Quality Assurance Manager Jobs

Reporting to the VP, Product for Diligent Market Intelligence, you will lead the strategy, roadmap and evolution of Stewardship Intelligence—one of DMI’s core data products. Stewardship Intelligence provides meeting , executive compensation, corporate governance and proxy-voting intelligence to institutional asset managers, stewardship and governance professionals, compensation advisers and consultants, and corporate issuers . You will lead both Product Management and Research. This is a domain-led role: substantial experience in stewardship, proxy voting, corporate governance, executive compensation, investor relations or a closely related capital- markets domain is required . You will translate customer and market needs into clear product priorities, improve how research is performed at scale, and ensure that Stewardship Intelligence remains trusted, timely and valuable to its users. Here’s a breakdown of what you’ll do Own and continuously refine the product vision, strategy, roadmap and prioritisation for the Stewardship Intelligence portfolio, covering meeting , executive compensation, corporate governance and proxy-voting intelligence. Lead, develop and organise the Product Management and Research teams, establishing clear priorities, effective ways of working (with an emphasis on AI integration where possible), strong collaboration and a culture of accountability and continuous improvement. Be responsible for improving dataset coverage, methodology , quality, traceability and timeliness, using appropriate process redesign, automation and AI-enabled approaches without compromising accuracy or trust. Partner closely with Engineering and UX to define, build and launch high-quality product experiences and Data-as-a-Service capabilities that make

A Career with Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What You’ll Do We are passionate about data. We collaborate to build elegant, effective, scalable, and highly reliable solutions to empower predictive modeling in finance. You will join a team that plays a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe. Specifically, you will: Serve as a frontline owner for thousands of mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with portfolio managers, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s Required Bachelor’s degree with a focus in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments; familiarity with Databricks is a plus. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal

JOB TITLE Data Reliability Engineer A CAREER WITH CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What you’ll do Ensure smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe Serve as a frontline owner for mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with investment professionals, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s REQUIRED Bachelor’s degree in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal skills. Commitment to the highest ethical standards About point72 Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Poin

Position Overview: The Services team has unrivalled expertise across corporate governance, audit, risk, compliance, and regulatory environments in many sectors. They have the scale and reach to deliver significant change smoothly, leveraging solution design and delivery to provide global, dynamic, flexible, and reliable outcomes with lasting results. Their vision is to partner as trusted advisors, working in joint teams that complement client strengths with the right mix of talent. A Delivery Analyst is an early‑career consultant in the Services team who supports delivery of audit, risk, and compliance solutions for clients. They assist with discovery and requirements capture by reviewing client documentation and helping lead discovery workshops to understand current processes and needs. Guided by senior advisors, they translate requirements into technical design documents, configure and iterate Diligent One prototypes, deliver enablement training, maintain issue logs, and follow the standard project methodology to deliver on time and in scope. Key Responsibilities Utilize your product and domain expertise to deliver customer requests and create a delightful customer experience. Be responsible for the timely and quality delivery of the services requested by customers. Collaborate with Customer Success Managers, Senior Managers and Managers to ensure any new service requests are handled appropriately or routed the request to the correct teams. Document and maintain the standard operating procedures for performing the customer-specific request. Consult with the global implementation teams and customer success teams to provide technical guidance to the customer to leverage more value from the product. Required Experience/Skills Ability to effectively engage customer per

Role Overview You’ll help global clients keep their most critical corporate governance data accurate, secure, and easy to use. As a Professional Services Data Entry Specialist, you turn complex client records into clean, reliable datasets and documents that board members, legal, risk, and compliance teams rely on to make decisions. In this role, you’ll work hands-on with governance data, migrate it between platforms, build smart questionnaires for directors and officers, and use Excel, databases, and AI tools to streamline how information is captured and maintained. You’ll collaborate closely with clients and internal teams, spot data issues early, and suggest better ways of working so implementations run smoothly and clients are set up for long-term success. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Migrate and transform client corporate governance data and documents into Diligent platforms, ensuring accuracy, consistency, and completeness. Build and configure Director & Officer questionnaires so clients can collect the right information from the right stakeholders. Run regular data quality checks, validate data against source records, and quickly correct errors to maintain high data integrity. Use advanced Excel functions, databases, and AI tools to manage, format, and optimize large data sets and bulk document uploads/downloads. Partner directly with client stakeholders and internal teams to clarify requirements, resolve data or technical issues, and provide clear progress updates. Identify and help implement improvements to data workflows, templates, and automation to make delivery faster, more consistent, and more scalable. These are the essentials you’ll need to get an interview Hands-on experience in a data-focused role (for example, data specialist, data analyst, data migration, or similar) in a professional environment. Strong skills in Microsoft Excel, including advanced functions for manipulating and analyzing data

