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Quality Assurance Manager Jobs

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Explore current quality assurance manager jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Sentry
📍 San Francisco• Full-time• Remote
27 days ago

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Sentry's issue platform processes billions of events every day to help millions of developers find and fix bugs. The hard part is deciding which events point to a problem, which belong together, and what a developer needs to know to investigate. As a Senior Software Engineer on the Issue Detection team, you'll design, build, and operate the systems that make those decisions. You'll work on real-time processing pipelines, monitors, and analysis systems that detect problems and turn them into issues. The work combines distributed systems with product engineering. Choices about detection accuracy and processing latency affect which problems developers see and how soon they can act. You'll help shape how developers monitor their applications and how Sentry groups related events into issues. You'll also build the context developers and AI agents need to investigate what went wrong. Keeping these systems reliable and fast as Sentry grows is part of the job, alongside making the issues they produce more useful. In this role you will Build and scale features on a product surface handling billions of events daily, where both query latency and correctness are immediately visible to users. Own the design and delivery of substantial projects end to end, scoping alongside product and design, making the technical calls within your scope, shipping, and instrumenting what you ship so the team can measure it. You will contribute to meaningful technical product decisions : grouping quality, search performance, migrations and backfills against enormous datasets, and making the surface work well for both humans and agents. Champi

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OpenAI
📍 New York• Full-time• Remote
1mo ago

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or c

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OpenAI
📍 San Francisco• Full-time• Remote
1mo ago

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

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OpenAI
📍 San Francisco• Full-time• Remote
1mo ago

About the Team OpenAI is building the next generation of advertising for an AI-powered world. As AI changes how people discover information, explore possibilities, and make decisions, we believe this presents a huge opportunity for small and medium-sized businesses to connect with customers in new ways. The SMB Ads Marketing team is building this opportunity from the ground up. We define how businesses discover OpenAI’s advertising platform, become successful advertisers, and grow their investment over time. Working closely with Product, Ads Engineering, Data Science, and Sales, we combine customer insight, rigorous experimentation, and fast execution to turn early opportunities into scalable growth. About the Role We are hiring a Lead, Ads Prospecting & Growth Intelligence to build the intelligence and orchestration platform powering OpenAI’s ads business. This person will help us identify the right companies and people, understand why they are relevant, determine the right next action, and learn from what happens afterward. Own the prospecting function for the ads business, serving SMB Ads while building a foundation reusable across segments. Set the vision, operating model, roadmap, platform choices, business rules, adoption, and outcomes; and partner with Ads Engineering, Data Science, and internal platform teams. Decide what to build in-house, enable through internal platforms, or deliver through selected vendors and partners. In This Role, You Will Lead the function’s strategy, roadmap, operating model, and adoption. Connect platform investments to measurable advertiser and business outcomes. Define a unified prospect, account, contact, and advertiser data model. Establish standards for identity, data quality, provenance, freshness, confidence, and consent. Combine market, intent, behavioral, product, CRM, campaign, and customer-success signals to improve targeting and customer engagement. Design enrichment and verification workflows. Evaluate in-house cap

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OpenAI
📍 Seattle• Full-time• Remote
1mo ago

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or co

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Pinecone
📍 New York• Full-time
1mo ago

About Pinecone: Pinecone is the trusted AI knowledge company. Its trusted AI knowledge platform—including its Database, Nexus, and Marketplace products—power accurate, fast, and cost-effective AI applications for more than 10,000 customers and 1M developers worldwide. Pinecone's mission is to make AI knowledgeable. For more information, visit pinecone.io . About the Team/Role: This is intended to be an entry level role for new grads/early career professionals. As an Associate Field Engineer, you'll work amongst our Customer Success and Solutions Engineering teams, building deep technical expertise and tooling to directly impact the core product and customer experience. You'll engage with technical stakeholders across the customer lifecycle, from helping prospects understand how Pinecone fits their architecture to guiding existing customers through implementation, optimization, and expansion. You'll collaborate closely with Sales, Product, and Engineering to scope solutions, troubleshoot complex issues, and surface customer insights that shape our product direction. Technical fluency, strong communication, intellectual curiosity, and an AI-first mindset are essential for this role. Responsibilities: Serve as a technical point of contact for customers across their journey from evaluation to production, ensuring best practices and accelerating time-to-value. Deeply understand customer architectures, use cases, and requirements to influence our roadmap and devise solutions that unblock and advance their goals. Build resources to monitor customer health, proactively identifying opportunities to address risk and drive expansion. Troubleshoot issues and deliver high-quality technical support, developing a strong command of Pinecone's product and the broader AI/ML ecosystem. Build processes and capture knowledge to scale and automate support, success, and outreach initiatives. Partner with Sales on technical discovery, deliver product demonstrations, and contribute to proof

