Engineering Manager Platform Migration Services Auth0 Salary India in Canada

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Operations at Brex Operations is the backbone of Brex’s mission to power businesses through our Intelligent Finance Platform. We own credit, fraud, money movement, and payments, protecting our customers and our company. From product operations that ensure flawless launches to scalable systems that drive innovation and precision, we operate at the intersection of product, design, engineering, and customer success. If you want to work at the heart of the business, Operations is where you belong. Where you’ll work This role will be based in our Vancouver office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week - Monday, Wednesday, and Thursday. As a perk, we also have up to four weeks per year of fully remote work! What you’ll do As a Fraud Operations Associate,

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Finance at Brex The Finance team is a strategic engine at Brex. We lead planning, forecasting, capital allocation, and ROI analysis — partnering across the business to drive clarity and unlock opportunity. We partner across teams at Brex to ensure our business is building and planning with the same dream big goals throughout our entire organization. We’re not here to report on outcomes; we shape them. If you want to influence company direction and think long-term about value creation, this is where your ownership starts. Cross-functional alignment: We work on complex problems that cut across Engineering, Product, Design, Sales, Marketing, Revenue Operations, CX, and more. This requires the ability to generate buy-in from a wide set of stakeholders on key initiatives Business intelligence: We are a data-driven organization that always provides data to support our decision-making. When data is not available, we find it in market a

About the role AI and coding agents have made building enterprise apps nearly effortless and exposed a massive gap in the infrastructure to run them. Sigma is emerging as the AI Runtime Environment that makes enterprise AI actually work, and this role will tell that story to the market, why it matters, and help define and create this new category. As Director of Product Marketing for AI, you will own the positioning and go-to-market strategy for Sigma's overall AI narrative and its specific capabilities, including: natural language exploration, agentic workflows, and AI-powered application building (both internal and using external coding agents). This is a high-visibility, high-impact role that sits at the intersection of product, sales, and the market. You'll translate a rapidly evolving AI roadmap into sharp, differentiated messaging that resonates with data teams, business leaders, and the enterprise IT buyers who evaluate and approve AI investments. You will be a key voice in helping Sigma win the category. What you'll do Define and own Sigma's AI product positioning and messaging from core value propositions to competitive differentiation and persona-specific narratives. Partner with Product and Engineering to understand and influence Sigma's AI capabilities and roadmap. Lead product launches for AI features and capabilities, coordinating across marketing, sales, customer success, and partnerships. Partner with sales leadership and frontline reps to understand AI deal dynamics, competitive objections, and messaging gaps and incorporate learnings into improved positioning, content, and enablement. Partner with the Enablement team, build and maintain sales enablement materials pitch decks, battlecards, demos, objection-handling guides that help the field win competitive AI deals. Develop thought leadership content and market education programs that shape how the industry thinks about building with AI on enterprise data. Conduct ongoing

Platform administration isn't the part of the product anyone screenshots for a demo. Nobody's writing a blog post about your identity provisioning flow. But it's the thing every other team at Diligent quietly depends on more than any other dev team in the company and when it breaks, everyone notices immediately. If that kind of quiet, high-stakes ownership sounds appealing rather than thankless, keep reading. This role is for someone who wants real skin in the game: you build it, you ship it, you support it. We're a high-initiative team that improves things we see first and asks permission later, building secure, event-driven microservices in TypeScript on AWS, and treating infrastructure as code the same way we treat application code: with rigor, not as an afterthought. Here's a breakdown of what you'll do (not all of it, just the important stuff) Design and build secure, scalable full-stack services using AWS serverless tech (Lambda, SQS, API Gateway) — with real attention to event-driven patterns and observability, not just "does it work on my machine." Own your services in production. That means building good observability, keeping an eye on alerts, and responding to them before they become bigger problems. Build infrastructure as code with AWS CDK and push for CI/CD that ships safely and often — not "big bang" releases you have to pray over. Design RESTful APIs other teams will actually want to consume: clear contracts, sane versioning, no surprises. Write tests — unit, integration, end-to-end — as part of how you build, not a chore you do after. Show up to architecture discussions with opinions and documentation, not just vibes. Use AI tools to move faster on coding, debugging, testing, and research — but you're still the one who validates the output. These are the essentials you'll need to get an interview 2-3 years of professional software engineering experience in an agile, full-stack-focused environment. Solid full-stack fundamentals: request lifecycles, d

