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Customer Learning Program Lead Jobs

10,000 active opportunities · Updated for October 2026

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Explore current customer learning program lead jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Mixpanel
📍 Sydney• Full-time• Hybrid
1mo ago

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Customer Engineering Team Mixpanel’s Customer Engineering teams are analytics consultants who embed themselves within our enterprise customer teams to drive business outcomes. We work with prospects and customers throughout the customer journey to understand what drives value, and serve as the technical counterpart to our Sales organisation to deliver on that value. You will partner closely with Account Executives, Customer Value Architects, Product, Engineering, and Support to successfully roll out self-serve analytics within our customers’ organisations, help manage change, execute on technical projects and services that delight our customers, and ultimately drive ROI on the customer’s Mixpanel investment. About the Role Our Customer Engineers are inquisitive, nimble, and able to clearly articulate the technical benefits and requirements of Mixpanel to developers and product managers, while also communicating the business value of our product to senior executives. In your first month, you’ll become a Mixpanel expert—both in features and functionality as well as implementation. You’ll shadow customer calls and demos with current Customer Engineers and Account Executives while learning to articulate our value proposition, and be trained on Mixpanel’s internal systems and tools. Within your first three months, you’ll be directly involved in deal cycles with Account Executives across the ANZ region. You’ll lead the technical qualification for customer use cases and deliver customised demos for prospects and existing customers, working directly with leadership at the prospect’s organisation to und

pythonsqlaws
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Coinbase
📍 Brazil• Full-time• Remote
1mo ago

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . The CX Intelligence Engineering team, part of Coinbase's Enterprise Applications and Architecture org, builds the multi-agent platform powering Coinbase Chat, Help Center, and agent tooling. As a Machine Learning Engineer on this team, you'll design and scale the agentic systems that automate complex customer support workflows, connecting LLMs with internal APIs and tools to deliver fast, accurate, and compliant AI-powered experiences for millions of customers. What you'll do: Architect multi-agent systems using advanced orchestration frameworks (LangGraph, Google ADK) to automate complex customer support procedures end-to-end. Build and scale integrations using Model Context Protocol (MCP) to connect LLMs with internal Coinbase APIs, databases, and third-party tooling. Develop automated "LLM-as-a-judge" evaluation pipelines to monitor, measure, and improve the performance of non-deterministic AI agents in production. Implement RAG, fine-tuning, and prompt engineering techniques to ensure chatbot responses are grounded, accurate, and compliant with Coinbase policies. Ship production-ready Python services that are resilient, low-latency, and capable of handling Coinbase-scale traffic across asynchronous microservices. Partner with Conversation Design and Product to translate complex business logic into executable agent procedures within the decentralized architecture.

REMOTEpythonreactaws
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C
1mo ago

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Machine Learning Engineer on the CX Intelligence team within Enterprise Applications and Architecture, you'll build the AI-powered conversational systems that connect Coinbase's Help Center, chatbots, and agent workflows. The team owns the multi-agent platform powering Coinbase Chat and agent tooling, partnering with Conversation Design, CX, and Engineering to deliver secure, scalable automated support. You'll lead the design and implementation of a unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants, directly improving how millions of customers get help. What you'll do: Architect and deploy the orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational environment. Build production-grade Python services that bridge advanced ML/AI research with reliable, measurable customer-facing products. Lead end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies from design through delivery. Establish best practices for system design, coding standards, and AI/ML development workflows across the team. Mentor engineers on architectural integrity and modern AI/ML patterns, raising the technical bar for the broader team. Co

REMOTEpythonawsmachine learning
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C
Coinbase
📍 - India• Full-time• Remote• From ₹66.1L/yr
1mo ago