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1mo ago

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

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Lyft
📍 Toronto• Full-time• From C$46/hr
1mo ago

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. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

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Baseten
📍 San Francisco• Full-time• Remote
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. ABOUT THE ROLE This role owns Baseten's relationships and market intelligence across the hardware and chip layer of the compute stack: NVIDIA directly and key OEM partners such as Dell, Lenovo, Pegatron, and Supermicro. As Baseten's compute strategy increasingly depends on hardware access and terms, this role is central to keeping Baseten ahead of the market. WHAT YOU'LL DO Build and maintain relationships across NVIDIA and key OEM partners (e.g. Dell, Supermicro) Track market intelligence on hardware availability, roadmaps, and terms to keep Baseten informed and strategically well-positioned Support deal structuring and negotiation in partnership with Baseten's deal-making function Work closely with Infrastructure and Hardware Platform engineering teams to ensure consistent, high-quality provider relationships and engineering partnerships Represent Baseten credibly across senior relationships in the hardware ecosystem, escalating to company leadership when strategically valuable WHAT WE'RE LOOKING FOR Existing relationships and credibility within the NVIDIA, OEM, and HPC ecosystem Strong relationship-management instincts, with the judgment to know when to bring in senior leadership for maximum impact Comfort operating in a fast-moving, high-stakes market where hardware access can be a major competitive differentiator Collaborative style — this role depends on close coordination with engineering counterparts, not just ex

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Plaid
📍 San Francisco• Full-time• Remote
1mo ago

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. About the Team At Embedded Insights, we find the best machine learning opportunities for external products and internal systems, and collaborate with cross-functional partners to bring them to life. We are a central team of Machine Learning Engineers and Data Scientists. We embed with partner teams to build and apply machine learning models that improve internal decision-making and power the Plaid product suite. About the Role You will be the first Data Scientist on the Embedded Insights team, part of Plaid’s Data organization. You will establish the analytics and metrics backbone for a team supporting a diverse set of internal and external products. You will help drive better decision-making, support machine learning model development, and contribute directly to the health of the Plaid network and the quality of Plaid’s products. Your day-to-day work will include: Analyzing entities across the Plaid network to understand behavior and identify opportunities, anomalies, and risks. Creating foundational metrics, dashboards, and monitoring systems that provide a clear view of network health and machine learning model performance. Evaluating the value and performance of machine learni

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1mo ago

About the Team The Emerging Products team is a lean, high-output product lab group that builds products at the forefront of model capabilities. We collaborate across all teams within the company, from research and infrastructure to consumer products. The team is responsible for identifying new product opportunities, building them quickly, dogfooding them internally, and then launching the successful products to users. We use data, user research, and analytics to inform our ideas, and make decisions on what experiments are worth iterating, stopping, or scaling. About the Role We’re looking for a senior, product-minded software engineer to own ambiguous 0-to-1 work from idea through prototype, validation, and handoff. This is a full-stack role with a strong frontend and product emphasis: you will build the interfaces and supporting backend systems needed to test new experiences quickly, while making sound architectural choices that enable successful concepts to scale. This role is based in our Mission Bay office in San Francisco. In this role, you will: Build and ship high-quality, product experiments across the full stack. Turn ambiguous user needs and emerging technical capabilities into testable product concepts, using research and metrics to guide iteration. Own technical direction for 0-to-1 projects, balancing speed, reliability, and a clear path from prototype to scalable product. Partner closely with design, product, research, and engineering teams to dogfood, evaluate, launch, and transition successful experiments. You might thrive in this role if you: Have a track record of building and shipping end-to-end products in fast-moving, startup, founder-led, growth, or other high-ownership environments. Bring strong frontend engineering skills and enough backend and systems depth to make sound full-stack architectural decisions. Pair product intuition with evidence, using user research and product data to identify opportunities and make pragmatic tradeoffs. Operat

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Lyft
📍 Mexico City• Full-time
1mo ago

