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We're looking for a Communications Specialist with a uniquely hybrid role combining media relations support, executive thought leadership program development, project management, and communications operations for the marketing team. This role supports how executives communicate externally - whether through press, speaking or social media - and internally, with CMO internal communications and content development. With a unique set of responsibilities supporting executive comms, internal communications for the CMO and planning for the marketing team, this role is key in how the marketing organization stays aligned, prioritized and running efficiently day to day. Straddling both the comms team and the office of the CMO, you will seek opportunities that carry the Diligent executives’ voices while also helping run the operating rhythm of the marketing team itself. You would be joining Diligent at an exciting moment in the company’s history, as they unleash their new AI-powered GRC platform to help General Counsels, Chief Compliance Officers, Audit and Risk Leaders. This is the result of nearly three years of intense development of agentic workflows inside the Diligent platform, as well as MCP/plug-in access to Diligent offerings - providing a robust, differentiated experience for clients who need solutions that accelerate and action critical business objectives, not just static reporting. This is a high-visibility role for someone who wants exposure to media relations, executive communications and marketing team operations at once. You'll work closely with the CMO, the executive team, the broader marketing leadership team, corporate communications, and the People team to make sure the right message reaches the right audience — and marketing leadership stays focused on what matters most with internal and external alignment on strategic priorities. What You'll Do Executive Thoug

You’ll shape the future of a business‑critical platform as the technical lead across both product engineering and cloud infrastructure. You’ll modernize a mature .NET application running on AWS today, while steering its evolution toward a cloud‑native, React/Node.js, AI‑enabled architecture. If you enjoy owning architecture end‑to‑end, from backend and frontend through CI/CD, DevOps, and AWS infrastructure, this role gives you real influence at Staff Engineer level and the opportunity to set engineering standards that others follow. You’ll spend your time leading complex .NET and React features, designing scalable AWS infrastructure with Infrastructure as Code, and building automation that makes releases fast, safe, and repeatable. You’ll work on performance, reliability, and modernization in equal measure—fixing what’s slowing the platform down today and designing what it will look like in the next generation. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture and development of enterprise .NET services and APIs that power a business‑critical platform. Design and operate AWS infrastructure (using AWS CDK in TypeScript) to support secure, scalable, multi‑environment deployments. Build and optimize CI/CD pipelines (AWS CodePipeline, CodeBuild, Windows build agents) to make shipping .NET and React changes fast and reliable. Drive modernization initiatives across the stack, including clean architecture, refactoring legacy components, and reducing technical debt. Design and tune PostgreSQL and MSSQL database solutions for performance, scalability, and reliability. Mentor engineers and influence engineering practices across teams, raising the bar on cloud, DevOps, and software design. These are the essentials you’ll need to get an interview Significant experience (typically 8+ years) delivering and operating scalable enterprise software, owning both application code and cloud infrastructure. Deep hands‑on expertise with C

Position Overview Diligent is looking for an experienced GRC Advisor to join the team and work on Key accounts to drive adoption and retention and identify areas for expansion within our platform. This position will leverage our GTM, and value drivers established through combining people, process, and technology. If you are anything like the talented GRC Advisors at Diligent then this feeling you have, might be the desire to serve others- but you are blinded by the limits placed on you in your current role. The Client Success Advisor role is key to Diligent’s Customer Success retention strategy. Key Responsibilities Provide guidance and best practices on configuring, customizing, and optimizing the functionality of the GRC platform and modules to align with clients’ business processes and objectives. Conduct in-depth assessments of clients’ GRC requirements, objectives, and challenges to recommend tailored solutions to address their business needs and goals. Collaborate with clients on internal roadmaps, governance, risk, and compliance requirements to be implemented within Diligent’s platform. Ensure proper understanding and adoption of the platform solutions to identify at-risk clients and help increase usage of the software and modules. Partner closely with internal Product, Customer Success, Support, and Sales teams to drive continuous improvement of the platform based on client use cases. Monitor industry trends, regulatory developments, and emerging best practices in the GRC landscape to proactively share insights and recommendations with clients from a subject matter expert perspective. Required Experience/Skills Minimum of 5-7 years of experience in a client-facing role within the legal, audit, risk, or compliance industry. Adaptive mindset and ability to drive out a meaningful path to how our customers see tangible business