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . The CX Intelligence team is part of Coinbase’s Enterprise Applications and Architecture org and builds the customer-facing and internal CX experiences that connect the Help Center, chatbots (CBCB), and agent workflows. The team owns the multi-agent platform which powers coinbase chat, Help Center and agent tooling surfaces, partnering closely with Conversation Design, CX, and other Engg teams to deliver secure, compliant, and scalable AI-powered support. Our work provides the trusted and accurate automated and agent-assisted experiences—helping customers get answers faster while enabling human agents to resolve cases more effectively. We are hiring an IC5 Machine Learning Engineer to drive the evolution of our conversational ecosystem by building a seamless hybrid vendor-internal chatbot experience. You will lead the design and implementation of a sophisticated unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants. This role is pivotal in managing complex state transitions, context sharing, and intent routing across a distributed environment. You’ll thrive here if you enjoy high ownership, architecting complex hand-off logic between disparate LLM frameworks, and building reliable AI-enabled products that are fast, measurable, and scalable. What you'll do: Architect and deploy the orchestratio

REMOTEpythonawsmachine learning
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E
Enigma
📍 New York• Full-time• $180K – $295K/yr
24 days ago

The Opportunity This is a critical and exciting time at Enigma. Our customers consistently tell us that our data products create tremendous value and are deeply aligned with their most important workflows. As demand grows, we have an urgent opportunity to improve both the intelligence of our data and the systems through which customers access it. We are looking for an experienced Senior/Staff Machine Learning Engineer to join our Match Team and help shape the next generation of Enigma’s customer-facing data products. In this role, you will combine advanced statistical and machine learning research with the engineering systems required to power fast, relevant, and reliable search experiences at scale. This is a uniquely high-impact role sitting at the intersection of information retrieval, ranking systems, semantic search, distributed systems, and customer data delivery. The Role At the core of Enigma’s product is our data, which makes both data science and delivery systems central to what we build. As a Senior/Staff ML Engineer on the Match Team, you will lead efforts that improve the relevance, latency, and scalability of our customer-facing data products. You’ll work across the full lifecycle: framing retrieval and ranking problems, developing models and experimentation strategies, evaluating results using real-world signals, and implementing high-throughput search and retrieval systems. This role is ideal for someone who is excited by both hard ranking/search problems and the systems challenges of turning those solutions into low-latency, production-grade retrieval systems. What You'll Do Develop innovative solutions to complex problems in information retrieval, ranking, semantic search, query understanding, and recommendation systems Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems using Python, Typesense, and AWS Evaluate and evolve our search technology stack, driving technical design decisions across index

pythonawsmachine learning
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SA
24 days ago

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. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

pythonawsrest
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Taskrabbit
📍 New York• Full-time• From $170K/yr
26 days ago

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role is hybrid requiring 2 days in office at our San Francisco or NYC hub every Tuesday & Wednesday. About the Role Machine Learning is a cornerstone at Taskrabbit, and we're looking for a Staff Machine Learning Engineer to join our team and lead the next phase of our customer retention strategy. This is a critical, full-stack role for an individual who is passionate about the end-to-end lifecycle: from initial research and model development to building the robust systems that power repeat customer engagement and lifetime value growth at scale. Taskrabbit's greatest growth opportunity lies in deepening customer relationships and accelerating repeat purchases. Our most valuable customers are those who return frequently, discover new service categories, and increase their spending over time. There's significant untapped potential in the marketplace: repeat customers spend 3-5x more than one-time users, and category expan

pythonsqldocker
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Taskrabbit
📍 New York• Full-time• From $170K/yr
28 days ago

About Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role is hybrid requiring 2 days in office at our San Francisco or NYC hub every Tuesday & Wednesday. About the Role Machine Learning is a cornerstone at Taskrabbit, and we're looking for a Staff Machine Learning Engineer to join our team and lead the next phase of our customer retention strategy. This is a critical, full-stack role for an individual who is passionate about the end-to-end lifecycle: from initial research and model development to building the robust systems that power repeat customer engagement and lifetime value growth at scale. Taskrabbit's greatest growth opportunity lies in deepening customer relationships and accelerating repeat purchases. Our most valuable customers are those who return frequently, discover new service categories, and increase their spending over time. There's significant untapped potential in the marketplace: repeat customers spend 3-5x more than one-time users, and category expan

pythonsqldocker
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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. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

