Enterprise Analytics And Reporting Manager in San Francisco

About the role The world is moving fast — and AI is moving faster. As a Product Marketing Manager focused on AI at Sigma, you'll be at the tip of the spear, helping define how we tell the story of one of the most exciting areas of the product. This role is as much about clarity as it is about creativity: you'll take complex, fast-evolving AI capabilities and distill them into the market messages, sales narratives, and customer stories that make people say "I get it — and I want it." We're looking for someone with genuine intellectual curiosity about AI, a bias for action, and exceptional instincts for what makes a message land. If you can absorb a lot of information quickly, find the signal in the noise, and write messaging that moves people — this role is for you. What you'll do Develop and refine positioning and messaging for Sigma's AI features, working closely with the Director of Product Marketing, AI and the Product team. Create sales enablement content — one-pagers, battlecards, demo guides, and objection handlers — that help the field confidently sell Sigma's AI capabilities. Support product launches for AI features: coordinate across product, design, marketing, and sales to bring new capabilities to market clearly and effectively. Research competitors' AI positioning and identify opportunities to sharpen Sigma's differentiation. Write and contribute to thought leadership content, blog posts, and customer-facing collateral that educate the market on Sigma's AI vision. Gather and synthesize customer and prospect insights — from win/loss data, customer interviews, and sales calls — to continuously improve messaging. Partner with demand generation and content teams to ensure AI messaging is consistently represented across campaigns, website, and events. What we're looking for 3+ years of product marketing experience in B2B enterprise software and/or cloud data platforms. The ability to learn quickly and deeply — you can get up to speed on a new te

AI only answers correctly when it can trust the data underneath it. This role owns two connected parts of how Sigma shows up in that world: where Sigma's experience lives outside its own product (MCP, a CLI, the Claude and ChatGPT marketplaces, integrations like Slack, Teams, and Glean), and the semantic layer that makes every one of those surfaces trustworthy. The first mandate is Sigma's AI ecosystem: defining Sigma's approach to MCP, giving external agents structured, governed access to Sigma's data model; owning the CLI, giving developers a fast way to work with Sigma outside the UI; and building Sigma's presence in the Claude and ChatGPT marketplaces, plus integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they already work. This is some of the most visible, fastest-growing surface area in the product. The second mandate is the semantic layer underneath it all. Every agent, chat answer, and integration is only as reliable as the data model behind it — get a metric definition wrong here, and every surface built on top inherits the mistake. This includes setting the roadmap for how semantic views connect across data platforms and how the model evolves as new AI capabilities emerge. What you'll do Define Sigma's approach to MCP, giving external agents and tools structured, governed access to Sigma's data model. Own the CLI roadmap, giving developers a fast, scriptable way to work with Sigma outside the UI. Build Sigma's presence in the Claude and ChatGPT marketplaces, along with integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they're already working. Set the roadmap for Sigma's data modeling strategy, including how semantic views connect across data platforms and how the semantic layer evolves as new AI capabilities emerge. Partner with engineering and design to ship integration and semantic modeling capabilities that hold up at enterprise scale.

Solution Architect Sigma Computing The SA role has evolved. Here’s the version we’re hiring for. The SA job in 2026 is not the SA job in 2023. Three things now sit at the center of how we evaluate this role. This hire has to do all three at a senior level, with the architectural depth to back it up. 1. Use AI every day to do the job better. If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are. We expect this hire to treat AI tooling as default infrastructure, not novelty. Come with a point of view on what you run, why, and how you use it to compress weeks of work into days. 2. Sell AI into the account. Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what. You have to be fluent. You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns. You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call. You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs. 3. Sell against AI. Every enterprise deal has AI competition in it. Sometimes it is Databricks Genie. Sometimes it is Snowflake Cortex Analyst. Sometimes it is a systems integrator pitching a bespoke agent built over the weekend. You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving. You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls. About Sigma Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, an

