Signal And Growth Insights Manager Jobs

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 . You'll join the Product Marketing team within the Institutional group and own how Coinbase's most complex institutional products show up to clients globally. You'll be the PMM behind spot, derivatives, cross-margin, liquidity, and execution workflows used by hundreds of hedge funds, asset managers, and market makers. Partnering closely with Product, Markets, Sales, Legal, and Comms, you'll translate deeply technical capabilities into clear positioning, sharp enablement, and GTM strategies that drive measurable client adoption. What you'll do: Own positioning and messaging for Prime and Markets across spot, futures, options, cross-margin, execution, and liquidity access, pressure-testing narratives with Sales, Product, Legal, and clients to ensure credibility at institutional scale. Lead GTM execution for major Prime and Markets launches, including product readiness, sales enablement, client communications, sequencing, and events. Build high-signal enablement materials - talk tracks, FAQs, battlecards, demos, and client-ready narratives - that reduce complexity for the field and reflect real objections, deals, and buying behavior. Partner with Sales, STPs, and Coverage to translate complex technical capabilities into institutional-grade clarity, and contribute market-backed insight that informs product roadmap conversations. Drive clarity around what's live, what's ne

About the team The OpenAI for Government team is a dynamic, mission-driven group leveraging frontier AI to transform how governments achieve their missions. Our team works to empower public servants with secure, compliant AI tools (e.g., ChatGPT Enterprise, ChatGPT Gov) and mission-aligned deployments that meet government technical requirements with strong reliability and safety. About the role Forward Deployed Engineers (FDEs) lead complex deployments of frontier models in production. You will embed with our most strategic government and public sector customers—where model performance matters, delivery is urgent, and ambiguity is the default. You’ll map their problems, structure delivery, and ship fast. This includes scoping, sequencing, and building full-stack solutions that create measurable value, while driving clarity across internal and external teams. You will work directly with defense, intelligence, and federal stakeholders as their technical thought partner, guiding adoption, maximizing mission impact, and ensuring successful deployments at scale. Along the way, you’ll identify reusable patterns, codify best practices, and share field signal that influences OpenAI’s roadmap. This role is based in Washington DC, Seattle or 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, including on-site work with customers. In this role you will Own technical delivery across multiple government deployments, from first prototype to stable production. Deeply embed with public sector customers to design and build novel applications powered by OpenAI models. Enable successful deployments across customer environments by delivering observable systems spanning infrastructure through applications. Prototype and build full-stack systems using Python, JavaScript, or comparable stacks that deliver real mission impact. Proactively guide customers on maximizing business and operational value from

Who We Are Simpplr is the AI-powered intranet for unifying the digital workplace. It brings people, trusted knowledge, apps, and agents into a coherent digital experience. Powered by a proprietary EX Knowledge Graph, Simpplr synthesizes signals and context across connected systems to deliver personalized information and actions. The platform serves as a digital hub supporting communications, engagement, employee services, and work. With low-code extensibility and enterprise-grade security and governance, Simpplr enables confident operation at scale. More than 1,000 organizations — including AAA, the NHS, Penske, and Moderna — trust Simpplr to keep their workforce informed, aligned, and productive. Learn more at simpplr.com . The Opportunity We're looking for a highly skilled Senior Product Manager – Enterprise Search to join our Product Management team . In this role, you'll own the strategy, definition, and execution of enterprise search across Simpplr — powering both Magnus (our AI assistant) and the Simpplr platform. You'll shape how employees find the right knowledge, content, and answers across the entire enterprise, quickly, accurately, and securely. Search is the connective tissue of the employee experience: it is what makes Magnus's answers trustworthy and what makes the Simpplr platform feel intelligent. You'll be responsible for the end-to-end search experience — from how content is ingested, chunked, and indexed, to how it is retrieved, ranked, and grounded into high-quality, permission-aware answers via retrieval-augmented generation (RAG). You'll work closely with AI engineers, search/ML engineers, data scientists, designers, and cross-functional teams to deliver a search foundation that is fast, relevant, and enterprise-grade. This role requires strong technical fluency in modern search and AI concepts — indexing, chunking, embeddings, vector and hybrid retrieval, ranking, and RAG — along with the product judgment to translate them into measurabl

