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Position Overview: The Solutions Sales Director will play an instrumental role in driving revenue growth for Diligent’s solutions across existing and new accounts. This role is focused on candidates with strong expertise in entity management space , either as a practitioner (e.g., company secretary) or someone who has directly used entity management tools in a commercial or operational setting. The Solutions Sales Director is responsible for managing larger, complex accounts with longer sales cycles and driving adoption of the Diligent One Platform. This individual contributor position manages the full sales cycle, from initial prospect/customer meetings through to deal completion, while orchestrating internal expertise to deliver on and grow accounts. Providing coaching, guidance, and support to Sales stakeholders is a key element to enable team members to learn best practices. Success in this role is measured by expanding product usage in existing customers, migrating customers to the Diligent One Platform, and selling to new accounts. Key Responsibilities: Demonstrate and maintain expert-level knowledge of Diligent’s entity and subsidiary management solutions. Prospect and manage new and existing business within the designated territory, focusing on larger, complex accounts with longer sales cycles. Apply a consultative ‘solutions selling’ approach, using deep domain expertise to understand customer needs and position the Diligent One Platform effectively. Leverage industry-focused insights to create long-term competitive advantages for customers. Expand strategic customer relationships and drive growth across multiple areas of the organisation. Gather feedback from customers on needs, products, and features; collaborate with product management and marketing to drive improvements. Develop strategic account plans that generate new business and upsell opportunities, coordinating cross-functional teams to execute plans. Manage the end-to-end sales cycle using

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

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

Here’s a summary of the role: Build cloud software that matters, grow your technical depth, and use modern AI tooling to do your best work. This is a hands-on engineering role for someone who enjoys solving product problems, writing clean code, and helping services run reliably at scale. You’ll work on secure, scalable microservices and APIs using TypeScript, AWS , and modern engineering practices. You’ll be part of a collaborative product engineering team where you can own features, contribute to design discussions, support production systems, and keep growing across backend, cloud, and AI-assisted development workflows. Here’s a breakdown of what you’ll do, not all of it, just the important stuff: Design, build, test, and improve backend services and APIs using Node.js, TypeScript, and AWS . Take ownership of well-defined features from planning through release, including code quality, deployment, and production support . Work closely with product managers, designers, and other engineers to turn requirements into practical, reliable solutions. Contribute to technical design conversations, code reviews, and engineering standards that keep the team moving well. Use AI tools to speed up research, coding, debugging, testing, and documentation, while checking outputs carefully and applying sound judgment. Help keep systems secure, observable, and maintainable by improving monitoring, reliability, and day-to-day development practices. These are the essentials you’ll need to get an interview: 3 to 5 years of professional software engineering experience building production applications in an agile environment. Strong backend development skills with Node.js and TypeScript, including experience building APIs or microservices. Experience with React or Angular in a product engineering environment. Hands-on experience with

Role Overview You’re a hands-on backend engineer who enjoys owning features end to end and working on real products that customers rely on every day. In this Software Engineer II role, you’ll help build and evolve a Third Party Risk Management SaaS platform using Laravel and PHP, designing scalable APIs and services that keep performance and reliability front and center. You’ll work in a product-focused team that owns its services from architecture and implementation through deployment, monitoring, and continuous improvement. You’ll mentor junior engineers, influence technical decisions, and use modern AI-powered tools thoughtfully to ship better code faster. If you’re looking for a mid-level role with real ownership, modern tooling, and the chance to grow your impact, this is for you. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Design, build, and maintain backend features and RESTful APIs in Laravel within a modern TALL stack environment. Own well-defined stories from implementation through deployment, monitoring, and iteration, ensuring performance and reliability. Contribute to architectural discussions and technical decisions that shape the Third Party Risk Management platform. Review code, improve test coverage, and strengthen CI/CD and engineering standards across the team. Mentor Software Engineer I colleagues through code reviews, pairing, and knowledge sharing. Use AI tools (e.g. GitHub Copilot, ChatGPT) to accelerate coding, debugging, testing, and documentation—while critically validating outputs and ensuring safe, responsible use. These are the essentials you’ll need to get an interview 3–5 years of professional software engineering experience in an agile, fast-paced environment. Strong experience with PHP and Laravel, ideally within the TALL stack (Tailwind, Alpine.js, Laravel, Livewire). Solid understanding of relational databases (MySQL or MariaDB), including data modelling and query optimisation. Experience designin

