Top AWS Jobs in Toronto

Conduct product and user behavior analysis, define KPIs, build dashboards and models, and design and evaluate A/B and multivariate experiments. Partner with product, lifecycle, marketing, data, and engineering teams to generate insights, improve user experiences, inform feature launches, and support growth decisions.

Design, build, test, deploy, and monitor scalable software systems for client organizations. Collaborate with engineers, product managers, and designers across distributed systems, APIs, data, cloud, and user-facing applications. Use AI-assisted development and integrate AI or LLM capabilities into products while working directly with clients in a collaborative consulting environment.

Conduct third-party security assessments, evaluate vendor controls, document risk findings, automate GRC workflows with Python and agentic coding tools, maintain integrations across ticketing and risk platforms, and develop dashboards and reporting. Partner with Procurement, Legal, Engineering, IT, Compliance, and Privacy to support risk-informed decisions and mature security governance processes.

Designs, deploys, and supports enterprise Azure cloud and DevOps solutions in a banking environment. Responsibilities include building CI/CD pipelines, managing Azure DevOps environments, automating infrastructure with Terraform and Bicep, supporting cloud services and container workloads, monitoring systems, troubleshooting incidents, and collaborating with technical and business stakeholders to deliver secure, reliable platforms.

Lead Forward Financing’s application and product security program, including pentesting, code review, vulnerability remediation, AI security testing, secure SDLC practices, and external exposure controls. Manage and develop senior security engineers, establish testing standards and remediation SLAs, build security services, and partner with engineering and executives to prioritize risk across web applications, APIs, cloud infrastructure, and AI-built software.

Leads data engineering consulting engagements, serving as a subject matter expert and data architect. Designs scalable data environments, models, pipelines, integrations, warehouses, and visualizations while ensuring quality and governance. Leads architectural decisions, project delivery, technology strategy, and AI-augmented development practices. Mentors technical teams, collaborates with data scientists, analysts, clients, and stakeholders, and drives process improvements and innovation. The remote role may require infrequent travel to the United States.

Owns 4–6 enterprise client relationships and a $1M–$3M portfolio. Leads technical discovery, requirements gathering, solution alignment, roadmap planning, risk management, and cross-functional delivery coordination. Advises clients on digital platforms, commerce, cloud, integrations, analytics, and software delivery. Partners with business development on proposals and expansion opportunities while maintaining account and pipeline data in HubSpot.

Leads Affirm’s Resilience Engineering team, defining strategy and managing engineers who build platforms for safe production load testing and chaos engineering. Owns fault-injection and experimentation systems, safeguards, observability, rollback mechanisms, monitoring, and incident response practices. Partners cross-functionally to identify systemic weaknesses, improve reliability, and embed resilience validation into engineering workflows. Requires leadership experience in reliability, infrastructure, or distributed systems and hands-on expertise with production testing, chaos engineering, cloud-native environments, and distributed-system failure modes.

Design, build, operate, and maintain critical distributed systems powering Grafana Cloud Metrics and the open-source Mimir project. Drive projects from concept through production, improve reliability and performance, contribute to roadmap and design decisions, review code, support teammates, manage releases, and participate in follow-the-sun on-call rotations. Work with cloud infrastructure, microservices, observability systems, and large-scale telemetry databases while collaborating in a remote, open-source environment.

Lead approximately 15 engineers and three engineering managers across communications products including SMS, secure messaging, email, and fax. Drive zero-to-one product development, reliability, and deliverability at scale while partnering with Product and Design. Develop engineering leaders, advocate for technical investments, translate technical impact for stakeholders, and guide practical AI adoption in a regulated SaaS environment.

Owns two revenue motions: converting Anthropic and AWS partner-sourced enterprise leads into consulting clients and independently generating new business in Financial Services and Life Sciences. Responsibilities include full-cycle sales, partner relationship management, co-selling, pipeline reviews, joint go-to-market planning, executive engagement, proposal scoping, negotiations, and closing consulting statements of work. The role also requires building an enterprise decision-maker network and collaborating with delivery, architecture, leadership, and marketing teams.

Own end-to-end enterprise deployments of Spellbook’s AI-powered legal technology. Build integrations with document management, identity, and internal systems; design workflow-heavy solutions involving permissions, approvals, routing, and auditability; customize AI workflows; collaborate directly with legal teams and end users; and convert deployment insights into scalable platform features.