About the Team The Hardware Health and Observability team owns the end-to-end health lifecycle of OpenAI’s global compute fleet. Our mission is to maximize healthy, usable compute across accelerator vendors, generations, cloud providers, and regions through reliable health signals, automated remediation, and scalable operational tooling. We build the systems that observe, detect, remediate, and verify hardware issues across GPUs, CPUs, networking, and platform infrastructure, enabling frontier model training and inference workloads to run reliably at hyperscale. We are the last line of defense for the success of OAI’s production and research workloads. About the Role On the Hardware Health and Observability team, you’ll build critical infrastructure that keeps OpenAI’s largest compute clusters healthy and operational at scale. Even small numbers of unhealthy systems can impact large-scale training and inference workloads. This team focuses on minimizing downtime, improving fleet efficiency, and ensuring compute resources remain continuously available to researchers and product teams. Engineers on this team own problems end-to-end, from defining health signals and debugging failures to building automated remediation systems that operate across millions of GPUs globally. In this role, you will: Define and maintain health signals across GPUs, CPUs, networking, and platform infrastructure. Build and evolve health checks that detect, remediate, and verify failures at scale. Ensure critical health checks execute with minimal latency to maximize workload uptime. Investigate hardware failures and system-level issues across large-scale compute environments. Own node lifecycle workflows including drain, quarantine, repair, RMA, and return-to-service processes. Build automation and tooling that enables global cluster management with minimal manual intervention. Partner with workload, reliability, and provider teams to integrate health signals into training and inference system

About the team The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem in close collaboration with our internal and external partners. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. This role focuses specifically on AI Safety: understanding and mitigating risks created or amplified by increasingly capable AI systems. It is not a cybersecurity, information security, or corporate security role. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs AI safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed responsibly across critical sectors. About the role We are looking for a Frontier AI Risks Lead to help us understand potential harms and misuse of AI in a time of rapid, sustained change. We seek to understand how developments in AI could intersect with misuse and abuse, accelerating existing harm areas and creating novel risks. We seek to scan available signals and use strategic foresight methodologies to enable proactive detection and mitigation of frontier AI risks. This is an AI safety role focused on frontier and systemic risks, including model misalignment, recursive self-improvement (RSI), multi-agent interaction, loss of control, runaway agents, and related emerging failure modes. In this role, you will help provide a strategic-level perspective on a range of frontier AI safety areas, producing actionable understanding of issues relevant to OpenAI’s platforms, systems, and broader mission. Utilizing mixed quantitative and qualitative methodologies, you will spot early warning signs, pull threads on potentially concerning behavior, and turn weak signals into clear, prioritized risk calls. You will focus on upstream ecosystem sc

PagerDuty (NYSE:PD) is a leader in Digital Operations Management. In an always-on world, organizations of all sizes trust PagerDuty to help them deliver a perfect digital experience to their customers, every time. Teams use PagerDuty to identify issues and opportunities in real time and bring together the right people to fix problems faster and prevent them in the future. Over 13,000 organizations (including 60 of Fortune 100) rely on PagerDuty to succeed with Digital Transformation, Cloud Migration, and DevOps Modernization. Notable customers include GE, Cisco, Genentech, Electronic Arts, Cox Automotive, Netflix, Shopify, Zoom, DoorDash, Lululemon and more. We are expanding rapidly as a platform for Digital Operations Management using AI/ML and Automation and growing our adoption by Development, IT, Customer Service, Security, and other teams across the organization. About the role PagerDuty’s Operations Cloud runs on a platform that ingests billions of signals and turns them into real-time action for thousands of customers. We’re looking for a Senior AI/ML Engineer who lives at the intersection of two disciplines: large-scale distributed systems and applied AI. In this role you will design and ship AI systems that run in production at PagerDuty’s scale — powering Incident Management AI Agents, event intelligence, and the LLM-powered capabilities embedded across our platform. You’ll own the full lifecycle, from framing the problem to serving reliably at scale. We are looking for a candidate who is genuinely passionate about building with modern AI — LLMs, agents, and retrieval — but grounded in the realities of building resilient, high-throughput systems. What you’ll do Design and build AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time event streams, from problem framing through production deployment and monitoring. Architect and own the systems behind them: agent and prompt orchestration, retrieval pipelin

PagerDuty (NYSE:PD) is a leader in Digital Operations Management. In an always-on world, organizations of all sizes trust PagerDuty to help them deliver a perfect digital experience to their customers, every time. Teams use PagerDuty to identify issues and opportunities in real time and bring together the right people to fix problems faster and prevent them in the future. Over 13,000 organizations (including 60 of Fortune 100) rely on PagerDuty to succeed with Digital Transformation, Cloud Migration, and DevOps Modernization. Notable customers include GE, Cisco, Genentech, Electronic Arts, Cox Automotive, Netflix, Shopify, Zoom, DoorDash, Lululemon and more. We are expanding rapidly as a platform for Digital Operations Management using AI/ML and Automation and growing our adoption by Development, IT, Customer Service, Security, and other teams across the organization. About the role PagerDuty’s Operations Cloud runs on a platform that ingests billions of signals and turns them into real-time action for thousands of customers. We’re looking for an early-career AI/ML Engineer who is excited to grow at the intersection of two disciplines: large-scale distributed systems and machine learning. In this role you will help build and ship AI systems that run in production at PagerDuty’s scale — powering Incident Management AI Agents, event intelligence, and the LLM-powered capabilities embedded across our platform. You’ll work alongside senior engineers on real production problems, learning how AI features go from a prototype to something that serves reliably at scale. We are looking for a candidate who is genuinely excited about building with modern AI — LLMs, agents, and retrieval — eager to learn how resilient, high-throughput systems are built, and motivated to grow into an engineer who is strong in both. What you’ll do Contribute to AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time data, with support and guidanc