You will own the roadmap for a core part of Diligent’s governance, risk and compliance SaaS platform, shaping how senior leaders and boards collaborate, communicate and make decisions in a secure, modern way. You’ll turn customer problems and market insights into simple, impactful product experiences, and work closely with engineering, design, and go ‑ to ‑ market teams to bring them to life. In this Senior Product Manager role, you’ll spend your time deeply understanding customer needs, prioritising what truly moves the needle, and defining clear success metrics for everything you ship. You’ll lead a cross ‑ functional squad, manage the product backlog, and launch features that drive engagement, adoption and measurable outcomes for our customers across the Diligent Platform. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Own and continuously refine the product roadmap for your area, using customer insight, data and market trends to prioritise what to build next. Define and drive product strategy that aligns with Diligent’s vision for modern governance, connecting your roadmap to clear business and customer outcomes. Act as the voice of the customer: run discovery, validate problems and solutions, and translate insights into clear user stories and product requirements. Lead an agile, cross ‑ functional team (engineering, UX, product marketing, sales, customer success) to design, build and launch high ‑ quality SaaS features. Set goals, KPIs and success metrics for your product, track performance and user engagement, and iterate based on what the data and customers tell you. Tackle complex product and execution challenges by breaking down ambiguous problems, navigating trade ‑ offs, and making clear, data ‑ informed decisions. These are the essentials you’

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

Here's a summary of the role: Do you love building scalable cloud platforms and solving complex engineering problems with modern technologies? As a Senior Software Engineer at Diligent, you'll design and deliver high-performing , serverless applications that power our global SaaS platform. You'll work extensively with TypeScript, Node.js, AWS, and event-driven microservices, owning services from design to deployment and production monitoring. This is an opportunity to influence technical decisions, mentor engineers, and explore how AI can transform software development and engineering productivity. If you're passionate about cloud-native architectures, distributed systems, and building software that scales to millions of users, we'd love to meet you. Here's a breakdown of what you'll do (not all of it, just the important stuff): Design and build scalable backend services and event-driven microservices using TypeScript and AWS. Develop secure APIs and integrations that power reporting, analytics, and dashboard experiences. Build and maintain serverless solutions using AWS services such as Lambda, EventBridge , SQS, and DynamoDB. Drive engineering excellence through testing, observability, automation, and production readiness practices. Contribute to infrastructure-as-code and CI/CD pipelines using AWS CDK and modern DevOps practices. Mentor engineers, participate in architecture discussions, and champion the use of AI tools to improve development efficiency. These are the essentials you'll need to get an interview: 6-8 years of professional software engineering experience. Strong experience with TypeScript, Node.js, and modern backend development patterns. Hands-on experience building cloud-native applications on AWS. Strong understanding of serverless architectures and event-driven microserv

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

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. 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 position and may be inclusive of several career levels at Scale; it will be determined du

About Scale AI 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 public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI. About Our FDE Team Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing the critical data infrastructure that powers the most advanced AI models, directly influencing how humanity interacts with AI. You will work with the world’s leading AI companies and government agencies to solve their most complex AI data-related problems. Responsibilities: Drive Impact: Directly contribute to the advancement of AI by delivering critical data solutions for leading AI innovators and

About the Role This role will serve as a key execution partner to the GenAI Customer Compliance Manager, with a strong focus on supporting GenAI delivery workflows through embedded compliance operations and Legal coordination. The GenAI Compliance Operations & Programs Associate will sit at the intersection of Delivery, Ops, and Legal, ensuring that compliance considerations are integrated early in the project lifecycle, risks are clearly identified and prioritized, and Legal is engaged with the right context at the right time. By owning execution, coordination, and delivery integration, this role frees the Customer Compliance Manager to focus on strategy, governance, and risk frameworks. The role requires strong operational ownership, comfort with ambiguity, and the ability to drive alignment across fast-moving, cross-functional teams. Key Responsibilities Compliance Review Operations & Legal Coordination Manage end-to-end compliance review workflows for GenAI projects — from early-stage intake through review, approval, launch, and verification — in close partnership with Engagement Management and Delivery. Evaluate incoming work for compliance risk signals (e.g., data sensitivity, copyright exposure, privacy concerns); triage and prioritize requests for Legal based on risk, scope, and delivery timelines. Partner with Engagement Management to translate and execute risk mitigation at both the project and customer level, gather operational input to develop and prioritize systematic compliance controls, and train/educate Ops stakeholders on common or emerging compliance risks. Ensure Legal receives clear, structured, and actionable context; coordinate reviewers across Legal and internal teams to support SLA adherence. Identify workflow friction points and contribute to improving processes, templates, and prioritization frameworks. Maintain dashboards to track throughput, bottlenecks, SLAs, and risk trends. Risk Mitigation Solutions & Monitoring Support Eng

