Top AWS Jobs in Toronto

Provide technical support to MongoDB customers by diagnosing complex architecture, performance, recovery, security, and deployment issues. Advise customers on operating MongoDB at scale, communicate solutions clearly, advocate for customer needs with product and development teams, and contribute to internal support-tool development. The role requires strong troubleshooting, systems, database, networking, cloud, communication, teamwork, and continuous-learning skills.

Develops and maintains shared backend and frontend platform capabilities, including .NET services, Angular foundations, SDKs, APIs, integrations, identity patterns, data access, messaging, and cloud-native components. Builds automated tests, CI/CD pipelines, observability, security controls, documentation, and reusable engineering standards. Supports consuming development teams, production operations, incident resolution, architecture implementation, and AI-assisted software development while ensuring quality, reliability, maintainability, and secure delivery.

Design and establish a governed AWS data architecture, including layered lake or lakehouse models, analytical data layers, PII controls, access management, lineage, residency, and reusable engineering patterns. Build reliable, loosely coupled data pipelines using managed AWS services, define governance and low-code guardrails, and contribute directly to data product delivery. The role also develops contextual data layers supporting efficient GenAI features and provides durable documentation and patterns for a small engineering team.

Provides technical leadership for application Site Reliability Engineering across AWS and Kubernetes environments. Designs scalable reliability frameworks, automation, self-healing systems, CI/CD pipelines, observability standards, and incident-management practices. Develops production code, mentors engineers, leads architectural decisions, manages on-call escalation, and integrates AI-driven insights into operations. The role influences global cloud strategy and engineering standards while reducing toil, improving uptime, and lowering MTTR.

Qualify enterprise leads, conduct discovery with financial services and life sciences buyers, scope AI consulting engagements with architects, negotiate proposals and SOWs, and close deals. The role manages the full sales cycle, coordinates with AWS and Anthropic partner representatives, maintains CRM and forecasts, and communicates buyer insights to leadership and marketing. Travel up to 30% is required.

Own and grow strategic Anthropic and AWS alliances, building partner activation, funding, competency, co-sell, and pipeline programs. Lead the alliances team, establish operating processes, develop executive partner relationships, and collaborate with sales, marketing, and delivery. Expand partnerships with GCP and emerging AI providers while maintaining partner tiers and program requirements. The role requires hands-on alliance management, team leadership, enterprise communication, AI ecosystem familiarity, and up to 40% travel.

Advise CIOs and technology leaders on IT strategy, digital transformation, cloud adoption, infrastructure modernization, enterprise architecture, and technology operating models. Lead current-state assessments, future-state strategies, roadmaps, business cases, workshops, and executive presentations. Manage project workstreams and stakeholder communications, mentor junior team members, build client relationships, and identify additional consulting opportunities.

Designs enterprise-scale cloud data architectures, lakes, warehouses, and lakehouses across AWS and Azure. Develops high-level designs, medallion architectures, data models, integration patterns, governance and security frameworks. Leads batch and real-time ETL/ELT architecture, cloud modernization, performance and cost optimization, while providing technical leadership and mentoring data engineering teams.

Leads complex application development and modernization across Salesforce, NetSuite, billing, and integrated platforms. Develops production-grade code, automation, integrations, and AI workflows; oversees testing, incident analysis, technical architecture, and vendor delivery. Serves as a subject matter expert, mentors engineers, establishes engineering and DevOps best practices, reviews code, reduces technical debt, and supports strategic enterprise initiatives.

Develop web applications and interconnected system solutions using Node.js, TypeScript, relational databases, APIs, and cloud services. Responsibilities include designing features, debugging, refactoring, code reviews, unit and integration testing, technical documentation, secure software development, and collaboration within agile SDLC processes. The role requires working with REST services, third-party integrations, source control, and frontend frameworks such as React or Angular.

Build and operate Thomson Reuters’ scalable search platform, including document ingestion pipelines, indexing systems, query APIs, cloud infrastructure, and AI-enabled retrieval capabilities. Responsibilities include designing distributed services, migrating from OpenSearch to Vespa, improving observability and reliability, participating in on-call, owning production incidents, mentoring engineers, and collaborating with research scientists and client teams to deliver search and AI features.

Build and deploy production-grade AI solutions for legal workflows, including RAG pipelines, agentic systems, enterprise integrations, evaluation frameworks, and observability. Collaborate with architects, engineers, clients, and legal subject-matter experts to translate legal needs into secure, scalable implementations. Participate in technical discovery, prototyping, demonstrations, prompt engineering, model evaluation, red-teaming, and MLOps/LLMOps lifecycle management.