Position Overview: As a Software Engineer II at Diligent, you’ll take on a hands-on technical role in building secure, scalable, and high-performing serverless microservices using TypeScript on AWS. You’ll contribute meaningfully to our mission of making governance effortless for our customers, working in a team of passionate and talented individuals that owns its services end to end—from architecture and implementation to monitoring and continuous improvements. This role is ideal for a mid-level engineer who writes solid code and embraces AI-powered tools to work smarter and faster. You’ll help shape architectural discussions, and scale modern development practices, including responsible use of AI in workflows. Key Responsibilities Design and implement secure, scalable, high-performing, yet simple solutions using AWS Serverless technology. These solutions should strive to be event-driven, highly observable, with infrastructure as code, and tightly leveraging AWS’s ecosystem of services. Optimize your development and delivery experience in order to maximize your team’s productivity and deploy continuously to production. Work in a collaborative environment where you regularly pair, plan, and execute tasks as a team and maintain a healthy development flow by adhering to Agile processes and driving iterative enhancements. Use AI tools to accelerate coding, debugging, testing, research, and code reviews, always validating outputs and applying judgment. Required Experience/Skills 3–5 years of professional software engineering experience in an agile, fast-paced environment. AI Tooling & Practices: Uses AI to boost productivity, skilled in prompt engineering, and evaluates AI outputs responsibly (bias, cost, ethics). Familiar with core AI concepts (tokens, context length, embeddings, hallucinations), understands high-level LLM behavior, and recognizes safe vs. unsafe use cases (privacy, security, fairness). Cloud & infrastructure basics: Hands-on with AWS ser

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

Come join our legal team to work on the most exciting legal, policy, and operational issues at the leading edge of AI. We're seeking strong product lawyers with specialized expertise in intellectual property law. As product counsel, you will advise on all legal aspects of product development, launch, and operations - including regulatory compliance, user terms, and risk management - while bringing deep expertise in your specialized legal area. The ideal candidate will have deep subject matter expertise in intellectual property law, a technology background, and a demonstrable history of providing practical product counsel to solve complex, time-sensitive problems in close partnership with cross-functional teams. This role reoprts to the Associate General Counsel, IP & Product. You will: Strategic Product Advice: Lead IP strategy for product development, embedding IP protection into the full product lifecycle from conception to commercialization, while also advising on related product and regulatory matters in collaboration with the broader legal team. Cross-Functional Collaboration: Partner with Research, Product, Engineering, Operations, Communications, and Marketing teams to mitigate IP risks in product development, data licensing, and open-source governance. IP Counsel: Support management of Scale's worldwide IP portfolio including patents and trademarks; assist with patent prosecution and trademark registration and enforcement. Risk Mitigation: Advise on third-party, synthetic, and open-source data and models, ensuring compliance with licensing requirements; design open-source governance policies. Agreements: Support drafting and negotiation of commercial agreement provisions involving intellectual property. Specialized Expertise: Provide counsel on machine learning, robotics, and other technical areas, with ability to engage effectively with technical teams on complex engineering and product issues. Training: Develop and deliver IP and data licensing trainin

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is building the next generation of AI and RISC-V compute. As a Sr. Staff NPI Global Supply Planner, you will own end-to-end demand, materials, and production planning across our AI hardware product lines, including Blackhole, Galaxy, and future platforms. You will translate engineering release schedules, BOM structures, and production forecasts into executable supply and capacity plans with our contract manufacturers, while keeping planning data accurate and reliable across ERP and PLM systems. This role is hybrid, based out of Toronto, ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A strategic, detail-oriented supply chain planner who can turn engineering and program ambiguity into clear, executable plans. Experienced in NPI planning within semiconductor, AI hardware, or high-tech manufacturing environments. Comfortable working across BOM structures, engineering change processes, ERP and PLM systems, and system-of-record data. A clear, collaborative communicator who can align engineering, operations, planning teams, and contract manufacturers. What We Need Lead end-to-end materials and production planning across NPI r

About the Team At DoorDash, design means making experiences for the people who order, the people who prepare, and the people who deliver. As a Designer at DoorDash, you want to build things that matter to real people. You're at your best when you can move from idea to shipped product quickly, bringing experiences to life that reach and influence users at massive scale. You'll care about whether the product you make solved a real problem for real people, or changed how someone experiences their day. About the Role In this role, you’ll join the Core Dasher team within our Dasher organization, focused on one of DoorDash’s highest-priority challenges: growing and retaining Dasher supply. The team works across Growth and Financial Products to identify new ways to create value for Dashers, including exploring how Crimson, financial incentives, and financial wellness offerings can become meaningful growth levers. You’ll help lead 0→1 opportunities from strategy through launch, partnering across Product, Engineering, Data Science, Marketing, and Finance to build experiences that can scale across the U.S. and international markets. You will report to the Head of the Core Dasher team within our Dasher organization. We operate in a hybrid model, with 1–2 days per week in one of our Design Hubs in San Francisco or New York City. You’re excited about this opportunity because you will… Define projects with a clear point of view on what to build, writing briefs that synthesize business and customer inputs into roadmap milestones; balance customer needs, business goals, and feasibility to shape what your team builds and why Bring clarity to ambiguous, cross-team problems and turn them into actionable work that ships; drive prioritization across your team and adjacent teams, making tradeoffs between design quality, speed, and impact so the highest-leverage work moves first Shape key projects from concept through execution — staying close enough to resolve issues during iteration, gu