About Scale AI At Scale AI, our mission is to accelerate the development of AI applications. For 10 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 public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI. About Our FDE Team Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing the critical data infrastructure that powers the most advanced AI models, directly influencing how humanity interacts with AI. You will work with the world’s leading AI companies and government agencies to solve their most complex AI data-related problems. Responsibilities: Drive Impact: Directly contribute to the advancement of AI by delivering critical data solutions for leading AI innovators an

Head of Enterprise GTM Strategy & Operations Reports to VP, Enterprise Sales · SF or NY Reporting to the VP of Enterprise Sales, this role owns both halves of Scale AI’s enterprise revenue engine: the strategy that determines where we play and how we win, and the operating system - people, process, and systems - that makes that strategy executable, measurable, and repeatable. On the strategy side, you set the analytical foundation for enterprise growth: segment and account prioritization, coverage and territory design, pricing and packaging inputs, and the diagnostic work that explains why the funnel behaves the way it does. On the operations side, you own the RevOps stack, forecasting, compensation design, sales enablement, and the operating cadences that convert strategy into predictable quarterly execution. The ideal candidate is equally comfortable building a segmentation model from a blank page and running a Monday morning pipeline review. You will lead an established team, with the Head of Sales Enablement and the RevOps Manager as direct reports. Your first job is to raise the ceiling on what that team delivers: sharper analysis, tighter operating rhythm, and enablement that measurably shortens ramp and lifts win rates. This is a senior, highly visible role partnering with Enterprise Sales leadership, Finance, Marketing, Product, and Solutions Engineering, with regular exposure to the executive team and board materials. STRATEGY Define which segments, industries, and accounts Scale prioritizes, and build the analytical case behind those choices Build and maintain the market sizing, segmentation, and account-tiering models that drive coverage decisions and investment trade-offs Lead hypothesis-driven analyses of the enterprise funnel - win/loss patterns, conversion drivers, deal economics, coverage gaps - and translate findings into specific changes to how we sell Partner with Finance and Product on pricing, packaging, and deal-structure strateg

Owns day-to-day deal pricing execution for Enterprise, including pricing calculations, staffing inputs, and dashboard reporting that gives Sales and Deal Desk leadership visibility into deal status, pricing, and margin. Partners with the Deal Desk Manager on customer deal structuring and on identifying ways to accelerate the deal approval process. What You’ll Do Deal Pricing Execution Manages day-to-day deal pricing calculations for Enterprise deals, including ROI modeling and EPD staffing inputs Applies existing pricing frameworks consistently across Land, Expansion, and Framework deals Partners with the Deal Desk Manager to design customer-specific deal structures for non-standard or complex deals Pricing & Deal Status Reporting Builds and maintains a pricing dashboard tracking deal status, pricing, margin, and overall deal health across the Enterprise pipeline Updates pricing and trend reporting to keep leadership current on where deals stand and how pricing is trending against targets Process Optimization Identifies bottlenecks in the deal review & approval process and proposes ways to accelerate cycle time Helps standardize and streamline recurring pricing/approval steps into repeatable, lower-friction workflows Tracks deal approval cycle time and surfaces trends to inform process improvements Cross-Functional Deal Coordination Owns deal crafting end-to-end from initial pricing/modeling through contract review, coordinating with sales management, reps, and internal stakeholders Ensures the relevant stakeholders (Accounting, Finance, EPD, Legal) review and approve deals at the appropriate stage before they progress Routes deal packages to the correct reviewers and tracks open items so deals aren't stalled waiting on sign-off Strategic & GTM Support Tackles ambiguous, open-ended questions around Scale's go-to-market motion and iterates quickly on solutions that deliver measurable results Supports Sales and Finance leadership in quarterly strategy and

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