Design, build, and deploy scalable, secure machine learning solutions—with emphasis on recommender systems. Produce design docs and representative models, establish ML best practices and quality control, lead engineering efforts, and collaborate cross-functionally to integrate ML products using cloud, MLOps, and data engineering tools.

Design, build, and operate a scalable search control plane managing provisioning, configuration, upgrades, indexing, and retirement across Kubernetes, Kafka, Vespa, and OpenSearch. Own multi-tenant security, observability, SLOs, infrastructure as code, CI/CD, capacity planning, reliability, and incident response. Provide technical leadership, establish architectural standards, lead infrastructure initiatives, partner with client teams, and mentor engineers.

The Senior Data Scientist will collect and transform complex datasets, develop and deploy machine learning, NLP, generative AI, and agent solutions, and optimize models for accuracy, explainability, and ethical alignment. Responsibilities include building custom transformer models, monitoring production pipelines, communicating insights through visualizations and presentations, and collaborating with cross-functional teams to drive productivity, revenue, and strategic decision-making.

Develop and support scalable, secure software for enterprise data catalog services. Responsibilities include designing and coding backend services, APIs, integrations, and data flows; applying cloud-native deployment and infrastructure patterns; testing, monitoring, and troubleshooting applications; conducting code reviews; documenting technical decisions; supporting incident resolution; and using approved AI-assisted development tools safely. The role also involves collaborating with architecture, security, infrastructure, product, and technology partners while contributing reusable engineering practices and mentoring team members.

Monitor, triage, investigate, and respond to enterprise security incidents across endpoint, network, identity, cloud, and application environments. Analyze SIEM and EDR/XDR telemetry, identify attack patterns and indicators of compromise, execute containment and eradication, improve detection rules and response playbooks, document investigations, support vulnerability remediation, and collaborate with technical and business stakeholders. Participate in on-call rotations, security exercises, reporting, and continuous improvement.

Lead solution architecture for enterprise applications, driving cloud (Azure) adoption, IAM (Okta/Auth0/Azure AD) design, microservices integration, API and batch processing, application portfolio rationalization, and governance. Partner with business and delivery teams to design secure authentication/authorization, create architecture roadmaps, and implement DevSecOps and agile practices.

Leads and develops a team of 6–8 software engineers while guiding architecture, design, data modeling, delivery practices, and technical growth. Partners with Product and Design to discover customer needs, assess feasibility, deliver incrementally, and share accountability for outcomes. Collaborates with engineering leaders on cross-team systems, infrastructure, CI/CD, testing, security, hiring, and engineering culture. Requires strong product engineering, leadership, communication, architecture, and mentoring experience.

Lead and support a team of 3–5 software engineers while remaining hands-on in development and testing. Guide architecture, data modeling, implementation, technical practices, and team growth. Partner with product and design leaders to discover customer needs, assess feasibility, deliver incrementally, and balance product innovation with technical health. Collaborate across engineering teams on shared systems, infrastructure, CI/CD, security, hiring, culture, and long-term subsystem ownership.

Develop and support AWS cloud-native web applications using Node.js, TypeScript, React, and Redux. Design backend services and asynchronous queue-based processes, build reusable frontend components, write unit tests, conduct code reviews, maintain quality standards, and manage AWS resources. Collaborate with product, UX, and QA teams in an Agile environment while mentoring junior developers.

Manage inbound enterprise leads and complete the full sales cycle for AI consulting engagements. Qualify prospects, conduct discovery with financial services and life sciences buyers, scope proposals with architects, negotiate contracts, and close signed statements of work. Maintain CRM accuracy, forecast deals, coordinate with AWS and Anthropic partner representatives, and provide market feedback to leadership. Travel for client meetings up to 30% of the time.

Build, execute, and maintain CI/CD and service pipelines across defined environments. Support source-control workflows, Azure deployments, SQL database changes, and build and deployment activities with development and QA teams. Participate in SAFe Agile ceremonies and contribute to sprint delivery while following established processes and incrementally improving infrastructure and deployment workflows.

Lead and develop an engineering team building AI content-platform systems, including ingestion, data processing, indexing, retrieval, and rendering. Set technical direction, collaborate with Product and Engineering leaders, guide architecture and design, ensure reliable delivery, improve engineering practices, hire engineers, and clarify system ownership. The role remains technically engaged through architecture discussions, code reviews, and distributed-systems problem solving.

Leads a distributed cloud support team as a hands-on technical player-coach. Responsibilities include resolving complex customer issues, managing escalations and incidents, monitoring support quality and queue health, mentoring engineers, improving processes, creating technical documentation and training, and coordinating with Engineering, Product, Security, Legal, Billing, and global support teams.