About the Team OpenAI’s Network Security team designs and operates the secure, reliable connectivity behind our offices, labs, campuses, cloud environments, people, and devices. We combine strong network fundamentals with automation, observability, and close partnership across IT, Security, Research, Applied, and business teams. About the Role As a Network Engineer, you will design, operate, troubleshoot, and automate secure, reliable networks across offices, labs, cloud connectivity, and production services. You will balance strategic platform work—architecture, standards, roadmaps, lifecycle planning, and automation—with responsive operations such as incidents, escalations, break/fix, and time-sensitive delivery. We’re looking for broad network engineers who meet users where they are, lead with curiosity, own outcomes end-to-end, move with urgency grounded in security, and iterate with purpose. You will turn operational signals and recurring reactive work into durable systems and standards. In this role, you will: End-to-end ownership of secure enterprise routing, switching, wireless, WAN, network services, and cloud connectivity. A deliberate balance of strategic platform improvement and responsive troubleshooting, change safety, incident response, and operational delivery. Purposeful iteration through software, APIs, Infrastructure-as-Code, Git workflows, testing, and CI/CD that reduces recurring reactive work. You might thrive in this role if you have: End-to-end ownership of secure enterprise routing, switching, wireless, WAN, network services, and cloud connectivity. A deliberate balance of strategic platform improvement and responsive troubleshooting, change safety, incident response, and operational delivery. Purposeful iteration through software, APIs, Infrastructure-as-Code, Git workflows, testing, and CI/CD that reduces recurring reactive work. Compensation, Benefits and Perks This is a position with OpenAI UK Ltd., which controls the hiring and manageme

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. Enterprise Marketing is responsible for driving B2B pipeline and revenue at Replit. The function owns the full enterprise go-to-market motion, from audience development and campaign strategy through to qualified pipeline delivery and sales handoff. It operates in close partnership with Sales, RevOps, Product Marketing, and an AI-driven paid media optimization team to move enterprise accounts through the buyer journey. A defining characteristic of Replit's enterprise motion is its PLG foundation. With millions of individual users already in the product, Enterprise Marketing is uniquely positioned to identify expansion signals and convert individual users into enterprise opportunities. Role The Senior Manager, Demand Generation is responsible for building and scaling Replit's enterprise demand generation function. The role owns B2B campaign strategy, ABM playbook development, funnel architecture, and pipeline accountability across the enterprise segment. Reporting to the Head of Enterprise Marketing, this role is the architect of Replit's enterprise campaign programs, defining who we target, what we say, and how we engage them across the buyer journey. Responsibilities Own enterprise pipeline generation through campaign strategy, audience development, and creative programs Partner with business leadership and finance to forecast pipeline targets, track performance, and present results in monthly and quarterly business reviews Build lead scoring frameworks, funnel definitions, and pipeline attribution models in partnership with RevOps Design and launch account-based marketing strategies targeting high-value enterprise accounts: account selection, engagement sequencing, and multi-touch campaign design Create repeatable cam

The Central Sales Analytics team at MongoDB sits at the center of how we understand and improve the performance of our revenue engine. While this role is rooted in Sales Analytics, its scope is broader and spans key parts of the GTM organization. This team partners closely with Sales, Sales Operations, Strategy & Planning, FP&A, Compensation, GTM Tech, and other cross-functional stakeholders to drive data-informed decisions across pipeline, productivity, forecasting, product adoption, and overall business performance. We are looking for a Sr/Staff Analyst who can operate as both a strategic thought partner and a hands-on builder. This person will lead high-impact analytics work, translate ambiguous business questions into clear analytical plans, and develop scalable data products that help leaders make better decisions faster. The right candidate combines strong business judgment with deep technical fluency in SQL and Python, and is comfortable influencing senior stakeholders while independently driving complex work from scoping through execution. This role also sits at an important intersection of GTM, Product, and Technology. In select cases, this person will work with Product and Technical teams to connect GTM insights with product signals and customer behavior, especially across GTM Tech, Atlas Core, and Emerging Products. There is also a strong expectation that this person brings an AI-forward mindset, using leading AI technologies and platforms to accelerate analysis, improve workflows, and build scalable insight-generation capabilities. We are looking to speak to candidates who are based in Gurugram for our hybrid working model. What you'll do Partner with Sales, Sales Operations, Strategy & Planning, FP&A, Compensation, GTM Tech, and broader GTM stakeholders to identify high-value analytical opportunities and turn them into actionable insights Lead deep-dive analyses across pipeline health, funnel conversion, seller productivity, quota attain