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

Here’s a summary of the role: Build software that matters, take real technical ownership, and use modern AI tooling to do your best work. This is a hands-on senior engineering role for someone who enjoys solving complex product problems, shaping robust solutions, and helping teams deliver reliable services at scale. You’ll work on secure, scalable microservices and APIs using TypeScript, AWS, and modern engineering practices. You’ll play a leading role within a collaborative product engineering team, owning complex features end to end, contributing to design and architectural decisions, supporting production systems, and helping raise the bar across backend, cloud, and AI-assisted development workflows. Here’s a breakdown of what you’ll do, not all of it, just the important stuff: Own and deliver complex backend services and APIs using Node.js, TypeScript, and AWS , from technical design through release and production support. Contribute to design and architecture discussions, making pragmatic decisions that balance delivery speed, maintainability, scalability, and security. Mentor and support less experienced engineers through code reviews, pairing, technical guidance, and day-to-day collaboration. Work closely with product managers, designers, and engineers across the team to turn requirements into practical, reliable solutions. Use AI tools to accelerate coding, debugging, testing, research, and documentation, while validating outputs carefully and applying sound judgment. Strengthen service reliability, observability, and engineering quality by improving monitoring, incident response, testing, and development practices. These are the essentials you’ll need to get an interview: 5 to 8 years of professional software engineering experience delivering production systems in an agile environment. Strong backend development s

Position Overview: The Solutions Sales Director will play an instrumental role in driving revenue growth for Diligent’s solutions across existing and new accounts. This role is focused on candidates with strong expertise in entity management space , either as a practitioner (e.g., company secretary) or someone who has directly used entity management tools in a commercial or operational setting. The Solutions Sales Director is responsible for managing larger, complex accounts with longer sales cycles and driving adoption of the Diligent One Platform. This individual contributor position manages the full sales cycle, from initial prospect/customer meetings through to deal completion, while orchestrating internal expertise to deliver on and grow accounts. Providing coaching, guidance, and support to Sales stakeholders is a key element to enable team members to learn best practices. Success in this role is measured by expanding product usage in existing customers, migrating customers to the Diligent One Platform, and selling to new accounts. Key Responsibilities: Demonstrate and maintain expert-level knowledge of Diligent’s entity and subsidiary management solutions. Prospect and manage new and existing business within the designated territory, focusing on larger, complex accounts with longer sales cycles. Apply a consultative ‘solutions selling’ approach, using deep domain expertise to understand customer needs and position the Diligent One Platform effectively. Leverage industry-focused insights to create long-term competitive advantages for customers. Expand strategic customer relationships and drive growth across multiple areas of the organisation. Gather feedback from customers on needs, products, and features; collaborate with product management and marketing to drive improvements. Develop strategic account plans that generate new business and upsell opportunities, coordinating cross-functional teams to execute plans. Manage the end-to-end sales cycle using