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable’s mission is to bring the power of computing and software development to everyone. We are developing a powerful and extensible toolkit that our customers can leverage to solve a variety of different problems and workflows. We’ve seen our most sophisticated customers use the product to run global processes across thousands of employees, coordinate precision manufacturing pipelines, and consolidate previously siloed mission-critical data into a single source of truth. The complexity of these use cases requires us to be extremely thoughtful about how we design and implement new functionality in the product and make sure it’s both easy to use and comprehend for our customers and maintainable for us. As a Full-Stack, Backend engineer at Airtable, you will have the opportunity to work with customers to deeply understand their needs and workflows. You will collaborate with cross-functional partners across product management, design, research and data science to create innovative new features that enable our customers to do their best work. You will be responsible for owning and executing the end-to-end implementation of these new features that will contribute to making our toolkit even more powerful and successful. We currently have openings on: The Admin & Governance Team (Full-Stack/BE) ensures Airtable is secure, compliant, and enterprise-ready. It owns key admin capabilities like the Admin Panel, SSO, and audit systems, as well as foundational features like User Groups. This team's mission is to accelerate organizational value for the largest customers with enterprise-first governance and controls. The Omni Capability & Quality Team (Full-Stack/BE) brings the power of AI directly to Airtable end users—

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's internship is not a side project. Interns own real, shipped work on the same roadmaps as full-time engineers, with mentorship from world-class talent and a culture that values ownership, speed, and truth-seeking. Many of our interns return as full-time Scaliens. Example Projects Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing billions of complex tasks Develop new AI infrastructure products to visualize, query, and explore Scale data Requirements A graduation date in Fall 2027 or Spring 2028 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Available for a Summer 2027 internship (May/June start dates) in San Franci

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

About the Team At DoorDash, design means making experiences for the people who order, the people who prepare, and the people who deliver. As a Designer at DoorDash, you want to build things that matter to real people. You're at your best when you can move from idea to shipped product quickly, bringing experiences to life that reach and influence users at massive scale. You'll care about whether the product you make solved a real problem for real people, or changed how someone experiences their day. About the Role At DoorDash, we’re redefining what it means to be a designer. We’re building a team of makers, builders, and doers. Over the past decade, “web designer” evolved into “product designer” as the scope expanded. Now, that shift is happening again — LLMs are broadening the role further, pushing design toward both strategic thinking and direct execution. As a Staff Product Designer, you’ll help lead this evolution: not only practicing build-first design, but scaling it across people, processes, and systems. In this role, you’ll join the Ads & Promos Design team — one of DoorDash’s fastest-growing businesses — owning end-to-end campaign experience design and shaping the strategic vision for our marketing tooling system. This platform powers both SMB and enterprise restaurants across DoorDash’s global markets and connects local businesses with over 40 million consumers globally. Your impact will span both team effectiveness and business growth. You’ll increase team velocity and autonomy by building reusable workflows, shared tools, and decision frameworks that enable designers to operate at a higher level with less coordination overhead. In parallel, you’ll drive measurable business outcomes by unlocking faster experimentation, shorter iteration cycles, and higher-quality execution across your team and adjacent teams. This role can be based in New York City, San Francisco, or Seattle and reports to the Design Manager for Ads & Promotions (Restaurant Experie

About Us Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X , and discover the projects we’re solving on our Blog . Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Team Twitch's Enterprise Platform & Technology (EPT) organization is looking for a Software Development Engineer II to build the systems where SAP meets AWS — extending our enterprise ERP with cloud-native services and agentic AI to power Finance and enterprise functions across Twitch and Amazon. This is a hands-on engineering role where you'll work on SAP-side development (ABAP, CDS, RAP, OData) and AWS-native engineering (Lambda, Step Functions, MCP servers, Bedrock, CDK) — owning integrations end-to-end. About the Role You'll work at the intersection of SAP enterprise systems and modern cloud engineering — building AWS-hosted APIs and pipelines that talk to SAP, standing up agentic AI tooling (MCP servers, Bedrock agents, Claude-powered workflows) that automates Finance operations, and shipping production AWS services alongside SAP customizations. The business problems are well understood; how you solve them with SAP + AWS + AI is up to you. We need someone equally comfortable writing ABAP inside SAP GUI and Python/TypeScript infrastructure code against AWS — a full-stack enterprise engineer who ships across both worlds and raises the bar on automation. You Will SAP Engineering (~50%) Design, build, and maintain integrations between SAP (S/4HANA, BTP) and downstream systems — own

