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Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

Overview: Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production

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 transport network serves the needs of millions of people every day who want to get from one place to another using Lyft cars, bikes and scooters, with public transportation, or on foot in the most efficient way. To serve these needs, we need to suggest the fastest, most affordable and safest routes. We achieve this by processing millions of rides, taking into account the latest traffic information and analyzing the preferences of drivers. To strengthen our efforts, we are hiring a Software Engineer who will work on improving our routing engine, on building cloud-based services that can process millions of route requests per day and on creating workflows to process and analyze the data collected from our rides. For this we are looking for someone who has a strong background in software architecture and algorithms and understands at the same time how to build efficient data processing pipelines. Our technology stack is based on the latest technologies such as AWS, Kubernetes, Apache Airflow, Flink, and Kafka. We use AI and machine learning to improve development productivity, optimize customer support workflows, and enhance operational efficiency — all without compromising code quality or security. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that delight millions of passengers and drivers. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best routing experience possible Build and deploy mission critical algorithms and services that can serve millions of requests per day (backend and data-streaming services written in C++, Go, and Python) Analyze rides, understand customer pain points, prioritize and size feature requests and help design solutions based on o

Product Owner OUR MISSION At Redwood Software we unleash human potential. We empower our customers with lights-out automation for their mission-critical business processes. Redwood Software is the leader in full stack automation for mission-critical business processes. With the first SaaS-based composable automation platform specifically built for ERP, we believe in the transformative power of automation. Our unparalleled solutions empower organizations to orchestrate, manage and monitor their workflows across any application, service or server – in the cloud or on premise – with confidence and control. 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 In the role of Product Owner for the Internal Product line, you will be responsible for driving development of internal tools, working closely with Product Leader, Consultants, Field Teams, Engineering, and QA. We subscribe to the philosophy that Product Managers and Product Owners are effectively CEOs of their product and drive growth and success of the product with the help of engineering, design, marketing, sales etc. The following attributes are key to excel in this role: Thrive in Ambiguity : POs carve the path and change it early and often as they collect more signals, while separating the noise. Strong Leadership: POs drive the day to day processes in managing the roadmap, driving the daily scrum rituals, and driving features/capabilities to on-time delivery. Strong Execution: This entails leading teams that work with you with fast-paced execution, using user research and business objectives to inform decisions, learning from new information and adjusting accordingly, communicating and managing relationships with stakeholders – both internal (your direct team) and external (senior leaders across the company, for example). Key Responsibilities Help PM leaders define the long term

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director, Customer Success Role Summary The Director of Customer Success is responsible for the health, retention, growth, and overall success of a portfolio of strategic customer relationships. This leader oversees a team of Customer Success Managers and serves as the operational and commercial leader for their segment, ensuring customers realize measurable value while protecting and expanding revenue. The Director partners closely with Sales, Product, TAMs, Specialist Business Leaders, Operations, and Support to drive customer outcomes, manage risk, and identify growth opportunities. Key Responsibilities Customer Retention and Growth Own renewal, retention, and expansion performance across assigned accounts. Ensure customers achieve measurable business outcomes and realize value from Mastercard solutions. Identify churn risks early and lead mitigation strategies. Partner with Sales to drive expansion opportunities and support commercial negotiations. Maintain accurate forecasts for renewals, risks, and growth opportunities. Strategic Customer Leadership Oversee a portfolio of high-value customer relationships through direct engagement and team leadership. Act as an executive sponsor for strategic accounts. Guide Executive Business Reviews and customer success planning

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

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. 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 with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation 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 and research 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: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/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,

