Top AWS Jobs in Toronto

Develops and supports data and AI products, translating business requirements into technical solutions. Responsibilities include data pipeline and warehouse development, testing, documentation, defect resolution, technical design, automation, reusable framework creation, process improvement, and stakeholder collaboration. The role requires ETL/ELT, SQL, NoSQL, Python, Spark, Scala, cloud, Hadoop, data profiling, batch and streaming data, and emerging AI capabilities.

Responds to production incidents across AWS and Kubernetes, diagnosing and remediating infrastructure, networking, database, cache, and deployment issues. Builds monitoring, observability, synthetic and load tests, SLOs, and reliability improvements. Maintains Terraform, Kubernetes, CI/CD, IAM, autoscaling, and security configurations; leads postmortems and incident follow-up. Participates in on-call operations and collaborates with engineering teams to improve application performance and reliability.

Develop and maintain scalable Java and big data applications across the software development lifecycle. Build distributed data-processing tools, REST APIs, and automation; analyze and debug systems; conduct test-driven validation; review code; and collaborate with internal teams and vendors. The role works with technologies including Apache Hudi, Trino, Spark, Kafka, cloud storage, and distributed computing platforms while promoting performance, reliability, modern engineering practices, and continuous technical improvement.

Designs and operates cloud foundations across AWS and GCP, including governance, identity, access controls, infrastructure as code, security primitives, networking, resource inventory, billing visibility, and self-service tooling. The role combines production software engineering, hands-on operations, monitoring, troubleshooting, documentation, and on-call ownership while enabling engineering teams to provision infrastructure safely and independently.

Owns end-to-end response to high-impact incidents in a 24/7 SaaS production environment. Coordinates technical teams during live incident bridges, removes blockers, manages escalations, communicates business impact, and ensures safe mitigations. Leads post-incident reviews, tracks metrics, improves runbooks and processes, and supports change and problem management. The role requires ITSM expertise, cloud and DevOps knowledge, AI-tool proficiency, strong communication, and calm decision-making under pressure.

Leads technical design and hands-on development for enterprise Java applications supporting secure, scalable payment platforms. Responsibilities include architecture and code reviews, API and integration development, database optimization, mentoring developers, Agile delivery, CI/CD, production support, incident remediation, observability, and modernization initiatives. The role collaborates with architects and financial institutions while driving engineering standards, solution design, and operational excellence.

Lead and manage MongoDB’s Storage Execution team, owning the roadmap for durability, availability, performance, transactions, storage architecture, index operations, and developer productivity. Partner with adjacent engineering and cloud teams, manage customer escalations, drive cross-team initiatives, improve engineering processes, and develop engineers through hiring, coaching, and performance management.

Build and operate AWS infrastructure, automation, observability, CI/CD pipelines, and internal developer platform components. Improve system reliability through resilience testing, automated recovery, capacity planning, and SLOs. Own projects from planning through rollout, mentor engineers, establish infrastructure standards, collaborate with software and security teams, and participate in a low-volume on-call rotation.

Own the post-sale technical relationship with customers, leading onboarding, architecture reviews, production launches, cluster health checks, usage reviews, and technical escalations. Partner with Support, Engineering, Product, and Solutions Architecture to resolve issues, communicate customer requirements, improve adoption, and drive technical success, expansion, and retention.

Lead the product workstream in client engagements to assess current PDLC, design future-state AI-native product development, coach PMs, scope and write executable specs for prototypes and MVPs, shape agentic product tooling, and feed field learnings back into methodology and pre-sales.

Lead development of a massively distributed edge compute platform. Design fault-tolerant systems, external APIs, high-throughput traffic routing, and Kubernetes-based resource management. Establish architecture standards, reliability metrics, security practices, and technical governance. Collaborate with AI/ML, hardware, networking, and security teams; communicate risks to executives; manage customer requirements; review code; and mentor engineers on distributed systems best practices.

Design, develop, test, and maintain scalable platform software and services. Collaborate with architecture and cross-functional teams, implement platform features, participate in code reviews, document technical specifications, troubleshoot issues, and optimize performance and scalability. The role requires Go development, scripting, Kubernetes, cloud-native technologies, containerization, cloud networking, and CI/CD experience.

Supports customers with database integration issues while developing and debugging Airbyte’s Java and Kotlin database connectors. Investigates replication, CDC, query performance, authentication, networking, schema evolution, and sync-state problems across databases, warehouses, and data lakes. Reproduces bugs, contributes to open-source code, collaborates with Engineering and Product, supports enterprise onboarding, mentors technical support staff, and creates troubleshooting documentation and automation playbooks.

