Top AWS Jobs in Toronto

Plans and executes manual and automated testing for large enterprise systems, including functional, integration, regression, accessibility, performance, load, security, and user acceptance testing. Develops test strategies, plans, scripts, cases, data, and traceability matrices; manages defects and test plans in Azure DevOps and related tools. Integrates automation with CI/CD pipelines, validates databases and data migrations, documents quality metrics, and collaborates with technical and business teams in Agile environments.

Plans and executes manual and automated testing for large enterprise systems, including functional, integration, regression, accessibility, performance, security, and user acceptance testing. Develops test strategies, plans, scripts, cases, data, and traceability matrices; manages defects and test assets in Azure DevOps and related tools. Collaborates with developers, analysts, project managers, and security teams in Agile environments, validates databases and data migrations, integrates automation with CI/CD pipelines, and reports quality metrics and compliance results.

Develop and maintain full-stack applications and backend services using Python, TypeScript, React, and Go. Manage PostgreSQL databases, AWS infrastructure, CI/CD, observability, monitoring, and operational reliability. Design schemas, optimize queries, manage migrations, improve automation and alerting, and collaborate with engineering and threat intelligence stakeholders. Preferred experience includes FastAPI, analytical datastores, security telemetry, knowledge graphs, AI-assisted tooling, CLI/TUI development, and Agentic/MCP technologies.

Owns enterprise AI architecture across AWS, Azure, Microsoft 365, and SaaS platforms. Defines target-state architecture, standards, guardrails, and governance; aligns engineering teams and senior stakeholders; oversees AI platform capabilities, Microsoft AI surfaces, security, DevOps, data, responsible AI, and regulatory compliance. Evaluates emerging AI technologies, supports architecture governance, mentors senior architects and engineers, and ensures production systems generate model-risk and regulatory evidence.

Lead quality assurance for enterprise systems by developing test strategies, plans, scripts, and cases; executing manual, automated, functional, integration, regression, performance, accessibility, and user acceptance testing; managing defects; integrating automation with CI/CD pipelines; and collaborating with technical and business stakeholders in Agile environments. Maintain quality documentation, metrics, coverage reports, release materials, and compliance with organizational, industry, regulatory, and AODA accessibility standards.

Lead and mentor a hands-on Conversational AI engineering team building Alfie, an LLM-based SaaS assistant. Own roadmap execution, delivery, quality, observability, and team growth while partnering with product, data, and architecture leaders. Design and ship APIs, services, data models, agentic workflows, and conversational experiences using AI-native development practices. Collaborate onsite in Toronto three days per week.

Leads the design, development, testing, implementation, and support of data and AI products. Translates business requirements into technical solutions, guides data engineering designs, mentors developers, improves delivery and deployment processes, and builds automation frameworks and reusable code. Develops ETL/ELT pipelines and works with structured and unstructured data across batch and streaming environments, using cloud, big data, AI, and modern data warehousing technologies.

Develop and maintain full-stack applications and engineering solutions using Java and modern web technologies. Responsibilities include REST API development, feature implementation, unit testing, code reviews, incident management, system integration, cloud deployment, quality assurance, documentation, and production support. The role collaborates with technology partners and business stakeholders, contributes to architecture and automation improvements, manages risks, and mentors team members.

Own end-to-end product capabilities across frontend and backend systems. Build accessible React and TypeScript experiences, real-time AWS Lambda services, scalable APIs, and data-intensive platform integrations using AWS, Kubernetes, Snowflake, PostgreSQL, DuckDB, and DataFusion. Lead technical design, code reviews, architecture, testing, observability, and roadmap discussions while mentoring engineers. Use and critically review AI coding agents, maintaining accountability for production implementation and outcomes.

Develop and enhance enterprise AI agents, orchestration workflows, conversational applications, and AI-powered automation using Python, LangGraph, and LangChain. Integrate AI solutions with enterprise systems and APIs, implement planning, memory, tool-calling, observability, and monitoring capabilities, and support production-grade generative AI platforms. Collaborate with engineering teams and stakeholders on architecture, reliability, performance, and scalable AI engineering practices.

Own Braze as the technical and product subject matter expert, developing integrations, data models, pipelines, migrations, and platform strategies. Partner with CRM, Marketing, Product, and Engineering teams to deliver scalable personalized engagement solutions. Monitor performance and deliverability, support adjacent marketing platforms, and ensure security, privacy, consent, compliance, and responsible gaming requirements. Document architecture and runbooks while supporting incident response for critical marketing systems.

Designs, develops, evaluates, and deploys machine learning models and scalable data solutions for advanced analytics and omnichannel marketing. Builds ETL pipelines, feature engineering workflows, and statistical models using Python and SQL; processes large-scale datasets across cloud platforms and data warehouses; and collaborates with technical teams and clients to translate business needs into reproducible analytical solutions and recommendations.