OUR MISSION At Redwood, we empower our customers with lights-out automation for their mission-critical business processes. ABOUT US Redwood Software is the leader in full stack automation fabric solutions for mission-critical business processes. With the first SaaS-based composable automation platform specifically built for ERP, we believe in the transformative power of automation. Our unparalleled solutions empower you to orchestrate, manage and monitor your workflows across any application, service or server — in the cloud or on premises — with confidence and control. Redwood’s global team of automation experts and customer success engineers provide solutions and world-class support designed to give you the freedom and time to imagine and define your future. Get out of the weeds and see the forest, with Redwood Software. 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 HR Manager for our Canada Center of Excellence, you will be the core People Lead for our growing Engineering team in Canada, building a vibrant, high-performing culture from the ground up. You will serve as a strategic HR partner with deep expertise in employee relations, talent development, leadership coaching, and Canadian employment standards. Using people data, AI, and automation, you will help leaders make informed talent decisions, streamline People practices, and connect local execution with Redwood’s global talent strategy. Partner closely with R&D and Engineering leaders to align talent strategies with technical roadmaps, product goals, and organizational priorities. Coach technical managers, from first-time managers through VPs, on difficult conversations, performance management, team dynamics, and building high-performing technical teams. Champion a culture of “AI First,” helping Engineering leaders use automated tools and digital enablement to improve team workflows. Us

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Softare Engineer II to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. You're excited about this opportunity because you will… Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because… 3+ years of professional experience working in data engineering, business intelligence, or a similar role 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 Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS

About the Team The Storage organization builds and operates the online stateful systems and abstractions that DoorDash Engineering depends on: reliable, efficient, secure, and easy to use. Within Storage, the Distributed Caching team owns every caching offering at DoorDash end to end, including ElastiCache (Redis/Valkey), Boulder (our KVRocks-based key-value store for high-QPS feature serving), Entity Cache (read Bill Shen’s engineering blog post, “ High-Performance Proxy Cache for DoorDash Services ”), and the Distributed Lock Service, plus the smart clients (asgard-redis, valkey-go) that sit in front of them. These systems back critical product surfaces across DoorDash, Wolt, and Deliveroo: the team runs roughly 400 ElastiCache clusters serving hundreds of millions of GET requests per second in aggregate, and Boulder, our offline-to-online feature store, serves billions of feature lookups per second at peak. About the Role The team owns provisioning of clusters and the smart clients that sit in front of them, baking in sensible defaults so that other engineering teams get a turnkey caching solution instead of having to run their own. You'll help drive Boulder's evolution to scale further, improve cost efficiency, enhance performance, and support real-time updates; re-platform the Distributed Lock Service onto a strongly consistent backend; and build the self-serve tooling and recommendation engine that let customers describe a workload (QPS, TTL, payload size, latency profile) and get the right backend without talking to a human. You'll go deep on cache invalidation, replication, sharding, compaction, and failover, while shipping the guardrails, automation, and observability that keep this scale operable by a small team. You must be located in San Francisco, Seattle, or the New York Metro Area for this hybrid position. You will report to the Engineering Manager on the Distributed Caching team within the Storage organization. You’re excited about this opportunity b

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Software Engineer on Spark Platform, you will execute across the surfaces of our in-house Spark deployment that serves the entire company. The work spans Spark runtime upgrades and performance, multi-tenant scheduling and executor bin-packing on Kubernetes, cluster lifecycle automation, and the observability and incident automation that keep the platform sustainable. You will move between layers as the work demands — picking up the next high-leverage problem regardless of where it sits — and partner closely with the rest of the team and with platform consumers across the company. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Build and operate an in-house Spark platform that runs at company-wide scale, spanning runtime, scheduler, reliability, and user-facing tooling. Drive multi-tenant scheduling, executor bin-packing, and cost-aware placement that let a small team serve dozens of consumer teams. Own pieces of cluster lifecycle automation — provisioning, upgrades, capacity changes, and node-failure handling — at a scale where these stop being manual events. Build the observability and incident automation that make the platform debuggable end-to-end and keep on-call sus