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! We’re looking for a Research Scientist to advance how high-quality data and environments for AI agents are created. You’ll build and optimize pipelines that combine real-world data, automated generation, and human expert input. Working with domain experts, academic partners, customers, and our product and engineering teams, you’ll scale these pipelines to target frontier model performance gaps and expand data and environment diversity. Your work will amplify human knowledge and judgement, enabling experts to create and refine data and agentic environments that strengthens Snorkel’s position as the frontier data lab. This role is ideal for someone who wants to advance frontier AI through data and environment creation and enjoys turning research into reusable, scalable systems. Location: San Francisco, New York, OR REMOTE Main Responsibilities Design, implement, and optimize reusable pipelines that combine AI capabilities with expert judgment to accelerate data and agentic environment creation. Design and run rigorous experiments to validate proof-of-concept approaches, measure their impact on data quality, pipeline efficiency, and model performance, and communic

About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The AI team is focused on one of Stripe’s most strategic growth areas: enabling the monetization and scaling of AI-native and AI-enabled businesses. We’re in a unique position – partnering with the world’s most ambitious AI companies (the likes of OpenAI, Anthropic, NVIDIA, etc) building on the frontier of artificial intelligence -- across infrastructure, foundation models, agents, and applications -- to help them grow and commercialize globally using Stripe’s full financial stack. As part of Stripe’s GTM / Sales organization, this team works closely with Product, Engineering, and Marketing to shape Stripe’s AI GTM strategy and ensure that the world’s leading AI companies -- from early-stage innovators to the largest public players -- choose Stripe as their monetization platform. What you’ll do Work with existing Stripe customers in the AI Industry to develop and execute long-term sales strategies to expand Stripe’s revenue Own the full sales cycle, from business case development, to deal structuring and negotiating, to close Develop account plans and cross sell into your list of strategic AI customers, driving growth through expansion and new revenue streams Drive deal strategy and commercial negotiations for large, complex renewals Develop relationships with executive stakeholders within your book of business, deeply understanding problems they are solving and helping drive to solutions Be responsible for account mapping and coordinating ef

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role Snorkel AI is looking for a Head of Talent Acquisition Operations & Insights to build and lead the systems, processes, tools, metrics, and operational infrastructure that power our recruiting organization. This leader will own the design and execution of a modern TA operations function that enables Snorkel AI to scale hiring with speed, quality, consistency, and data-driven decision-making. This is a builder role for someone who has stood up TA operations in a hyper-growth technical startup environment. You should be equally comfortable designing the strategy, implementing the systems, improving process, building reporting, leading recruiting coordination, and partnering with recruiting and business leaders to improve how hiring gets done. We are looking for someone who brings strong operational discipline, deep knowledge of recruiting systems and workflows, and a forward-looking perspective on how AI can modernize talent acquisition. What You’ll Do Build and lead the TA operations function for Snorkel AI, including recruiting systems, tools, workflows, reporting, process, and coordination. Own the recruiting tech stack, including ATS configu

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Team Marketing at Snorkel is growing rapidly and anchored by high-ownership operators who lead independently, align cross-functionally, and consistently deliver outsized results. We partner across Sales, Product, Research, and the executive team to translate complex AI and data value into differentiated positioning, integrated programs, and field-ready enablement that accelerates growth. The culture is high standards, high autonomy, and high collaboration. About the Role Reporting to the Sr. Director of Product Marketing, the Product Marketing Manager, Frontier Labs will own the GTM execution for our frontier lab business. You will partner closely with Research, FDE, and frontier-facing sales teams to translate technical work into research-credible positioning, repeatable sales plays, and high-quality GTM programs that resonate with research and procurement leaders inside frontier labs. You will keep the frontier asset library (battlecards, technical one-pagers, decks, benchmark and eval narratives) sharp against a fast-moving market, and bring competitive and customer insight into every motion. This is a hands-on role for a product marketer who wants

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About The Role Snorkel is hiring a Head of Security to build and lead our security function end-to-end — infrastructure security, application security, and governance, risk & compliance (GRC). You'll own the security function end-to-end — strategy, team, and execution — and operate as the primary security voice with customers, auditors, and the exec team. You'll report to the CTO. This is a builder's role: you'll take security from its current state to a mature, right-sized function as Snorkel scales, hiring and developing the team as needs grow. Key Responsibilities Security Leadership & Team Building Define Snorkel's overall security strategy,