Own and scale a multi-cloud data platform across AWS and Azure. Manage Apache Airflow, Kubernetes, Terraform, Helm, ArgoCD, CI/CD, observability, big data infrastructure, governance tooling, and FinOps initiatives. Provide end-to-end architectural and operational ownership, improve developer tooling, define platform roadmaps, manage incidents, enforce engineering standards, and mentor data platform engineers.

Principal Software Engineer leading architecture and implementation of resilient, low-latency distributed systems for the RunMyJobs platform. Responsibilities include technical strategy, full-stack development, AI-assisted software development, CI/CD and observability, code and design reviews, quality improvement, troubleshooting, and mentoring. The role requires expertise in Java, microservices, cloud platforms, containers, frontend technologies, databases, automated testing, and AI developer tools, with broad technical ownership but no direct people management.

Build and deliver production AI systems across machine learning, generative AI, and agentic workflows. Design scalable ML and data pipelines, integrate heterogeneous data, evaluate emerging AI frameworks, and deploy secure cloud-native solutions. Collaborate with data science, product, security operations, and threat research teams to deliver customer value. Write and review code, troubleshoot production issues, measure AI quality, document technical decisions, and mentor engineers.

Build, maintain, and improve highly automated build, release, testing, and continuous delivery infrastructure. Develop internal tools and automation, collaborate with Development, QA, and Operations, and implement AWS-based technologies to scale infrastructure and accelerate testing. Partner with internal customers to roll out projects, monitor adoption, gather feedback, and refine processes. The role requires software development experience, cloud and containerization knowledge, and cross-functional collaboration.

Architects and develops AI-powered systems, backend services, APIs, experimentation frameworks, and automation using foundational models. Integrates AI capabilities with microservices, AWS, Snowflake, and diverse technology stacks while ensuring scalability, reliability, and maintainability. Collaborates with product, data science, and engineering teams to translate business needs into technical solutions, evaluate emerging AI tools, and rapidly prototype proof-of-concept applications.

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.

Lead platform infrastructure reliability initiatives for a microservices-based cloud SaaS solution. Design scalable, automated, observable infrastructure; define platform roadmaps; guide engineering teams through design reviews; reduce operational toil; build monitoring and alerting; and participate in on-call incident response. The role uses AWS, Kubernetes on EKS, Istio, infrastructure-as-code, GitLab, Argo CD, and Datadog.

Leads the design, development, maintenance, and technical direction of a scalable insurance SaaS platform. Works across .NET back-end and Vue/React front-end technologies, optimizes performance, enforces coding and security standards, leads code reviews, resolves bugs, and mentors developers. Collaborates with product, design, and engineering teams on architecture, requirements, testing, cloud infrastructure, microservices, and continuous platform improvement.

Build enterprise Workforce Management software for forecasting, staffing, scheduling, adherence, intraday management, and operational reporting. Develop Java and Spring Boot microservices, React and TypeScript applications, REST APIs, event-driven workflows, and PostgreSQL data models. Integrate WFM with CX, ACD, HR, payroll, identity, and enterprise data platforms. Contribute to cloud-native deployments, CI/CD, testing, performance optimization, architecture, code reviews, and client-facing collaboration.

Design, develop, test, deploy, and support scalable cloud-native applications using Java, Spring Boot, React, TypeScript, Node.js, PostgreSQL, microservices, and REST APIs. Build CI/CD pipelines, containerized deployments, integrations, observability, and secure distributed systems. Collaborate with product, UX, QA, DevOps, architecture, and engineering teams while troubleshooting production issues and improving application performance, resilience, and maintainability.

Develop and close strategic mid-market and enterprise business for Build.io in the US. Own the full sales cycle, including prospecting, discovery, technical evaluation, negotiation, procurement, and closing. Build relationships with technical and executive stakeholders, manage pipeline and forecasting, drive account expansion, and help shape the company’s enterprise go-to-market strategy.

Provides technical leadership for cloud platform engineering, including cloud architecture, infrastructure automation, CI/CD, security, reliability, self-service delivery, and developer enablement. The role leads design and code reviews, mentors engineers, improves cloud services and delivery processes, and guides implementation across teams using public cloud platforms, Terraform, Kubernetes, and modern DevOps tooling.