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes: Create multi-layered guardrails around agents Optimize data retrieval for agents Orchestrate fleets of asynchronous agents Automatically alerts users to deviations in data Illustrating how an agent reached a decision As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders. You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency. Define technical strategy for agentic guardrails, explainability, and fleet orchestration. Ensure system reliability and performance across multiple security classifications and network types. Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance. Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members. Influence the long-term product strategy and technical roadmap for the Federal business unit. Consult on the architecture of AI-powered solutions for large-scale federal contracts. Ideally you will have: Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world's most important decisions. The next frontier for AI is the physical world. We're looking for an AI Product Manager to own the Robotics vertical within our Physical AI team. In this role, you'll own both the development of the data and training environments (the teleoperated demonstrations, real-world collections, simulated tasks, and annotation products that labs use to train and evaluate robot policies) and the "data as a product" strategy that powers them. You'll understand where physical AI is headed, decide what robot tasks and embodiments are worth collecting, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside robotics or physical AI research, and is able to pair that domain understanding with a sense for where current robot policies succeed and fail in real-world workflows. You'll translate that expertise into datasets, environments, and evaluation frameworks that teach robots to do real physical work, and you'll be the domain expert Scale's most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You'll Do Own the Robotics AI roadmap & data strategy: Set product direction for the robotics training stack and the data strategy behind it — what data we collect, on which hardware and embodiments, and what we source internally vs. through our marketplace. Establish a vision for where physical AI is heading, driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading physical AI labs to understand where their robot p

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

Scale AI sits at the forefront of enabling machine learning for advanced robotics systems. As an Operations Program Manager focused on data creation for robotics models, you will design and execute the solutions, tools, and processes that power high-quality training data at scale. You’ll ensure precise, timely delivery of datasets that drive perception, manipulation, and autonomous decision-making in robotic platforms. With rapid growth, new customer onboarding, and continual product innovation, we face both strategic questions and hands-on operational challenges—your contributions will be key to solving them. You will be part of a highly motivated team of operators and collaborators who will ensure steady delivery and customer satisfaction. You are relentless in driving stellar results, running pilots, tests, and experiments, then handing over new designs to a team of skilled operators. The blend of operations, process improvement, and cross-functional leadership make this a unique and exciting role that will provide an opportunity to work with multiple teams (e.g., Engineering, Marketing, Operations, Analytics, and several others) across the company and around the globe. You will: Drive some of our most critical operational processes Improve existing processes and tools globally Collaborate with stakeholders to improve processes for new and existing customers Create an effective feedback loop between the frontline, product, strategy, and customers Build, maintain, and regularly communicate detailed reporting for other leaders across the company who will use your team's data to inform their own operations and strategy Ideally you'd have: Industry experience in supply chain, finance planning, in an operational role and/or in a top tier consulting firm An undergraduate degree from a top university in an analytics heavy major (e.g., Engineering or Economics) and/or a graduate degree from a top university in Engineering, Economics, or Business Experience leading day to

At Scale, we believe that AI will dramatically improve the world, and our mission is to accelerate the development of AI. We’re looking for a Field Marketing and Events leader to continue to build and manage Scale’s robust Gen AI and Research field marketing and events program, including but not limited to Scale hosted executive events, Scale hosted practitioner events and meetups, research conferences, and our annual flagship conference, AI Leadership Summit. You will join a rapidly growing team with the opportunity to manage and execute events from start to finish, drive lead generation and pipeline growth, and plan event programming with the largest names in AI. The successful candidate will have a solid understanding of technology, model builder, and research markets, strong project management skills, a strategic mindset, ability to manage and grow a team, and a passion for AI & technology. You will: Own annual planning for all Gen AI and Research events including strategy and budget Establish event activities in line with sales goals and deal acceleration, prioritizing goals from the go-to-market leadership and business development teams on event location and audience Manage team of field marketing and events managers who will execute on planning and logistics. This role should have a player-coach mentality and ability to also execute on nuts to bolts planning for all executive dinners, meetups, happy hours, sponsored trade shows, and hosted conferences Manage contractor relationships including event production firms and outside vendors, and event budgets Align with growth marketing on marketing campaigns and marketing qualified lead (MQL) reporting Track event campaign performance, measuring ROI, results, and metrics through Salesforce and own any course correction for events that are not performing Own all aspects of Scale hosted conference, Scale AI Base Camp, including venue selection, vendor management, logistics, speaker

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