Senior Backend Software Engineer Salary India in Canada

(Sr.) Revenue Accounting Manager Sigma Computing is seeking a Senior Revenue Manager to join our Revenue team and play a key role in managing revenue accounting and revenue operations in a fast-growing SaaS environment. Reporting to the Senior Director of Revenue, this role will own key aspects of the revenue close, revenue recognition, contract review, and related processes. The Senior Revenue Manager will serve as a subject-matter expert on revenue accounting, partnering closely with Sales, Deal Desk, Legal, FP&A, and Finance to assess complex customer arrangements, ensure appropriate revenue treatment, and build scalable processes and controls. Key Responsibilities Own key components of the monthly, quarterly, and annual revenue close, including revenue recognition, deferred revenue, unbilled revenue, and related reconciliations. Ensure compliance with ASC 606 and applicable accounting standards. Review customer contracts and non-standard arrangements to determine appropriate revenue recognition. Partner with Sales, Deal Desk, Legal, FP&A, and Finance to assess the accounting implications of new products, pricing structures, and complex deals. Review and approve revenue-related journal entries, reconciliations, and supporting schedules. Develop, maintain, and improve revenue accounting policies, procedures, and internal controls. Own accurate and timely billing operations, including review and validation of sales tax applied to customer invoices. Own sales tax compliance processes, including periodic reviews of nexus, taxability, and potential exposure across applicable jurisdictions. Support internal and external audits, including preparation of revenue-related schedules and documentation. Identify opportunities to streamline, automate, and scale revenue processes. Partner with Finance Systems and other stakeholders on revenue system enhancements and process improvements. Support the implementation and optimization of revenue-related

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. That’s where you come in. As an AI/ML Engineer, you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. What You’ll Do Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features Tackle novel UX problems at the intersection of AI, BI, and apps What You Bring Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (required) 10+ years of experience building and deploying production-grade AI/ML systems Deep knowledge of machine learning, deep learning, and applied AI Experience across the full ML lifecycle: data curation, training, deployment, monitoring A track record of building things that ship—whether it’s recommendations, search, machine translation, or something equally complex Experience adapting or training foundation models (language or multimodal) for novel domains Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You know your way around cloud infrastructure (AWS, GCP, Azure) You’ve worked in a fast-moving startup or high-growth environment Additional Job details The base salary range for this posit

Sigma is transforming how businesses allow customers to build apps, agents and dashboards on top of governed enterprise data. Hence, we are growing the design team and looking for designers who are excited to solve challenging problems, deliver impactful capabilities throughout our stack to build world-class technology. You will be part of a talented team of designers with a shared mission to make data easily accessible for all users. We're looking for a Senior Product Designer / Design Engineer who sits at the intersection of interaction design and AI engineering: someone who uses AI to ship faster, builds the skills and evals that make AI more effective, and invents new interaction paradigms for how people work alongside intelligent systems. This isn't a traditional design role. Yes you'll be using Figma, but also writing code with AI, training it, evaluating it, and questioning every assumption about what a "UI" can be when the interface itself reasons. Please note this is a 4 day on-site role in our San Francisco office. What You'll Do Start with AI, stay with AI. Use LLMs to clarify scope, draft specs, surface edge cases, and align your team before committing to a direction, use AI coding tools to build and iterate on the solution itself, and merge code to prod when fits. Prototype in code. Build working interfaces with Cursor and Claude Code, guiding structure, behavior, interaction, motion and UX quality while AI handles implementation. Partner directly with engineering to decide what moves into the product and what stays as a validated spike. Bring it to production. Fix small interaction and refinement issues directly on prod code. Design new AI interaction paradigms for conversational interfaces. Invent and validate novel patterns for how users converse with, direct, and trust AI systems - especially in data contexts where precision and confidence matter. Write evals, skills, and help on tools. Build the scaffolding that makes AI reliabl