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. Every day, millions of riders and drivers depend on Lyft to get where they're going. When something goes wrong along the way, they expect us to make it right — quickly, clearly, and without friction. How fast and how well we resolve those moments shapes whether people keep choosing Lyft. The Self-Serve Intelligence team, within the Safety & Customer Care org, is composed of engineers building the AI-powered systems that do exactly that: resolving rider and driver suboptimal experiences without agent involvement through AI Assist (e.g. AI Agents), automations, and self-serve workflows. Our goal is to make getting help feel effortless. We design and build backend services, APIs, and GenAI-powered products that combine robust engineering with applied AI to deliver reliable, scalable self-serve experiences. We are looking for a highly motivated, collaborative, team-focused and technically strong Software Engineer to join our Self-Serve Intelligence team. As a member of this team, you will build the services and AI-powered products that resolve customer issues autonomously. Every day, you'll partner with machine learning engineers, product, design, data science, and operations on high-impact projects — from shipping new AI Agent capabilities, to building the evaluation pipelines that keep their quality high, to improving the backend services underneath them. You'll bring strong engineering instincts, genuine curiosity about applied AI, and a willingness to work through ambiguity in a space that changes month to month. Responsibilities: Write well-crafted, well-tested, readable, and maintainable code Partner with senior engineers to design, build, and ship backend services and GenAI-powered products (e.g. AI Agents) that resolve rider and driver suboptimal experiences Independently lead tasks fro

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1mo ago

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is looking for an experienced Data Engineer to support and accelerate the productivity of our Go-To Market organization. In this role, you will facilitate Smartsheet's growth strategy through insights produced with data analysis. You will work directly with senior leadership to inform strategic decision-making as part of a collaborative, motivated team. Your work will be instrumental in helping our Sales partners optimize their pipeline, increase retention, and close deals. You Will: Help to create, evolve, and maintain the reporting infrastructure for the Sales organization to promote more intelligent discussion at all stages of the sales funnel. Partner with engineering, data science, and other analytics teams to build scalable analytics solutions with a focus on reporting capabilities. Mine large datasets to ensure data accuracy and completeness for reporting purposes. Analyze and monitor data for anomalies, with a focus on data quality and consistency within reports. Guide commission and territory planning processes with analytical support, providing the necessary reports and data. Develop and maintain key performance indicators (KPIs) to track sales performance, pipeline health, and other critical metrics. Automate report generation and distribution to improve efficiency. Provide technical expertise and guidance to junior analysts on data extraction, transformatio

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1mo ago

The MongoDB Atlas Clusters Team is seeking a Senior Staff Product Manager to provide division-wide, product leadership for MongoDB Atlas which is our best-in-class, fully managed, multi-cloud database service that simplifies the complexities of deploying and managing highly available database deployments across multiple regions and cloud providers. As the most senior product management contributor, you will shape the multi-year strategy, product architecture, and market trajectory for the entire Atlas Clusters business unit. You will be the primary product authority on the most complex trade-offs, anticipating systemic risks and cutting through structural friction that blocks multiple teams and initiatives. This role requires collaboration with distinguished engineers to rigorously debate strategy and pressure-test assumptions and advise executive leadership on options that balance long-term monetization, strategy, and business outcomes. And, where relevant, owns the pricing and monetization strategy for the product line. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. Responsibilities Product Vision and Roadmap: Spearhead strategic unity across multiple product areas over a multi-year horizon to drive a coherent product experience Business Leadership: Originate and de-risk the division’s most consequential strategic bets, owning rigorous business cases and advising leadership on multi-year economic outcomes Customer Advocacy: Engage with strategically significant customers at the senior level (e.g., advisory boards and executive briefings) to surface cross-portfolio opportunities and inform the roadmap PM Excellence: Elevate the global standard of product management by mentoring Staff and Senior PMs and pioneering new data-driven playbooks across the organization. Create frameworks and standards for customer and market research that others use for conducting high-quality customer and market research Cross-Fu

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Lyft
📍 Montreal• Full-time• C$34 – C$36/hr
1mo ago

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. As a Test Automation Intern at Lyft, you'll collaborate closely with industry-leading engineers while enjoying the freedom to innovate from day one. Your contributions will be pivotal in accelerating our product development and enhancing user trust and satisfaction through the creation of cutting-edge test automation tools. At Lyft, we cultivate a dynamic and collaborative office environment, where brilliant minds are always eager to hear and support your next big idea. What will yours be? Responsibilities: Own your project, while checking in with other team members throughout the day with questions and updates You leave the code in a better state than when you found it (progressive refactor) You value reliability, ensured by testing (unit, integration and load tests) Participate in code reviews to ensure code quality and distribute knowledge Continuous integration and deployment Go home knowing that your work today is meaningfully improving the quality of every Lyft Urban Solutions rider! Experience: Currently pursuing a Bachelor's or Master's degree in Computer Science from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required) . For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Montreal Strong knowledge of CS fundamentals Excellent communication skills Passion for community, sustainability, and/or transportation Passion for quality and testing Ability to thrive in a startup environment Contributions to open source projects Experience working with databases Experience solving real-time technology problems Experience with mobile development Experience wit

aigorust
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