Top AWS Jobs in Toronto

Designs and implements AWS cloud security architectures, controls, identity and access management, encryption, monitoring, network protections, and DevSecOps automation. Secures containers and serverless workloads, conducts vulnerability assessments and penetration testing, supports compliance audits, develops incident response plans, and integrates security into engineering workflows. The role also leads cloud security initiatives, trains internal teams, and promotes best practices across regulated environments.

Develop and maintain enterprise full-stack applications using Java Spring Boot, React.js, TypeScript, microservices, REST APIs, and cloud technologies. Design scalable backend services, integrate AI agent capabilities, deploy applications using AWS, Kubernetes, and OpenShift, and collaborate with cross-functional teams. Responsibilities include system analysis, testing, implementation, risk management, technical advising, user support, and mentoring junior developers.

Leads a specialized enterprise sales team selling platform, data, analytics, AI, and extensibility solutions to CIO and CTO organizations. Responsibilities include coaching account executives, managing complex $500K+ ARR sales cycles, overseeing statements of work and technology roadmaps, forecasting revenue, modeling business performance, and coordinating co-selling with AWS, GCP, and global system integrators.

Provides customer-facing technical support for Snowflake and cloud environments, owning cases from triage through resolution. Troubleshoots SQL, logs, APIs, data warehousing, MLOps pipelines, model performance, and infrastructure issues using AI-assisted tools, scripting, and automation. Collaborates with engineering and product teams, documents solutions, reports bugs, and participates in on-call, weekend, and holiday rotations. Requires fluent Japanese and English, strong communication, and familiarity with AI, cloud platforms, and machine learning technologies.

Develop and maintain large-scale data and machine learning applications using Scala, Python, Spark, AWS, and modern DevOps practices. Responsibilities include designing data pipelines, deploying and monitoring machine learning models, optimizing distributed systems, supporting the full software lifecycle, documenting processes, and collaborating with data science, Data Ops, DevOps, and product teams in an Agile environment.

As a Senior Software Developer, you will architect and develop robust software solutions, enhance software stability, manage tech debt, and collaborate with teams while staying updated on new technologies.

Leads the technical design and development of fault-tolerant, cross-functional full-stack applications for Capital One’s travel portal. Builds front-end and back-end systems, contributes to architecture and high-level design, establishes engineering standards, improves developer tools and experience, provides technical support, and mentors junior and intermediate engineers. Collaborates throughout the software development lifecycle in an agile, hybrid work environment.

Lead a team of at least six engineers building enterprise developer platforms and tools. Architect AI-powered developer productivity capabilities, optimize development workflows, manage GitHub and CI/CD infrastructure, and improve internal libraries. Partner with engineering, product, and business leaders on technical strategy, mentor engineers, establish standards, and drive innovation across a large technology organization.

The Strategic Account Manager supports enterprise account growth across NAMER by executing account plans, generating pipeline, leading discovery, building stakeholder relationships, coordinating partners and internal teams, and managing opportunities through closure. The role requires enterprise technology or services sales experience, commercial target achievement, complex deal management, value-based selling, accurate forecasting, and strong communication. It offers a development path toward Strategic Account Director.

Build and deploy production generative AI and LLM systems for financial services and healthcare clients. Embed with client teams to understand business operations, design AI solutions, create evaluation suites, and deliver cloud-native systems on AWS. Lead engagements from strategy through deployment, contribute to AI tooling and blueprints, advise senior stakeholders, and support pre-sales. Work hands-on with Claude, Claude Code, Cowork, integrations, and production engineering practices.

Owns enterprise integration architecture across multiple projects and teams using the Boomi platform. Defines integration standards, reference architectures, API strategy, security, deployment models, governance, monitoring, and scalability practices. Designs integrations among enterprise applications, databases, files, APIs, messaging systems, and EDI networks. Leads architecture reviews, production support, migration roadmaps, client discussions, estimates, documentation, and developer mentoring.

The Senior SRE Developer will improve the reliability, performance, observability, scalability, and automation of a cloud-native mortgage platform. Responsibilities include monitoring with Datadog, optimizing CI/CD pipelines using GitHub Actions, Kubernetes, and ArgoCD, managing infrastructure as code with Pulumi and Crossplane, supporting incident response and on-call operations, defining SLOs, advising on system architecture and capacity planning, and enabling development teams through knowledge sharing and operational best practices.

The Senior SRE Developer will improve reliability, performance, observability, scalability, and automation for cloud-native distributed applications. Responsibilities include monitoring and alerting, metrics and log analysis, CI/CD and infrastructure automation, Kubernetes and ArgoCD deployment improvements, capacity planning, incident management, SLO guidance, developer enablement, system design consultation, and participation in the platform on-call rotation.

