Aws And Tooling Platform Lead in Canada

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. Marketplace teams are at the heart of our products and decision-making, owning everything from rider pricing to driver earnings, incentives, and efficient matching. We’re looking for passionate, driven engineers to build systems that empower our riders and drivers to have the best transportation experience possible through prediction, adaptivity, and personalization. We’re looking for someone who is excited about working in a fast-paced, innovative, and impactful environment to create reliable solutions to distributed computing, ML, and data problems. The Pricing team is a centerpiece of Lyft’s Marketplace org, determining prices for all rideshare products and supporting new initiatives. Rider Engagement develops rider-facing engagement levers and optimizes user pricing experience to drive both short term and long term business outcomes. We work with Product & Science to solve and implement complex pricing requirements, balancing the needs of riders, drivers, and the business goals. As an owner of one of the most critical flows in the company, you will work on a wide array of challenges such as latency-sensitive concurrency problems, large scale distributed systems, and experimentation. If you’re interested in playing a large part in demand / supply management and improving the Lyft customer experience, this could be a great fit for you. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience. Work closely with cross-functional teams and partner teams to develop solutions based on technology and business needs, and advance team’s goals and priorities Independently lead features from idea to positive execution and launch Unblock, support and communicate with internal partners to achieve results Write well-crafted, well-tested, readable, maintaina

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 Lyft Business Product Platform team builds the systems and experiences that power Lyft's B2B products — enabling companies, organizations, and their employees to seamlessly access Lyft's transportation network. We sit at the intersection of product and platform, owning both the customer-facing features and the underlying infrastructure that makes them reliable at scale. Our work directly impacts how businesses integrate with Lyft, how admins manage their programs, and how millions of riders get where they need to go. Responsibilities: Drive architecture and technical design for systems that are highly available, scalable, and built to last — not just for today's requirements but for where the product is heading Own features end-to-end: from shaping the technical spec and design through to production rollout and operational health Think critically about how AI capabilities can be incorporated into Lyft Business products to improve the experience for business admins and riders — and bring that perspective into roadmap and architecture conversations Make well-reasoned trade-off decisions and communicate them clearly to peers, leads, and cross-functional partners Write clean, well-tested, maintainable code and hold a high bar for the same in code reviews Partner across engineering, product, and design to align on direction and get buy-in on technical approaches Proactively engage in incident response, contributing both to resolution and to long-term reliability improvements Grow the team's technical culture through design reviews, tech talks, and mentorship Experience: 5+ years of software engineering experience, with a track record of designing and shipping production systems at scale Strong system design instincts — you can reason through distributed systems trade-offs, identify failure modes, and

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. Marketplace teams are at the heart of our products and decision-making, owning everything from rider pricing to driver earnings, incentives, and efficient matching. We’re looking for passionate, driven engineers to build systems that empower our riders and drivers to have the best transportation experience possible through prediction, adaptivity, and personalization. We’re looking for someone who is excited about working in a fast-paced, innovative, and impactful environment to create reliable solutions to distributed computing, ML, and data problems. The Pricing team is a centerpiece of Lyft’s Marketplace org, determining prices for all rideshare products and supporting new initiatives. We work with Product & Science to solve and implement complex pricing requirements, balancing the needs of riders, drivers, and the business goals. As an owner of one of the most critical flows in the company, you will work on a wide array of challenges such as latency-sensitive concurrency problems, large scale distributed systems, and experimentation. If you’re interested in playing a large part in demand / supply management and improving the Lyft customer experience, this could be a great fit for you. Responsibilities: Help define the roadmap and architecture based on technology and business needs Unblock, support, effectively communicate, and obtain buy-in across teams to achieve results Lead projects of multiple people from idea to positive execution Write clear, scalable and clear design documentation Write well-crafted, well-tested, readable, maintainable code Utilize your expertise in Python, Golang, AWS to deliver robust and scalable solutions Participate in code reviews to ensure code quality and distribute knowledge Proactively participate in resolving ongoing incidents Share your kno

About the Team The Technical Support team is responsible for ensuring that developers and enterprises can reliably build mission critical solutions using OpenAI models. We provide technical guidance, resolve complex issues and support customers in maximizing value and adoption from deploying our highly-capable models. We work closely with Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. We think from an automation-first mindset and leverage the latest in AI to scale our support operations. Join the Senior Support Engineering (SSE) team at OpenAI and help shape the future of Technical Support in the age of AI. About the Role We are looking for a Senior Support Engineer to collaborate directly with our strategic enterprise accounts and product teams, helping solve some of the most difficult problems faced by our Customers. You will be part of the best technical troubleshooting team at OpenAI, and our Customers and Engineering teams will look to you for technical guidance in addressing the most technically difficult issues in our environment. As a Senior Support Engineer, you will design and run operational processes to monitor our top strategic customers and a 24x7 response team. You’ll work closely with our Infrastructure and Engineering teams to deliver the best possible experience to customers at scale. Working directly with our most strategic Customers - You will be crucial to the success of the most innovative, disruptive, and high-scale AI solutions being built with the OpenAI API platform. The nature of this role will be low volume, high difficulty. This Toronto-based role is currently remote and is expected to transition to an in-office arrangement. In this role, you will: Be among the foremost technical and troubleshooting experts for our API platform at OpenAI. You are the last line of defense before the core Engineering team. Proactively identify and implement opportunities to scale suppor