Senior Software Engineer - Observability and Reliability About the Role We are growing the engineering team and looking for engineers who have the chops to build and deliver world-class technology. You will be part of a talented team of engineers with a shared mission to make data easily accessible. What You Will Be Doing Build observability tools and platforms, including: metrics, logging, distributed tracing, dashboarding, alerting, application performance management Build with modern tools and languages like Go, Open Telemetry and Kubernetes Participate in on-call rotation and ensure uptime of services Create runtime tools/processes that optimize cloud triaging and limit downtime Define best practices around making our systems and services measurable Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies. We expect successful candidates to be coding a majority of their time Qualifications We Need Strong Computer Science fundamentals 5+ years industry experience building and maintaining high-quality software, especially software other engineers use You apply a product mindset to infrastructure systems and feel accomplished enabling others Desire to be a great teammate and have fun at work Strong sense of craftsmanship, and a healthy academic curiosity Qualifications We Want (also, skills you’ll learn!) Experience building systems for data analytics Distributed systems monitoring and profiling skills Knowledge of cloud application security models Administered cloud service infrastructure (GCP, AWS, Azure) Startup experience Additional Job details Additional Job details The base salary range for this position is $170k - $240k annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize e

Overview We are seeking a hands-on Director of AI Software Engineering to lead and scale AI engineering efforts supporting multiple business units across Governance, Risk, and Compliance (GRC). This role sits at the intersection of product delivery, platform evolution, and applied AI—driving real-world impact across core workflows. This is not a pure management role. We are looking for a builder who leads from the front, someone who has recently written production code, shipped systems end-to-end, and can operate comfortably in ambiguity while aligning teams and stakeholders. What You’ll Do Lead AI Engineering Across GRC Own delivery of AI-powered capabilities embedded directly into business unit workflows (e.g., risk analysis, compliance automation, reporting, due diligence) Partner with product, data, and platform teams to translate business problems into scalable AI systems Stay Hands-On Contribute to architecture, code reviews, and critical path implementation Prototype and validate new approaches (LLMs, agents, retrieval systems, classification pipelines, etc.) Set engineering standards for performance, reliability, and cost efficiency Build and Scale Teams Lead and mentor a high-performing team of AI/ML and software engineers Drive hiring, coaching, and career development Establish a culture of ownership, speed, and technical excellence Drive Execution Deliver production-grade systems—not experiments Balance speed with rigor (security, privacy, compliance) Operate across multiple concurrent initiatives with clear prioritization Communicate and Influence Act as a bridge between engineering and business stakeholders Clearly articulate trade-offs, risks, and outcomes to senior leadership Align cross-functional teams around shared goals and timelines What We’re Looking For Proven Builder 10+ years in software engineering, with recent hands-on coding experience Demonstrated track record of shipping production systems at scale Experience with modern

Here's a summary of the role: Identity infrastructure is not glamourware . It doesn't get standing ovations at company all-hands. But it is the thing every product in the portfolio depends on, and when it breaks, everyone knows. If you're the kind of PM who finds that genuinely interesting, read on. This role is for someone who has lived inside SAML flows, argued over PKCE token lifetimes, and knows exactly why SSO bypass lists are a necessary compromise. You'll own the authentication platform that thousands of enterprise customers trust, and you'll shape it alongside engineers who go deep. No surface-level roadmap ownership here. Here's a breakdown of what you'll do (not all of it, just the important stuff) Own the product strategy and roadmap for core authentication flows: SAML 2.0, OIDC/OAuth 2.0 with PKCE, MFA enforcement, token lifecycle management, and multi-IdP federation. Make product decisions that sit at the intersection of system design, security architecture, and developer experience, working directly with senior engineers on protocol choices and infrastructure trade-offs. Drive adoption of platform identity capabilities across internal engineering teams through influence, moving products toward modern API patterns and away from legacy integration surfaces. Use AI coding tools (Claude Code, Cursor, or similar) to prototype ideas and validate concepts before you pitch them; this is expected, not optional. Track the IAM standards landscape, including passkeys, FIDO2, SCIM, zero-trust, and verifiable credentials, and use that knowledge to sharpen product direction. Translate complex authentication concepts (JWT structures, SAML assertions, PKCE handshakes) into clear specs, user stories, and prioritized backlogs for audiences from engineers to executives. These are the essentials you'll ne

