Support Engineer in Toronto

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the Role At Sentry, Support is an engineering discipline. Our customers are the greatest technical minds in the world—developers at elite enterprises building the future of software—and they deserve answers that go deeper than a knowledge base link. We are architecting the Technical Support engine . We’re looking for a veteran engineer to help us redefine the standard of technical support by combining deep human expertise with autonomous agentic systems. You are a debugger of both code and systems. You will treat support volume as a data signal to build automated resolution paths, ensuring our human engineers only touch the most complex, high-impact architectural puzzles. Sentry Support Engineers aren't just clearing queues; they are Orchestrators . You will engage with our users across GitHub, Discord, and our internal systems, while acting as the Technical Lead for our Agentic Ops. You ensure that when a developer asks a complex question, our systems have the right context and a seamless "Human-in-the-Loop" path to you when deep, nuanced expertise is required. In this role you will Master the Sentry Ecosystem & Support Elite Developers Deep-Dive Debugging: Perform root-cause analysis on complex issues and distributed tracing gaps across polyglot environments. Support the Great Minds: Act as a strategic consultant for senior engineers at our largest enterprise customers, solving high-stakes architectural challenges that push the boundaries of observability. Troubleshoot SDK Implementations: Go deep into the source code of Sentry’s SDKs to help developers instrument complex frameworks and custom environments. Engin

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Role You are a deep technical architect. Whether it's a Fortune 500 CTO or a startup founder, you know how to read the room and steer it. You have handled enough OAuth token flows, SCIM failures, and multi-product integration edge cases to spot root issues fast. In this role, you will help shape how developers understand identity at scale. You serve as the top technical escalation point for our support team. You are our domain expert. You influence product roadmaps. You mentor engineers. You challenge standard practices. You raise the bar across the entire global team. You handle ambiguity well. You operate with full autonomy. You focus on delivering outcomes that unblock our most complex accounts. What You Do Strategic Escalations and Architecture This is not primarily a queue role. You will mostly engage on cases that exceed senior engineer scope, the ones that need architecture judgment, not triage. End-to-End Ownership: Resolve our most complex developer cases, including multi-product architectures, ISV integration designs, and strategic account escalations. Cross-Functional Bridge: Serve as the technical link between Developer Support and ISV Partnerships, working directly with strategic partners on integration design. Architectural Consulting: Join customer and partner calls to advise on architecture and resolve issues beyond standard support scope. Product and Executive Engagement Roadmap Influence: Partner with Product Management and Engineering

Engineering Manager, AI Conversation Platform Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The newly formed Conversation Platform team aims to build a conversation platform for all merchants who use Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include customizing the Stripe landing page to suggest bespoke integrations, allowing users to command the Stripe API in natural language, and resolving user issues automatically. We are developing RAG based systems on the latest LLMs as well as fine-tuning our own models. We’re an end-to-end team going from ideas to models to shipping in production. What you’ll do Responsibilities Driving an ambitious vision for AI/ML that benefits our users Setting the technical & process direction for the team based on business goals Brainstorm and coordinate product integrations with partner teams Proposing new ideas and building prototypes Be an integral part of a larger ML community internally & externally Hire & develop a world-class team to deliver high-quality ML systems. Coach engineers to help them grow in their careers and maintain a high bar Who you are We are looking for ML Engineering Managers who are passionate about using ML to improve products and delight customers. You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy them to production, even if it involves making substantial changes to backend code. You a

Engineering Manager, AI Conversation Platform Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The newly formed Conversation Platform team aims to build a conversation platform for all merchants who use Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include customizing the Stripe landing page to suggest bespoke integrations, allowing users to command the Stripe API in natural language, and resolving user issues automatically. We are developing RAG based systems on the latest LLMs as well as fine-tuning our own models. We’re an end-to-end team going from ideas to models to shipping in production. What you’ll do Responsibilities Driving an ambitious vision for AI/ML that benefits our users Setting the technical & process direction for the team based on business goals Brainstorm and coordinate product integrations with partner teams Proposing new ideas and building prototypes Be an integral part of a larger ML community internally & externally Hire & develop a world-class team to deliver high-quality ML systems. Coach engineers to help them grow in their careers and maintain a high bar Who you are We are looking for ML Engineering Managers who are passionate about using ML to improve products and delight customers. You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy them to production, even if it involves making substantial changes to backend code. You a

About the Role: As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi. A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine. You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams. Responsibilities: Design and build scalable, high throughput, and low latency distributed systems using Scala Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art. Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc. Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi. Your Background: Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM b

