Production Support Engineer Cloud in Toronto

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 Agent Gateway Team The Agent Gateway team owns the identity-aware infrastructure that connects enterprise AI agents to the tools, data, and services their organizations authorize. Every call from Claude, Agentforce, Codex, and internal/homegrown agents to a resource flows through us. We enforce authorization, isolate credentials, mint the right token per target, and produce the audit trails that security teams rely on. We are early in a rapidly evolving space. The standards for agent identity (MCP, OAuth token exchange, DCR) are being built under our feet. Our roadmap includes hardening the data plane for on-premises customer deployments, extending policy semantics beyond tool-level allowlists, adding native support for Agent-to-Agent brokered delegation, and scaling to tenants with thousands of virtual MCP servers. The Senior Software Engineer Opportunity Okta is looking for a Senior Software Engineer to help build the Agent Gateway. You will own features and components across the data and control planes, turning technical designs and product requirements into reliable production systems. Working alongside staff engineers, you will implement token exchange, request routing, credential resolution, and policy evaluation as agent identity specifications evolve. This is a hands-on software development role at the intersection of product, security, and infrastructure. You will ship services that handle agentic traffic reliably and performantly at scale. Wha

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

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

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 Team : Have you ever considered what powers the intelligent features behind seamless product experiences? The GenAI team is at the forefront of enabling AI-powered security and intelligent innovation across our organization. From crafting AI powered security services, to intuitive generative AI-powered chat experiences that provide instant product support, and developing the best developer experience around authentication for generative AI and AI agents, our team is instrumental in bringing the transformative power of AI to life. We collaborate closely with the Machine Learning team and various product teams to ensure the seamless and secure delivery of AI-enhanced features that provide real value to our users. The Opportunity : As a Staff Machine Learning Engineer on the Generative AI team, you will help shape, architect, and accelerate our Generative AI strategy by contributing across the stack of model development, infrastructure, and platform services. You’ll drive design and implementation of production-ready AI/ML systems at scale: ranging from LLM-powered features to reusable components that other teams across Okta can build on. You will have the opportunity to: Architect, design, and deploy robust Machine Learning & GenAI systems, ensuring seamless integration with diverse platform services and establishing scalable LLMOps pipelines in production. Drive technical decision making while striving to hit the right balance between factors s

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

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 a Infrastructure Engineer at Lyft, you will run our Production Infrastructure by monitoring system availability and take a holistic view of our platform health. You will build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you will seek opportunities to optimize our systems in order to push our platform forward, anticipating our customers' needs in order to continually improve the platform. You will provide Lyft partner teams with operational support to help them build robust large scale distributed systems. About the Team Data Pipelines is at the heart of all critical data flowing through Lyft supporting hundreds of services that impact millions of drivers and passengers every day. Our team’s mission is to empower Lyft engineers to self-serve in building and maintaining data pipelines as needed to support products that deliver the world’s best transportation experience. We leverage a variety of technologies to store, stream and manage data making it available to our internal customers. Responsibilities: Maintain and analyze metrics from; operating systems; control planes; and applications to assist in fault detection and performance enhancement Design, develop and deploy tooling and systems that continually improve the reliability, scalability and efficiency of our platform Balance feature development speed and reliability with service-level objectives Operate and improve our Infrastructure using industry best practices and tools Participate in design and

About the role There’s a wide gap between an agent that works in a demo and one that works across millions of live transactions. Closing it is the job. You’ll embed with the teams and customers who depend on AI — risk, fraud, collections, payments, support, developer experience — and design, build, and ship agentic systems into their production environments. You’ll also help build the platform underneath: Paytm’s AI inference platform (Pi) and the agentic runtime, orchestration, and tooling that lets agents reason, plan, use tools, and run multi-step workflows safely.