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We’re looking for dedicated, experienced, and deeply curious individuals to help solve some of the most complex challenges faced by our customers while building the future of post-AGI support alongside us. In this role, you’ll work directly with customers through support tickets and live calls, troubleshooting high-impact issues and resolving novel, often ambiguous technical problems in one of the fastest-moving environments in technology. As AI adoption rapidly accelerates, the work you do will directly support mission-critical systems being built on OpenAI’s platform, serving as a critical line of defense for customers operating at massive scale. Beyond resolving technical issues, you’ll help define what world-class support looks like in an AGI-driven future. You’ll partner closely with Engineering, Product, and Operations to improve systems, reduce bugs, and elevate the customer experience, while leveraging automation, agents, and our own AI technology to transform how support operates at scale. This Toronto-based role is currently remote and is expected to transition to an in-office arrangement. In this role, you will: Work directly with customers to troubleshoot and resolve their most complex technical issues, including API failures, integration challenges, authentication errors, and production incidents. Providing

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

About the job Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain.We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise — we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions. As Artefact continues to grow in the US, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption. Who We Are Founded and headquartered in Paris, Artefact is a next-generation consulting firm, specializing in data, analytics & AI consulting, dedicated to transforming data into business impact across the entire value chain of organizations. We are proud to say that we help our clients grow their data and digital capabilities, and that we’re also growing in parallel. We have 2000 employees across 36 offices who are focused on accelerating digital transformation. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts are all dedicated to bringing extra value to every client. We design data-based solutions to meet our clients' specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we've acquired with our 1000+ client base around the globe. Find out more at artefact.com . What you will be doing Artefact is looking for a Senior AI & Data Scientist: a scientist who owns models end to end, from problem framing thr

This position is based in Vancouver, BC , within Diligent’s Technical Center of Excellence. We are currently hiring candidates who are based in or able to work from Vancouver . Software Engineer — Platform AI Service Levels: Software Engineer II Senior Software Engineer Staff Software Engineer Location: Vancouver Position Overview As a Software Engineer on Diligent's Platform AI team, you'll help design, build, and operate the core services that power AI-driven capabilities across Diligent's global product suite. You'll build secure, scalable, serverless services on AWS that translate AI research and models into commercial-quality, production-ready solutions — enabling customers to derive insights from their governance data. You'll work closely with AI researchers, product managers, and other engineering teams, owning your services end-to-end: architecture, implementation, deployment, and monitoring. The team operates with a strong AI-augmented engineering culture — using AI tools to accelerate coding, testing, debugging, and delivery — while applying sound judgment about when and how to apply them. Key Responsibilities Design and implement secure, scalable, fault-tolerant, high-performing solutions using AWS serverless technology — event-driven, highly observable, and built with infrastructure as code. Collaborate with AI researchers/engineers to translate AI and LLM capabilities into robust, production-grade services, and help other teams integrate them. Build and maintain the pipelines needed to deploy, monitor, and manage AI services at scale — observable, resilient, and cost-effective. Use AI-powered development tools (code assistants, test generation, architecture exploration) responsibly to accelerate delivery and improve quality, always validating outputs. Participate in architecture discussions and design reviews, and contribute to product design by understanding customer problems — especially where AI can offer a breakthrough solution. Work in

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

OUR MISSION At Redwood, we empower our customers with lights-out automation for their mission-critical business processes. ABOUT US Redwood Software is the leading orchestration platform for the autonomous enterprise, driving business transformation at the lowest total cost of ownership. Redwood empowers organizations to intelligently automate and orchestrate mission-critical business and IT processes across complex ERP, hybrid cloud, data and emerging agentic AI systems. Through its SaaS-first automation fabric—with AI embedded across the automation lifecycle—Redwood accelerates the path to autonomous operations. Backed by 30 years of experience and trusted by more than 50% of the Fortune 50, Redwood helps organizations unlock human potential to focus on innovation, growth and what’s next. CORE VALUES One Team. One Redwood Make Your Own Weather Obsess over Customer Success Work the Problem Be Curious Own the Outcome Respect Each Other YOUR IMPACT As a Senior Full Stack Software Developer, you will be responsible for leading the design, development, and delivery of scalable full-stack applications, shaping system architecture, and driving engineering excellence across Redwood’s automation and SaaS platforms. Design, develop, and implement scalable, secure, and high-performance full-stack applications using Java, JavaScript, and related technologies Architect and build backend services, APIs, and microservices with a focus on scalability, reliability, and maintainability Develop responsive, accessible, and high-quality front-end user experiences Partner with product managers and stakeholders to define technical strategy and translate business requirements into system designs Own and contribute across the full software development lifecycle, from architecture and design to deployment and optimization Establish and promote best practices in coding, testing, observability, performance optimization, and AI usage Lead architectural discussions a

About the Team Come help us build and develop tools serving hundreds of engineers internally! We’re looking for a Fullstack Software Engineer to join our Developer Insights team. About the Role Our mission is to improve the developer experience of engineers at DoorDash by building various internal products, including our internal developer portal, Developer Insights. Our success as a platform team depends on the success of the product teams we serve. Because of this, we invest in building a strong community that encourages participation and promotes best practices. You’re excited about this opportunity because you will… Introduce cutting edge technologies to our engineering organization, including tools built on LLMs Build new features for Developer Insights (using Backstage.io) Improve the developer experience for all of our engineers Work and collaborate across team boundaries. Contribute features and bug fixes to upstream open-source projects. Mentor and educate your peers. Lead the team in a technical fashion and assist in roadmap planning and measurement of existing features. Represent the team at large in OKR and engineering all-hands presentations. Context switch from frontend to backend to data depending on the need that arises. We’re excited about you because… You have at least 2 years of experience in web technologies using Typescript with React on the frontend with Java, Kotlin, Python or Go backend experience. You have a product mindset and apply that to how you would build out platform services. You love systems and software, and you're proficient in both. You’re curious and dive deep into different system architectures. You are an organized and excellent written and verbal communicator. You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Compensation The successful candidate’s starti