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C
Cloudflare
📍 Hybrid• Full-time• Hybrid
1mo ago

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Locations: Austin, TX About the Role You’ll help define how machine learning models run across Cloudflare’s global network, from frontier open LLMs and real-time voice models to customer-deployed models served on heterogeneous GPUs and next-generation accelerators. You’ll work with systems engineers, product teams, hardware partners, and AI/ML engineers to bring models into production with low latency, strong reliability, and effic

pythonawsmachine learning
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D
1mo ago

Enterprise Customer Success Managerとして、Datadogの中でも最大規模かつ戦略的に重要な顧客を担当し、プロダクトの健全な活用促進と、ポジティブな顧客体験の実現をリードしていただきます。 Datadogでは、オフィスカルチャーを大切にしています。人と人との関係性やコラボレーション、そこから生まれる創造性を重視し、ハイブリッドワークを通じて、一人ひとりに合ったワークライフバランスを実現しています。 主な業務内容(What You’ll Do) SalesおよびTechnical Solutionsと連携し、オンボーディングから活用成熟フェーズまでのプロダクト利用促進を主体的に推進 新規顧客のオンボーディングプロセスをオーナーとして設計・推進・プロジェクト管理 顧客のサクセスプランを策定し、主体的に管理・実行 Datadogへの投資価値・成果について、意思決定者と継続的に認識をすり合わせ 顧客組織内のキーパーソン・影響力のあるステークホルダーとの関係構築・維持 社内の各部門(Sales、Support、Enablement、Product、Finance、Legal)との密な連携 利用状況データをモニタリング・分析し、更新機会やリスクの早期把握 顧客のプロダクト活用および健全性(Customer Health)の最終的な責任者として対応 求める人物像(Who You Are) B2B SaaSにおけるCustomer SuccessまたはAccount Managementの実務経験3年以上 大手エンタープライズ顧客を含むアカウントポートフォリオの担当経験 顧客の課題・目的・優先順位を理解するためのディスカバリーを主導できる方 複雑な内容を分かりやすく伝え、顧客の課題・目的と結びつけて説明できる高いコミュニケーション力 また、相手に応じてメッセージを柔軟に調整できる方 スピード感のある環境で、自身のスキルを継続的に高めながら、チームのベストプラクティス形成にも積極的に関与できる方 必要に応じて顧客訪問やイベント対応のための出張が可能な方 本ポジションでは、日本国内およびグローバルの社内関係者・社外のお客様とのコミュニケーションが発生するため、日本語・英語ともに、読み書きおよび会話においてビジネスレベル以上の語学力をお持ちの方 Datadogは、さまざまな立場の人々を大切にしています。誰もが初日から上記の資格をすべて満たすわけではないことは理解しています。それでも構いません。テクノロジーに情熱を持ち、スキルを伸ばしたいと思っている方は、ぜひご応募ください。 利益と成長: 最高のオンボーディング MEDDICとCommand of Messageの営業研修 包括的な企業文化、コミュニティ・ギルドに参加する機会 社内ネットワークのための部門内メンターおよびバディ・プログラム 継続的な専門能力開発、製品トレーニング、キャリアパスの提供 新規雇用株式(RSU)および従業員株式購入制度(ESPP) 手厚く競争力のある福利厚生パッケージ 上記の福利厚生と成長は、雇用国やDatadogでの雇用内容によって異なる場合があります。 #LI-Hybrid About Datadog: Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram , LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to