Position Overview We are seeking a transformative Senior Director, Talent Acquisition to lead the overall recruiting function and deliver a high-impact, modern, and scalable hiring experience across the organization. In this role, the successful candidate will partner closely with senior business leaders and HR stakeholders to align hiring priorities, shape workforce plans, and support business growth through innovative, data-driven talent strategies. This leader will oversee end-to-end recruitment strategy and operations, guide team performance, and drive process improvements that strengthen hiring outcomes, scalability, speed, and quality of hire. A key focus of the role will be leading the successful implementation and optimization of Workday Recruiting and related processes, while advancing the use of AI-enabled recruiting tools, automation, talent intelligence, and analytics to improve sourcing effectiveness, decision quality, operational efficiency, and candidate experience. The ideal candidate is an AI-forward talent acquisition leader who brings strong leadership, stakeholder management, strategic thinking, and communication skills, along with deep expertise in recruiting operations, team development, talent analytics, recruiting technology, and enterprise process transformation. They will bring experience leading large-scale systems and process change, including Workday implementation or optimization, as well as a thoughtful approach to the responsible use of AI and technology across the hiring lifecycle. They will also bring a fresh and creative approach to attracting top talent and play a key role in advancing and strengthening our employer brand in the market. Key Responsibilities Lead the global Talent Acquisition function across a broad team or portfolio, with accountability for recruiting strategy, delivery, team capability, technology adoption, and performance against hiring goals. Partner closely with senior business leaders, HR

You love turning real business problems into working AI solutions — and you’re not afraid to roll up your sleeves to ship them. In this role, you’ll lead Diligent’s internal AI Solutions function , a small, high-impact team that is embedding AI and GenA I into the systems thousands of colleagues use every day across Marketing, Sales, Customer Success, Finance, HR, Legal, and Product & Engineering. You’ll set the AI vision and roadmap for internal tools, architect solutions, and still build hands-on — from prototypes and reference implementations through to production-grade integrations . You’ll own how AI shows up inside ERP, CRM, BI and core IT platforms, and you’ll be accountable for making those solutions reliable, secure, compliant, and measurably valuable for the business. If you enjoy being a “player-coach” who can move seamlessly between executive conversations and deep technical reviews, this role gives you the scope, visibility, and impact to shape how a global SaaS leader uses AI to run smarter and faster. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead, coach, and grow a high-performing team of AI Solutions Architects and Engineers, setting clear goals and building the capabilities the business needs as AI demand scales. Define and own the strategy, vision, and roadmap for internal AI solutions, translating business priorities into a focused portfolio of AI and platform initiatives. Design and deliver end-to-end AI/GenAI solutions — from ideation and prototyping through production deployment, monitoring, and continuous improvement. Embed AI capabilities (such as RAG, copilots, agents, summarization, and classification) into core business applications including ERP, CRM, BI, and other enterprise systems in a robust, maintainable way. &nbsp

Most security assurance work is reactive: a customer asks, a team scrambles, an answer goes out. This role exists to end that cycle. As a Senior Staff Analyst, you’ll own a named portfolio of our most significant customers from a security perspective, and get ahead of what they need — their regulatory environment, their audit calendar, their risk appetite, their control expectations — well enough to have the evidence ready before the request arrives. You’ll lead customer security audits hands-on, sit across from customer security teams as a peer rather than a form-filler, and build account security plans that make the next assessment predictable instead of painful. This is deliberately a hands-on senior individual contributor role. You’ll spend your time in audits, in customer conversations, and in the detail of controls and evidence — not in a management chain. If you’ve got deep SOC 2 and ISO 27001 knowledge, real technical range across cloud architecture, identity and vulnerability management, and the presence to hold a room with a sceptical CISO, this is a portfolio you can genuinely own. Here’s a breakdown of what you’ll do (not all of it, just the important stuff): Own a portfolio of strategic accounts as their dedicated security point of contact, building durable relationships with their security, risk, compliance and procurement teams. Lead customer security audits and assessments hands-on — scoping, preparing evidence, running the sessions, defending control design and driving findings to closure with internal owners. Build and maintain an account security plan for each account: their frameworks and regulators, audit and reassessment cycles, known concerns, open items and the roadmap commitments they care about. Anticipate requirements before they’re raised, tracking regulatory change, industry expectations and each account’s compliance calendar so documentation and evidence are staged in advance. Act

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

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

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. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

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

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