Job Requisition ID # 26WD101306 Position overview Autodesk Flow is the connected platform behind how film and television get made — from the moment footage is captured on set, through review and approval, to final delivery. This is a dedicated ABM role for Flow, working hand in hand with the Flow sales organization. You will be their marketing counterpart: building the account clusters, programs and sales-facing materials that turn business priorities into engaged accounts and qualified pipeline. You will shape how the account-based motion works here — how accounts are scored and clustered, how programs are built around sales priorities, and how we measure what they produced. You will work in close partnership with a Field Marketing Manager, the wider Media & Entertainment marketing organization, and our central content team. Location :This position can be remote or hybrid. Responsibilities Partner with Sales: Act as the dedicated ABM partner to the Flow sales organization, building programs around their account priorities and revenue targets Run a recurring planning cadence with Sales — account co-planning, pipeline reviews and quarterly business reviews — reviewing engagement, buying signals and next best actions Own lead routing and funnel optimization for Flow, making sure the handoff from marketing program to seller follow-up is fast, clean and measured Partner across Marketing, Industry Strategy and Technical Sales to coordinate account engagement Build and prioritize account clusters: Build account clusters around shared buying t

Who We Are Simpplr is the AI-powered intranet for unifying the digital workplace. It brings people, trusted knowledge, apps, and agents into a coherent digital experience. Powered by a proprietary EX Knowledge Graph, Simpplr synthesizes signals and context across connected systems to deliver personalized information and actions. The platform serves as a digital hub supporting communications, engagement, employee services, and work. With low-code extensibility and enterprise-grade security and governance, Simpplr enables confident operation at scale. More than 1,000 organizations — including AAA, the NHS, Penske, and Moderna — trust Simpplr to keep their workforce informed, aligned, and productive. Learn more at simpplr.com . About the role We are looking for a Lead Voice AI Engineer to build production-grade Voice Agents for frontline heavy verticals like healthcare, manufacturing, warehousing, retail, hospitality focusing on employee support, procurement, collections, logistics, ordering etc. You will lead the design of low-latency, real-time voice systems combining ASR, TTS, LLMs, conversational AI, enterprise workflows, knowledge retrieval, compliance, and human handoff. This is a hands-on technical leadership role for someone who can take Voice AI from architecture to production. Responsibilities Design and build the real-time voice runtime for live conversations. Build and optimize streaming ASR, TTS, VAD, endpointing, turn-taking, and barge-in. Build adaptive voice pipelines for high-noise frontline environments (60-112 dB), hospitals, factory floors, warehouses, including server-side noise cancellation, echo suppression, and dynamic ASR/TTS optimization for PSTN and mobile phone audio quality. Architect multi-provider speech routing across a broad multilingual matrix, including code-switching (e.g., Spanglish, Hinglish), where no single ASR or TTS provider covers all languages, and language detection, provider selection, and fallback chains must operate

Who We Are Simpplr is the AI-powered intranet for unifying the digital workplace. It brings people, trusted knowledge, apps, and agents into a coherent digital experience. Powered by a proprietary EX Knowledge Graph, Simpplr synthesizes signals and context across connected systems to deliver personalized information and actions. The platform serves as a digital hub supporting communications, engagement, employee services, and work. With low-code extensibility and enterprise-grade security and governance, Simpplr enables confident operation at scale. More than 1,000 organizations — including AAA, the NHS, Penske, and Moderna — trust Simpplr to keep their workforce informed, aligned, and productive. Learn more at simpplr.com . About the role You'll join our Technical Support team as a technical writer. You'll write the documentation that helps customers understand and use the product. You'll report into Support, so you'll work closely with agents and support leaders to shape what the knowledge base should become. You'll also partner with product managers, designers, and engineers to document features before they ship. Your writing will shape how well customers can help themselves. You'll help reduce ticket volume, speed up support responses, and give the AI assistants that handle customer questions better material to work with. It's a hands-on writing role that directly affects customer experience. What you'll do Write and update knowledge base articles for the product areas you own, including admin guides, how-tos, and troubleshooting content Work with the support team to spot common customer issues, close gaps in the KB, and decide what to update next Partner with PMs and engineers as new features get built, drafting release notes, in-app help text, and UX microcopy along the way Own one or two product areas as your main focus, and pitch in on shared areas when needed Create your own screenshots and short screen recordings to go with your writing Explain AI fe

About Scale AI At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that

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