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 We are a small team of AI builders in Paytm Labs. As a Staff AI Platform Engineer, you will work across inference and agentic systems. You will contribute to Paytm's AI inference platform (Pi), serving internal teams and enterprise customers - running our own coding and domain-specific models (voice, vision, risk, fintech workflows) as well as third-party models. You will also architect and build the platform that enables autonomous AI agents to operate safely and reliably in production - the runtime, orchestration, and developer tooling for agents to reason, plan, use tools, and execute complex multi-step workflows, automating both software development and business processes. You will work at the intersection of LLMs, distributed systems, and production fintech infrastructure, helping define how inference and agentic AI are built and deployed across payments, risk, fraud, collections, support, and developer experience.

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! Why this role? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for a Site Reliability Engineer to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. As a Site Reliability Engineer you will: Build self-service systems that automate managing, deploying and operating services. This includes our custom Kubernetes operators that support language model deployments. Automate environment observability and resilience. Enable all developers to troubleshoot and resolve problems. Take steps required to ensure we hit defined SLOs, including pa

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. Our ultimate goal is to be a leader in democratizing access to private and public equity markets by making those assets available on-chain and be tradable 24/7. As a Staff Software Engineer in this role, you will work on the most critical projects across Tokenization, Robinhood Chain, and the Robinhood Wallet. Most importantly, you will proactively coach and uplift other team members, drive engineering excellence, and set the highest bar for quality. This role is based in our Toronto office, with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. What you’ll do Own the technical vision and execution for Robinhood Chain, the Tokenization Engine, and the Robinhood Wallet Design, build, and operate the core services that power Robinhood Chain, the Tokenization Engine, and the Robinhood Wallet Remain deeply hands-on by writing production code, leading complex implementations, and setting the standard for engineering quality across the platform Improve

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the role The App Runtime team is building a platform that lets every Snowflake user go from an idea to a live, deployed web application (Node.js first) in minutes. We own the end-to-end experience of building and running apps, from Cortex AI-assisted development to deployment in a secure, scalable infrastructure. Apps built on the platform inherit Snowflake's security, governance, lineage, and access controls by default. See Deploy Faster with Snowflake Apps . As a Staff/Principal Engineer, you will shape the product and its architecture. It’s a high leverage role - you will lead a team to scale and harden an early-stage, public-preview product. Your decisions will have a long-lasting impact on the future of Snowflake as an app platform. This role requires a unique combination of deep hands-on expertise in scalability, performance and security, great product instincts, customer obsession and the organizational influence to drive cross-team programs. Responsibilities Own the roadmap and technical decisions to evolve the public-preview platform into a production-grade one, adding features like horizontal scaling, cost efficiency via suspend/resume, support for stacks beyond Node.js, and stronger access and data-governance controls Stay deeply hands-on by authoring specs

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. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

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 are building and maintaining a highly scalable asynchronous platform that empowers our organization to handle critical business cases. As a software engineering team, our mission is to create robust and innovative solutions that drive the success of our business and deliver unparalleled value to our customers. We adopt Infrastructure as Code practice to automate the provisioning and configuration of our resources, which helps reduce manual configuration and improve consistency. Our team culture is built on collaboration, open communication, and a supportive environment where each member's ideas are valued and contributions are recognized. We believe in the importance of fostering a positive workplace culture that inspires innovation and creativity. Responsibilities: Maintain and analyze metrics from; operating systems; control planes; and applications to assist in fault detection and performance enhancement Design, develop and deploy tooling and systems that continually improve the reliability, scalability and efficiency of our platform Balance feature development speed and reliability with service-level objectives Operate and improve our Infrastructure using industry best practices and tools Participate in design and production readiness reviews, platform management and capacity planning ceremonies with cross-functional teams Document Infrastructure operations process and insights, identify repeatable actions and ruthlessly automate repetitive tasks Participate in our teams on-call rotations, respond to incidents and support other teams mitigate customer impacting events Experience: 5+ years experience working on teams responsible for software development, automation and systems engineering Experience building large-scale infrastructure, distributed systems or networks. Knowledge with SQS,

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