Design, build, and maintain full stack web applications and APIs for Investment Banking and Global Markets. Implement responsive React UIs, backend services (FastAPI/Flask/Node.js), data pipelines, microservices, and real-time data handling. Integrate generative AI/LLM APIs, ensure performance, security, testing, and monitoring, and collaborate with data scientists and stakeholders to deliver scalable, production-grade solutions.

Lead end-to-end data science and machine learning initiatives, including problem formulation, data preparation, model development, evaluation, deployment, and ongoing improvement. Build production-quality Python solutions using NLP, predictive modeling, anomaly detection, forecasting, and modern AI techniques. Collaborate with Product, Engineering, QA, and stakeholders to deliver customer-facing capabilities, diagnose model and data issues, establish evaluation frameworks, and mentor other data scientists.

Own Clutch’s end-to-end data platform, including scalable warehouse architecture, ELT pipelines, data models, quality monitoring, observability, governance, and DevOps automation. Partner with analysts, data scientists, and business stakeholders to support analytics, financial services, experimentation, and decision-making. Mentor engineers, establish data standards, and make technical decisions balancing speed, cost, reliability, and maintainability.

Leads customer success planning and execution for Microsoft customers, aligning stakeholders, technology investments, and business priorities. Builds trusted-advisor relationships, orchestrates Microsoft and partner teams, drives cloud adoption and AI transformation, manages customer risks and dependencies, and ensures measurable value realization. The role also establishes governance, success metrics, and delivery rhythms while advocating for customers and improving execution effectiveness.

Design and deliver secure, scalable Java microservices for Citi’s global reference data platform. Responsibilities include shaping architecture, developing REST APIs, deploying production solutions, partnering with distributed engineering teams, promoting coding and security standards, and mentoring engineers. The role requires expertise in Java, Spring, databases, messaging, cloud platforms, testing, and build tools, with beneficial experience in NoSQL, GraphQL, frontend frameworks, integration tools, API gateways, CI/CD, and Unix/Linux scripting.

Own solution, integration, security, deployment, data-flow, and resilience architecture for a high-volume regulated workflow and case-management platform. Design API, event, file, batch, content, RPA, cloud, identity, audit, AI, and disaster-recovery patterns. Guide technology selection, threat modeling, governance, production readiness, and maintainable implementation while addressing legacy-system constraints, privacy, records management, and operational resilience.

Leads hands-on engineering for a secure workflow and case-management platform in a regulated financial-services environment. Responsibilities include technical design, coding standards, architecture implementation, workflow configuration, identity and access controls, integrations, AI/document services, testing, observability, code reviews, technical problem-solving, production support, and coaching distributed engineers. The role requires strong full-stack, cloud-native, secure-development, data, workflow, and enterprise application experience.

Designs and operates secure cloud infrastructure, infrastructure-as-code, CI/CD pipelines, identity controls, monitoring, vulnerability management, backup, disaster recovery, and production-readiness processes. The role embeds security testing and audit evidence into delivery workflows while supporting regulated workloads, incident response, release cutovers, and root-cause analysis. It partners with engineering, architecture, privacy, risk, audit, and enterprise security teams to ensure secure, resilient, and compliant platform operations.

Lead technical design and delivery of AI-enabled solutions for Citco’s Fund Services transformation program. Integrate AWS, cloud data platforms, Sigma, UiPath, Databricks, machine learning models, LLMs, and conversational AI. Establish MLOps, CI/CD, security, responsible AI, and production-readiness standards while owning solution lifecycles. Lead proofs of concept, mentor developers, oversee monitoring and support, and collaborate with technical and business stakeholders.

Designs, operates, and improves production Kubernetes platforms across cloud environments. Manages ArgoCD GitOps workflows, Terraform infrastructure, CI/CD integrations, platform reliability, observability, security controls, and developer enablement. Collaborates with application teams to onboard services, create self-service tooling and documentation, respond to incidents, and improve platform availability and performance.

Design secure, scalable solution architectures supporting technology transformation and modernization. Partner with business and technology stakeholders to translate requirements into technical designs, evaluate cloud, AI, automation, and emerging technologies, and lead proofs of concept and feasibility studies. Guide cloud-native modernization, present recommendations through governance forums, develop transition architectures, assess third-party solutions, and ensure alignment with security, data governance, architecture, and regulatory requirements.

Provides high-volume IT support for employees, managing identity and access across SaaS applications, troubleshooting authentication and integrations, supporting Mac devices through MDM, and maintaining documentation. The role also manages Jira ticket queues, assists with onboarding and offboarding, collaborates with DevOps, Security, and HR, and provides basic audiovisual support for company events. It requires strong communication, prioritization, troubleshooting, and technical documentation skills in a hybrid Toronto environment.

Designs and implements secure architectures across applications, infrastructure, cloud environments, and operations. Conducts threat modeling, risk assessments, architecture reviews, and vendor security reviews; develops security standards and controls as code; supports incident response, monitoring, and compliance with NIST, ISO 27001, SOC 2, and GDPR. Partners with engineering, product, IT, DevOps, and compliance teams while mentoring technical staff and promoting secure development practices.