Lead Irth’s cybersecurity program across vulnerability management, incident response, cloud and identity security, compliance, and customer trust. Prioritize and drive remediation of security findings, manage AWS and Azure security controls, oversee IAM and access reviews, maintain NIST- and ISO-aligned policies, and support SOC 2 audits. Lead incident communications, tabletop exercises, penetration testing, customer security reviews, and regulatory responses while partnering with engineering, infrastructure, IT, GRC, executives, and customers.

Define platform architecture, build agent runtimes and evaluation harnesses, scale AI training and inference pipelines, and deploy Fastino into customer-managed AWS environments. Develop secure sandboxed execution for agent workloads, ship full-stack features, partner with AI researchers, mentor engineers, guide AI coding agents, and translate customer feedback into product decisions.

Own data engineering for workforce forecasting and staffing products. Build and operate Databricks pipelines, lead the Redshift-to-Databricks migration, manage database replication and file ingestion, establish data contracts, handle PII and data residency, monitor quality and costs, and support on-call operations. The role also requires documentation, infrastructure-as-code, collaboration with product and analytics teams, and pipelines supporting forecasting or machine-learning models.

Investigate and manage security incidents from triage through containment and documentation. Build incident-response playbooks, automate repetitive workflows, improve SIEM and SOAR capabilities, develop detection rules, report incident trends, and coordinate with Engineering, HR, Fraud, and Privacy teams. Participate in on-call support and act as incident commander for lower- and medium-severity incidents.

Lead hands-on development of Citi’s multi-tenant enterprise AI platform. Build full-stack AI components, intelligent agent orchestration, Model Context Protocol servers, advanced RAG pipelines, and vector and graph database integrations. Provide technical direction, lead delivery of complex AI platforms, collaborate with subject matter experts and UI/API teams, and deploy scalable generative AI solutions into production.

Lead technical presales engagements with B2B customers by designing API and SaaS solutions, building demos and proofs of concept, creating integrations, and translating requirements into technical specifications. Partner with Account Executives, Product, Engineering, and Public Safety teams to assess feasibility, manage technical risk, and advance customer relationships. Use AI tools to prototype and solve customer challenges. Travel up to 25%.

Leads analytics support for international sports fan growth and engagement. Partners with marketing, club, league, and regional stakeholders to define analytics opportunities, perform SQL and Python analysis, develop segmentation, propensity, churn, forecasting, and customer lifetime value models, and translate findings into business recommendations. Owns reporting and data quality, presents to senior audiences, mentors analysts, coordinates team priorities, and collaborates with data engineering and external partners.

The Data Engineer will design, build, deploy, and maintain scalable data and software solutions across on-premise and cloud environments. Responsibilities include participating in the data engineering lifecycle, improving system performance and resilience, assessing cloud solutions, documenting architectures, collaborating with stakeholders and engineering teams, and implementing modern data practices using Azure, Databricks, Snowflake, Python, and SQL. The role also supports DevSecOps, CI/CD, infrastructure as code, and continuous improvement.

Serve as the primary technical advisor for enterprise customers, guiding Camunda adoption, technical implementation, platform health, risk mitigation, escalations, and ongoing success. Build relationships with business and technical stakeholders, create adoption plans, provide hands-on guidance, and collaborate cross-functionally. The role requires enterprise software experience, programming knowledge, modern solution architecture expertise, Kubernetes familiarity, and willingness to travel on-site up to 50% during busy periods.

Designs, develops, tests, and maintains Python-based APIs, backend services, data platforms, and AI-ready data foundations. The role involves SQL, FastAPI, cloud platforms, secure software development, CI/CD, observability, production support, and integration with enterprise applications. It collaborates with product, AI, application, architecture, reliability, and security teams in an Agile environment to deliver scalable and maintainable platform capabilities.

Supports data transformation initiatives by building and maintaining ETL/ELT pipelines, automating data ingestion, validating data quality, and transforming datasets using SQL or Python. Collaborates with business stakeholders and data professionals across multiple departments, while documenting workflows, data dictionaries, and processes. This role provides hands-on data engineering experience during an eight-month internship.

Build scalable full-stack B2B SaaS applications for fintech customers using Angular, TypeScript, Java Spring Boot, Databricks, relational databases, and AWS. Responsibilities include front-end and back-end development, cloud deployment, testing, code quality, performance optimization, cross-functional collaboration, and mentoring junior engineers.