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. We're looking for a Workato/Boomi Integration Engineer to build and support enterprise automation, with a focus on Legal systems integration (CLM, e-signature, matter management, compliance). You'll work across iPaaS, APIs, and AI/agentic tooling (Workato Genie, AI Skills, MCP servers) to connect Legal and other business systems. Responsibilities: Design and build Recipes and process automations across multiple systems, including AI-powered workflows using Workato Genie and MCP servers. Build and support AI Agents (Genies) for Legal and business-process automation, including prompt design and IDP for unstructured Legal content (contracts, filings). Design and manage secure API endpoints (REST/SOAP) and SFTP connections; build ETL/data-sync pipelines across formats (JSON, XML, CSV, EDI). Deploy and manage On-Premises Agents (OPA) for secure, behind-firewall connectivity. Maintain platform environments and security (RBAC, SSO, versioning); monitor jobs and troubleshoot failures. Build employee-facing tools (Workbot/ChatOps, Workflow/AgentX Apps, Slack integrations) with human-in-the-loop steps. Integrate business applications (CRM, HR, Finance, LMS, Legal, Budget & Forecast) via Boomi, with emphasis on Legal, Financial, and Supply Chain integrations. Write and optimize SQL/PL-SQL and custom scripts (Java/Groovy/JavaScript/Python); manage code via Git/GitHub; provide production support and on-call as needed. Partner with Legal, Compliance, and IT stakeholders to gather requirements and translate them into working integrations. Experience: 6–8 years of integration/automation experience, with hands-on Workato and Boomi. 4–6 years building and managing APIs (API Gateway, OAuth/SAML/JWT) and SFTP-based file transfers. 2+ years supporting Legal systems integrations (CLM, e-signature, matter management, c

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Vanta's Core Platform team provides the foundational infrastructure that powers all engineering at Vanta. We're expanding upmarket to support enterprise customers, which requires strategic investment in platform systems that ensure security, reliability, and developer productivity at scale. As we expand upmarket to support enterprise and regulated customers, we’re investing heavily in platform capabilities that scale securely while reducing cognitive load for product teams. As the Engineering Manager, Core Platform at Vanta, you'll own the foundational infrastructure that every engineer builds on, ensuring it scales with company growth while remaining fast, simple, and reliable. This team’s ownership spans shared services infrastructure, observability and monitoring, datastore management, and async work systems. Our Engineering Managers develop and grow high-performing teams that deliver significant value to our customers and enable our business to scale. This role sits at the intersection of technical architecture and team development, with real authority to set direction and grow a world-class platform team. Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as an Engineering Manager at Vanta: Lead and grow high-performing platform engineering teams that deliver reliable, scalable infrastructure and operational excellence for Vanta’s products and customers Set technical direction and drive multi-quarter platform initiatives spanning infrastructure reliability, security, scalability, and developer experience across shared systems and services Partner closely with product engineerin

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Our Infrastructure team is passionate about building software to solve problems at massive scale. We do this often, and when we believe our solution is worth sharing with the community, such as Envoy Proxy , we open source our ideas for the benefit of others. As an Observability team member, you are responsible for the operation and maintenance of our logging and metrics infrastructure. You ensure all teams at Lyft are aware of the operational health of their products by monitoring system availability and take a holistic view of our platform performance. You build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you find opportunities to improve our systems in order to push our platform forward. You provide our partners with the support they need to help them build robust large scale distributed systems. We count on the reliability of our infrastructure to empower Lyft teams to provide our customers rich experiences that are highly available with rock solid performance to ensure our transportation platform continues to connect people and places. As we grow our team, we are seeking experienced Infrastructure Engineer to ensure that as our Infrastructure continues to scale, our platform continues to provide an essential and dependable service that transports millions of people every day. Specifically we are searching for someone who brings fresh perspectives, enjoys collaborating with cross-functional teams in order to continually improve our products and services for our customers. Responsibilities: Maintain, improve, and develop tooling and systems that enhance the reliability, scalability, and efficiency of our platform. Assist engineering teams in defining service-level objectives (SLOs) and provide the necessary toolin

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Our core corporate finance functions are critical to Lyft’s success. The health and sustainability of our applications, systems, tooling and processes are critical for daily operations and for Lyft’s ability to grow. The Oracle EPM Engineer possesses both business and technical acumen. This engineering role provides support for Lyft’s Corporate consolidations systems, managing their daily performance and incidents, creating automated workflows, building customer solutions, configuring applications, providing end user training and protecting all system related information assets. In this pivotal role, you will leverage your deep expertise in FCCS, ARCS, Data Exchange and EDMCS to drive innovation across our financial consolidation, reporting, reconciliation, and planning processes. Working at the intersection of finance, technology, and strategy, you'll collaborate with key stakeholders to architect solutions that enhance accuracy, efficiency, and compliance while positioning our organization for continued growth and adaptability in a dynamic business environment. Responsibilities: Strategic Leadership & Expertise Lead all aspects of the front-end administration of the FCCS, ARCS, Data Exchange, EDMCS systems including maintaining metadata, rules, forms, developing reports, creating locations, mappings, and granting user access. Serve as the support person and subject matter expert for FCCS, Data Exchange and ARCS configurations, setting technical standards and driving continuous improvement initiatives Strong understanding of complex EPM implementation projects from conception to completion, ensuring on-time, within-budget delivery while exceeding stakeholder expectations Advanced System Configuration & Development Design and implement sophisticated FCCS business rules, incl