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing data structures and data warehouse architecture, this team serves as the foundation for decision-making at DoorDash. The focus extends to enhancing the developer experience by creating tools that support the organization's high-velocity demands. To lead the growing team of Data engineers we are looking for managers who are passionate about Data and are thought leaders in coaching, guiding and leading teams to make Data a winning edge for DoorDash. About the Role DoorDash is looking for a Data Engineering Manager to guide the development of enterprise-scale data solutions. This manager will also act as a technical expert on all things related to data architecture to empower the greater community of data engineers, data scientists, and DoorDash partners. Your focus extends to fostering an engineering culture of excellence, empowering engineers to deliver reliable, flexible solutions at scale. Additionally, you'll play a pivotal role in building and nurturing a top-performing team, driving innovation and success in a dynamic, fast-paced environment. You must be located in San Francisco, CA, Sunnyvale, CA, or Seattle, WA for this hybrid position. You’re excited about this opportunity because you will… You are a people leader. You thrive in hiring, building, growing and nurturing impactful business focused data teams You are a technology leader. You drive the technical and strategic vision for the embedded pods and foundational enablers to meet current and future needs for scale and interoperability You strive for continuous improvement of data architecture and development process You think of quick wins

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Senior Data Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. This is a hybrid position and you must be located in Sunnyvale, San Francisco, or Seattle. You're excited about this opportunity because you will... Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because... 5+ years of professional experience 3+ years experience working in data engineering, business intelligence, or a similar role Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms Excellent communication skills and experience working with technical and non-tec

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. Lyft is looking for a seasoned Sr. Manager, Accounts Payable, tto join our Controllership organization. In this high-impact leadership role, you will own Lyft’s end-to-end AP, which includes the T&E and corporate card programs. The role spans domestic and international operations—and serves as a key strategic and operational leader overseeing how the company pays its corporate suppliers, manages vendor relationships, and scales its procure-to-pay processes. You will lead a team of managers and individual contributors located across multiple locations, and partner closely with Finance, Procurement, Treasury, Legal, Tax, and the broader business to ensure operational and compliance excellence at scale. This role is uniquely positioned at the intersection of operational rigor, global expansion, and financial transformation—making it ideal for a leader who thrives on building world-class teams, deploying automation intelligently, and delivering best-in-class supplier experiences. Responsibilities: Team Leadership & Development Lead, mentor, and develop a multi-layered team of AP managers and staff distributed across the multiple locations, fostering a culture of accountability, continuous improvement, and growth. Set clear performance expectations, provide regular coaching and feedback, and support career development pathways for all direct and indirect reports. Build organizational capacity by identifying skill gaps, championing training initiatives, and creating succession plans for critical roles. Model Lyft’s values and leadership principles, cultivating a high-trust, inclusive, and results-oriented team environment. AP and T&E Operations & Procure-to-Pay Collaborate with business partners on the full end-to-end procure-to-pay cycle including Global Supply Management and Procurement O

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 Rider Loyalty team is where riders become members. We build the membership, rewards, and benefits products that give people a reason to choose Lyft on every trip, and we make sure the value a rider has earned shows up at the moment it matters. Loyalty sits inside the Rider Loyalty, Partnerships, and Rider Pay (PLP) group. You will lead a team of engineers across iOS, Android, and Server. You will own the membership and rewards platform end to end and work daily with Product, Design, Data Science, and Partnerships. Responsibilities: Own the Loyalty roadmap from strategy through delivery. Turn goals like member growth and retention into an engineering plan, and manage the dependencies that run through Partnerships and Rider Pay. Build and scale the systems behind membership, rewards earning and redemption, and benefit delivery. Hold a high technical bar through architecture reviews, tech debt management, observability, reliability, and on-call. Grow engineers by matching people to the right opportunities, setting clear expectations, and giving feedback early. Experience: 5+ years building software professionally, including 2+ years directly managing engineers. You have managed a team that shipped both mobile and backend work, and you can still read and review code in at least one of those areas. You have owned a consumer product used by millions of people each month. You use AI tools in your own work and have a clear view of where they help and where they do not. BS/MS in Computer Science, Computer Engineering, or a related field, or equivalent practical experience. Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Child care and pet benefits Access to a Lyft funded Health Care Savings Accou