure and performance, and using AI tools to accelerate development and workflows.

Build and scale the enterprise sales organization: define sales architecture, hire and lead founding sales team, own enterprise ARR growth, close initial six- and seven-figure deals, establish land-and-expand motions, manage channel/partner strategy, navigate enterprise security/procurement, and align sales with product and engineering.

Lead design and operations of GPU infrastructure and Kubernetes-based AI platform environments. Manage capacity planning, optimize training/inference workloads, define reliability and security practices, implement IaC, monitoring, and disaster recovery, and collaborate with AI engineering to evolve infrastructure.

Lead technical design and delivery of scalable, secure microservices. Drive engineering standards, code reviews, architecture decisions, cross-functional collaboration, and introduce tools/process improvements.

Design, develop, and maintain scalable full-stack services using a TypeScript stack and microservices. Collaborate with stakeholders, participate in code reviews and system design, lead project lifecycles, optimize performance, and ensure testable, reliable code across frontend and backend systems.