Build and evolve Spellbook’s platform and infrastructure across AWS, MongoDB, infrastructure as code, CI/CD, authentication, APIs, worker queues, monitoring, and observability. Improve service reliability, performance, developer productivity, build tooling, and development workflows while establishing quality and operational best practices for a growing engineering team.

Build and scale backend systems and AI workflows for Spellbook’s legal technology platform. Responsibilities include designing reliable search, inference, orchestration, and RAG retrieval systems; managing rate limits, retries, fallbacks, permissions, and data isolation; optimizing MongoDB performance; partnering with Product and Design; and participating in on-call response. The role requires strong distributed-systems expertise, production backend experience, and the ability to turn ambiguous problems into reliable shipped solutions.

Own post-sales technical relationships for Azure-focused customers, providing FinOps guidance, cloud commitment optimization, governance advice, and executive-level business insights. Monitor Azure commitment utilization, lead Quarterly Business Reviews, identify expansion opportunities, and collaborate with Product, Engineering, and Support to resolve challenges and influence the roadmap. The role requires strong Azure expertise, cloud economics knowledge, customer-facing communication, and the ability to translate technical findings into measurable business outcomes.

Own post-sales technical relationships for enterprise and mid-market customers, advising on multi-cloud FinOps, commitment strategy, cloud cost optimization, governance, and savings. Lead executive business reviews, translate cloud consumption data into business insights, identify expansion opportunities, resolve customer challenges with internal teams, and mentor junior Technical Account Managers.

Build and optimize backend services, APIs, databases, and high-performance compute models. Develop systems in C# and Java and optimized C++ simulation code using concurrency, synchronization, multiprocessing, and numerical methods. Design IPC mechanisms, profile performance-critical workloads, contribute to architecture and code reviews, mentor engineers, and support testing and CI/CD. Preferred experience includes parallel computing, scientific or geospatial modeling, cloud infrastructure, containers, observability, and high-throughput pipelines.

Provides production database administration and support across Oracle RDS, Aurora PostgreSQL, and Microsoft SQL Server in AWS environments. Responsibilities include incident response, performance tuning, troubleshooting, security hardening, monitoring, backup and recovery, schema changes, ticket management, documentation, and collaboration with application and infrastructure teams. The role supports highly available customer-facing databases and contributes to automation, compliance, reliability, and continuous operational improvement.

Develop high-performance networking software across data-path, control-plane, forwarding, and protocol layers. Build packet-processing pipelines using C/C++, DPDK, VPP, and Network ASICs; implement SD-WAN, IPsec, VPN, firewall, DPI, and QoS capabilities. Integrate networking components into Kubernetes and Docker environments using distributed systems, message buses, and gRPC. Troubleshoot production systems and collaborate with distributed engineering teams.

Design, build, and productionize LLM-powered systems (adaptive content, tutors, evaluators) and AI pipelines (RAG, embeddings, fine-tuning). Prototype and optimize models across modalities, define AI safety/evaluation/observability practices, and collaborate with product and engineering to measure learner outcomes and iterate.

Design, build, and maintain SparkSQL/PySpark data pipelines in the central data lake to ingest IoT, product, and unstructured data (video/audio). Produce reliable computed tables for analytics, model training, and dashboards; integrate external datasets; ensure high data quality and uptime; and collaborate with Data Science, ML, and cross-functional teams.

Design, build, and operate large-scale Spark/PySpark data pipelines and the enterprise data platform. Implement data integrations, transformations (Python/SQL), monitoring, and data quality. Build MCP servers and AI-enabled tooling, optimize performance, mentor engineers, and lead cross-functional data projects to enable analytics and automation.

The Staff Software Engineer, Backend for Capacity Modeling develops scalable backend systems, maintains capacity models, and collaborates on technical strategies while ensuring system availability and high-quality code delivery.

Build and maintain backend systems for money movement and card ledger features. Design, develop, and launch scalable APIs and services (Python or Kotlin) using AWS, MySQL, and Kubernetes. Collaborate with product, design, data science, and cross-functional teams, support operations and on-call, create and monitor metrics, participate in code reviews and hiring, and deliver well-tested, extensible solutions.

Own and evolve Babylist's AWS infrastructure, Terraform IaC, Kubernetes/EKS clusters, CI/CD, and observability for a platform serving millions. Lead incident response, improve developer tooling, and set reliability standards across engineering teams.