Top AWS Jobs in Toronto

Own and scale Nango’s cloud platform, including compute, networking, databases, Kubernetes, IaC, and GitOps. Lead BYOC and private-cloud deployments, improve provisioning and observability, establish SLOs and incident processes, and manage Postgres, Redis, Elasticsearch, and ClickHouse at scale. Drive infrastructure security and compliance for SOC 2, GDPR, HIPAA, and enterprise reviews while shaping product strategy and supporting a remote-first engineering team.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

Lead end-to-end database migrations from Oracle/SQL Server to PostgreSQL for Guidewire Cloud. Design migration and cutover strategies, optimize performance, build automation and tooling (bash/Python), configure replication tools (AWS DMS, GoldenGate, transactional replication), validate and reconcile data, troubleshoot across application and network layers, and drive repeatable, low‑downtime migrations while collaborating with cross-functional teams.

Le directeur ou la directrice dirigera la stratégie, la feuille de route et l’équipe de gestion de produits axées sur la croissance des vendeurs et des marchands. La personne optimisera la distribution, la découverte, la conversion et les ventes sur des plateformes de marché et d’infonuagique, établira des partenariats stratégiques et mobilisera les équipes d’ingénierie, de ventes, de marketing, de finance et de réussite client. Le rôle exige une solide expérience commerciale, du leadership produit et une expertise des écosystèmes technologiques.

Design and implement cloud infrastructure and MLOps solutions for customers using GPU cloud technologies. Advise clients, conduct proofs of concept, workshops, presentations, and training; develop infrastructure-as-code architectures and documentation; optimize ML pipeline performance and scalability; support product and technical teams with customer expertise; and assist with technical marketing events.

Lead the architecture and implementation of complex cloud-based data solutions for clients. Define strategic data roadmaps, support pre-sales engagements as a data engineering subject matter expert, conduct technical interviews, mentor architects and engineers, and establish data standards and operating procedures. The role requires extensive AWS and complex data systems experience, expertise across traditional and modern data technologies, strong documentation practices, and excellent communication.

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.

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.

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

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.

Productionize, optimize, and scale LLM and ML inference across multi-cloud and Kubernetes. Deploy GPU-based workloads, implement routing/failover for model services, reduce latency via quantization/pruning/distillation, profile and tune hardware utilization, and build observability, monitoring, and cloud-native guardrails for enterprise AI services.

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

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.

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.

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

Build responsive web applications and scalable frontend/backend services, design secure APIs and databases, implement AI-powered search and asset management features, collaborate on system architecture, and optimize performance and UX for a cloud-native DAM platform.

Lead the migration of Vanta’s compliance data platform from MongoDB to schema-aware PostgreSQL while maintaining backward compatibility and data integrity. Design high-throughput Kafka and S3 pipelines, eventual-consistency safeguards, query APIs, tenant isolation, caching, and distributed storage systems. Set architectural direction, mentor engineers, drive cross-team technical roadmaps, and improve reliability, observability, and operational practices for auditable enterprise-scale infrastructure.

Build and ship end-to-end product features across frontend and backend: design APIs, develop backend services and asynchronous pipelines, implement responsive React UIs, optimize performance and reliability, work with AWS and queueing systems (e.g., SQS), and collaborate with product and design to deliver polished, scalable workflows.

Own and build end-to-end product features across frontend and backend: design APIs, develop backend services and asynchronous pipelines, implement high-performance React UIs, optimize reliability and scalability, work with AWS and queueing systems (e.g., SQS), and collaborate with product and design to ship data-intensive workflow automation.

Build and operate Valence's shared platform primitives (auth, routing, LLM gateway, deployment, observability, SLOs) to enable safe, scalable, and compliant delivery of AI-first products. Implement CI/CD gates, progressive delivery, rollback automation, security guardrails, region-aware routing, and developer-facing templates and tooling.

Design, build, and productionize LLM-based conversational and AI systems for enterprise coaching. Integrate structured and unstructured data, prototype end-to-end services, improve model behavior and observability, and collaborate with product and engineering to deploy scalable, reliable AI-driven coaching workflows.

Design, build, and optimize Databricks-based data and ML platforms. Own ETL pipelines, Delta Lake lakehouse, MLflow model lifecycle, MLOps, cluster optimization, RAG/LLM solutions, BI integration, and data governance with Unity Catalog.

Design, develop, and maintain backend microservices for reporting, analytics, data export and data-driven features. Collaborate with product, data, and engineering teams, implement APIs for BI tools, ensure data quality/governance, participate in design reviews, mentor junior engineers, and support agile delivery.