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. Responsibilities: Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft Evolve data model and data schema based on business and engineering needs Implement systems tracking data quality and consistency Develop tools supporting self-service data pipeline management (ETL) SQL and MapReduce job tuning to improve data processing performance Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions Experience: Bachelor's degree in Compute

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Driver team is dedicated to fostering a platform of high-quality service by empowering drivers to perform their best. We are looking for a product-minded engineer who wants to build and improve products that sit at the center of the core driver experience. Products you drive will solve pain points that matter most to drivers by streamlining key interactions, reducing friction, and creating systems that feel intuitive, fair, and supportive. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. Responsibilities: Design and implement backend features end-to-end with clear ownership, delivering well-scoped work from technical design through to production with moderate guidance from senior engineers Write clean, reliable, well-tested code that meets team standards and holds up in code review Participate actively in code reviews, giving specific and constructive feedback while continuing to develop your own review instincts Debug and resolve issues across backend services including performance bottlenecks, reliability problems, and data integrity issues Collaborate with product managers, designers, and partner engineering teams to clarify requirements and surface technical constraints early Contribute to technical discussions and help evaluate implementation approaches for new features Write unit and integration tests for your own code and develop familiarity with the team's broader testing and observability practices Address technical debt and make incremental improvements to existing services as part of regular development work Participate in on-call rotations, respond to production incidents, and support teammates in mitigating custome

About the Team: Tubi's Internal Tools team is at the forefront of AI integration, developing everything from developer resources to production-grade AI for business operations. We are the group responsible for turning AI from an experiment into an operating capability: training, infrastructure, developer agents, and AI-powered business systems. Engineers operate with high ownership and autonomy, collaborating on shared architectural decisions and AI infrastructure. What You'll Do: Own systems end to end — design them, build them, and support them in production. Lead the projects you own: sequence the work, decide what lands first, and set technical direction for the engineers working with you. Sit with the people who use what you build, and turn what you learn there into a system. Design the service boundaries, contracts and schema evolution that let our platforms grow without breaking the teams depending on them. Make our AI systems dependable in production: evaluation harnesses, human approval steps before an agent acts, retries that handle a model returning something unexpected, and cost tracking that tells you what a task costs before you run it. Build what other engineers build on — agent skills, tool and MCP integrations, shared libraries — and raise the bar through code review, design discussion and mentoring. Spot the platform work nobody has asked for yet, make the case for it, and build it. Your Background: 5+ years of professional experience building and operating production systems, from design through production ownership. A system you designed and can walk us through end to end — where its boundaries sit, what constrained it, and what you chose against. Strong programming proficiency in a statically typed language such as Rust, Go, C++, Java, Kotlin, C#, or TypeScript. Production Rust is a plus rather than a requirement. You have owned a service in production: you wrote the runbooks, you knew what it cost, and you were the one paged when it broke. Expe

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! About the Role We are seeking a proactive, customer-focused IT Support Specialist based in Toronto to anchor our regional IT operations. In this role, you will be the primary point of contact for internal employees, delivering white-glove technical support while managing core identity, collaboration platforms, and SaaS systems. Beyond day-to-day helpdesk operations, this position bridges traditional IT support and modern systems engineering. You will leverage automation, scripting, and modern DevOps practices to streamline user lifecycles, eliminate manual toil, and ensure our workforce operates securely and efficiently. Key Responsibilities Serve as the first point of contact for internal employees, triaging incoming requests through the ticketing system and established support processes. Troubleshoot and resolve workstation, laptop, mobile, and basic network issues for on-site staff and remote employees, escalating more complex support cases to senior staff or the appropriate team. Deliver calm, clear support during high-priority incidents, keep users informed, and document work thoroughly through to resolution. Manage end-to-

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. This is a hybrid-role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a Director of Machine Learning Engineering and Infrastructure to lead a hybrid team bridging advanced ML engineering with world-class infrastructure design. In this role, you will own the strategic direction and execution for scaling our machine learning capabilities while ensuring our distributed systems and infrastructure can support innovation at massive scale. You will combine technical depth with leadership excellence to guide teams that deliver both foundational ML systems and high-performance distributed services. This is a hybrid role for our Toronto office. What You'll Do: Lead and manage high-performing teams across ML engineering and ML infrastructure, fostering a culture of innovation, collaboration, and growth. Define and execute the strategic roadmap for ML systems, including recommendation, personalization, and ads optimization. Oversee the design, development, and deployment of scalable ML pipelines: data ingestion, feature engineering, model training, evaluation, and serving. Architect distributed systems to support ML workloads at scale, ensuring reliability, observability, and operational excellence. Partner closely with Product, Engineering, and Content teams to align on business goals and deliver impactful ML-driven experiences. Support best practices in experimentation, evaluation, and ML system monitoring. Ensure cost efficiency, scalability, and performance in ML infrastructure investments. Your Background: 10+ years of industry experience spanning machine learning engineering and distributed systems. 3+ years of leadership and management experience, with a proven ability to build and lead strong t