aigorust
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R
1mo ago

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. ABOUT THE TEAM + ROLE We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The AI R&D team is at the core of Robinhood's product intelligence. Our mission is to build and scale high-impact models that power personalization, search, social feeds, fraud detection, and risk management for millions of Robinhood users. We operate as a cross-functional partner to growth, product, and data engineering—translating complex financial data into intelligent systems that make Robinhood smarter for every customer. We move fast, raise the bar, and care deeply about building things that matter. If you've ever wanted to solve personalization problems no one else has cracked—in one of the most data-rich, regulated industries on the planet—this is the team for you! As a Staff Machine Learning Engineer on the AI R&D team, you will own the design and delivery of sophisticated personalization and recommendation systems that directly shape what millions of users see and do on the Robinhood platform. You'll be a technical anchor on a growing, high-caliber team — collaborating with product, data engineering, and fellow ML engineers to take ambitious ideas from zero to one and into production at scale. You'll help define the team's technical direction, mentor engine

pythonvueaws
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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Mission The Global Revenue Enablement (GRE) organisation exists to equip every audience in our ecosystem — field sellers, technical specialists, and partners — with the clarity, content, and skills they need to execute with speed and consistency. But enablement doesn't stop at the field. The fastest path to consumption is a customer who knows exactly how to use what they've bought. That's where Customer Activation comes in. We're building a function that embeds education directly into the account motion — not as a post-sale afterthought, but as a deliberate strategy to accelerate time-to-value, reduce friction in expansion conversations, and protect consumption in accounts that matter most. As the Customer Activation Partner Lead for APJ, you will own this motion across one of Snowflake's most strategically important and fastest-growing regions. You'll work at the intersection of sales, customer success, and learning — translating account intelligence into education plans, and education outcomes into pipeline signals. You'll bring deep relationships with field teams and the commercial instincts to position training not as a line item, but as a growth lever. This is a player, coach role for someone who wants to build. If you've spent your career watching education get un

aigorust
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T
Twilio
📍 - India• Full-time• Remote
1mo ago

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as Twilio’s next Senior Manager, Machine Learning on Twilio’s Conversation Memory team. About the job This position is critical to leveraging Twilio’s massive data ecosystem and communication scale to build foundational platform capabilities for the next generation of conversational AI, specifically by owning the development of 0-to-1 platform features that empower developers to build sophisticated, context-aware customer engagement applications. This is a highly technical, hands-on role, requiring a "player-coach" mentality to actively contribute technical expertise, bridge the gap between theoretical research and production-grade experimentation, and provide strategic direction to the team, rather than being purely a people manager. The leader in this role must demonstrate a strong bias for action, establishing a high-performing engineering setup that enables rapid iteration, experimentation, and deployment of models in this 0-to-1 set

REMOTEawsazuregcp
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24 days ago

About Us Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values Data driven: Start with truth, measure what matters. Courageous: Bias to action; run toward hard problems. Innovative: Seek novel, elegant solutions. Lean: Do more with less. Build, ship, learn fast. Humble: Strong opinions, lightly held. About the Role We’re looking for a Group Product Manager, Customer Acquisition to lead a portfolio of high-impact B2C growth products and develop a team of Product Managers. This leader will partner across Product, Engineering, Marketing, Design, and Analytics to identify meaningful customer and business opportunities, translate them into clear strategies, and deliver measurable improvements in growth, conversion, profitability, and customer lifetime value. This is a hands-on leadership role for someone who can operate at multiple altitudes: setting portfolio direction, coaching PMs, shaping senior-level decisions, and helping teams move quickly from insight to measurable learning. What You’ll Do Set a clear product strategy and portfolio of opportunities across multiple product teams. Lead and mentor 4 Product Managers (2 PMs and 2 SPMs), including hiring, coaching, performance management, career development, and raising the quality of product thinking. Coach PMs on customer discovery, strategic thinking, experimentation, execution, and business impact. Partner with functional leaders to set priorities, allocate resources, and resolve cross-team dependencies and trade-offs. Improve the quality and speed of product decision-making, helping teams move from customer insights to validated learning efficiently. Enable PMs to operate with autonomy while maintaining alignment and accountabilit

aimarketinglean
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