Must be based in Vancouver The role We're hiring a dedicated data engineer to own the production data platform that our delivery, product, and engineering teams run on; designing integrated, governed data pipelines and delivering automated reporting, AI-assisted workflows, and predictive signals on top of them. You'll write production code, design systems, own CI/CD, and be accountable for the correctness of data that leaders make decisions on. What you'll do Design and operate our cloud data platform: ingestion, transformation, orchestration and serving. Integrate data from across the business (delivery tooling, CRM, product telemetry, finance, support and customer feedback systems) with shared identifiers, data contracts and lineage. Build automated and continuously refreshed reporting so teams manage by exception rather than chasing status. Connect approved AI agents to governed data with structured outputs, provenance, guardrails and human approval in the loop. Build feature pipelines and the MLOps controls behind predictive use cases: tests, versioning, promotion gates and drift monitoring. Own the engineering standards for data: testing, observability, environment promotion, PII classification and access control. What you'll bring Strong software engineering fundamentals: production-quality code, API and interface design, testing discipline, systems design. Real experience building and operating production data platforms on a cloud warehouse or lakehouse (Snowflake and AWS preferred) with dbt and a modern orchestrator. Practical AI tooling experience: something shipped, not prototyped. LLM-backed classification, extraction or structured-output pipelines; agent and tool-calling workflows; retrieval; evals. You can reaso

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’

Role Overview You are a senior product leader who wants to shape how AI transforms IT and cyber risk management at scale. In this role, you will own one of the most strategic product areas in a global GRC SaaS platform, defining how organisations identify, assess, and act on cyber risk — and how CISOs and boards get the clarity they need when it matters most. You will set and drive the product vision, roadmap, and outcomes for IT & Cyber Risk on a multi-solution platform used by enterprises worldwide. You will partner closely with engineering, design, data science, and senior leaders to build AI-native capabilities that automate risk detection, prioritisation, and reporting. Your work will have high executive visibility, real strategic weight, and direct impact on how customers manage governance, risk, and compliance. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the end-to-end product strategy and roadmap for IT & Cyber Risk, aligning to company objectives and broader platform direction. Design and deliver AI-powered features (LLMs, agents, ML models) that automate risk identification, assessment, and reporting for enterprise security and risk teams. Partner with engineering, data science, and design to define technical approaches, ship high-quality releases across web, mobile, and API, and iterate using product analytics. Develop deep market and customer insight by engaging regularly with CISOs, security leaders, and risk managers, and turn those insights into clear product bets. Define, track, and communicate product KPIs, AI performance metrics, and north star outcomes to senior stakeholders, including business cases for major investments. Work cross-functionally with Sales, Customer Success, Professional Services, and Marketing to ensure successful launches and adoption of new IT & Cyber Risk capabilities. These are the essentials you’ll need to get an interview 7+ years of product management experience, includi

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

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail. What You’ll Do: Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs. Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Be able, and willing, to multi-task and learn new technologies quickly What We’re Looking For: 4+ years of full-time engineering experience, post-graduation Experience scaling products at hyper growth startups Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies Proficient in Python or Javascript/Typescript, and SQL Experience with Kubernetes Experience with major cloud providers (AWS, Azure, GCP) Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences 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 fo

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

Director of Engineering, Physical AI Role Overview The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment. This role requires significant ownership in a fast-paced environment and you will motivate internal teams to set the pace for business growth. Travel will come into play. Key Responsibilities: Set and drive the technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research Lead a multidisciplinary engineering organization—spanning engineering managers, software engineers, ML engineers, and ML research scientists—while designing the organizational structure, talent strategy, and culture required to scale rapidly without compromising on quality or strategic alignment Maintain exceptional technical and operational excellence by deeply understanding team deliverables, asking incisive questions, identifying slipping standards early, and knowing precisely when to step in Drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities Collaborate with researchers and clients to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads Required Qualifications: Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field 8+ years of engineering experience in fast-paced environments, including 4+ years direct people management demonstrated history of recruiting, mentorin

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 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 are producing is some of the most important work for how humanity will interact with AI. Our Approach As part of the interview process, you’ll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale. Responsibilities: Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal Collaborate closely with internal operators (your use

Software Engineer Argentina; Uruguay Software Engineer - Robotics & Autonomous Systems Scale's Robotics business unit is dedicated to solving the data bottleneck in Physical AI across Robotics, Autonomous Vehicles, and Computer Vision. In this role, you'll be a key contributor building production systems for robotics data collection, model training pipelines, and evaluation infrastructure. You'll have the opportunity to own critical parts of our robotics platform, work directly with cutting-edge robotics and AV customers, and shape the future of embodied AI systems. You Will: Own and architect large-scale data processing pipelines for robotics and autonomous vehicle datasets Build ML training and fine-tuning pipelines using Scale's robotics data Work across backend (Python, Node.js , C++), and frontend (React, TypeScript) stacks to build end-to-end solutions Develop tools and real-time systems for robotics data collection, teleoperation, model evaluation, data curation, and data annotation Interact directly with robotics and AV stakeholders to understand their technical needs and drive product development Design comprehensive monitoring and evaluation frameworks for robotics models and data quality Solving complex, late-stage industry challenges in concurrent and real-time robotic systems, with strict attention to timing constraints and data integrity. This often involves deep investigation, reviewing academic papers, and direct collaboration with robotics vendors Collaborate with ML engineers and researchers to bring robotics research into production Deliver features at high velocity while maintaining system reliability and performance Ideally, You Have: At least 6 years of high-proficiency software engineering experience, with a strong background in complex systems and the ability to independently research, analyze, and unblock hard technical problems. Strong programming skills in Python and TypeScript/Node.js for production systems Experience with React and m

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas