Ai Knowledge Analyst Jobs

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role Most companies have more GTM ideas than they can reliably execute. Launching a new motion still requires manual targeting, weeks of enablement, seller coordination, and messy measurement. Learnings live in people's heads. When something works — or stops working — the playbook doesn't change fast enough. Ramp is building the AI platform that GTM runs on — a ground-up application layer where agents handle execution, playbooks encode institutional knowledge, and every interaction feeds a learning loop that makes the system smarter each cycle. We're operating at the frontier of what agents can do in a real enterprise context, and the problems are unsolved: reliable background execution at scale, human-agent collaboration that earns trust, and feedback loops that turn raw GTM signal into a compounding organizational advantage. As a PM for Revenue, you'll own the data and execution layer that makes the GTM platform work: the scoring and routing systems that get the right accounts to the right people, the data infrastructure and acquisitions

Scale GP is Scale's enterprise Generative AI platform—APIs and infrastructure for knowledge retrieval, inference, evaluation, and intelligent automation. We power mission-critical workflows for leading enterprises, helping teams turn complex data and models into reliable, production-ready AI systems. We're building a new AI Enablement team to create the next generation of agent-powered tools that ground AI in real operational workflows. Our goal: help internal teams demystify their own workflows, then deploy agentic systems that reason over data, take action, and deliver measurable outcomes. We don't build in a vacuum. You'll use our own platform to solve real business problems internally—then selectively commercialize that same stack for customers. What we run on is what we sell. This is a 0→1 team. We're looking for a sharp, product-minded engineer who thrives in ambiguity, moves fast, and loves building systems from scratch alongside customers and cross-functional partners. You'll work closely with product, forward-deployed engineers, data scientists, and applied AI teams to turn real-world problems into scalable production solutions. If you like shipping fast, owning outcomes, and working across the stack—from polished frontends to distributed backends to LLM integrations—this role is for you. What You’ll Do Own full-stack features and projects end-to-end — from design through production deployment — within a larger product area Sample surfaces - Accounting Agents, Finance Copilots, GTM Agents, Agentic Experimentation Platforms Develop reliable backend services in Typescript/Python, work with distributed systems, data pipelines, and AI/ML infrastructure Integrate LLMs, vector databases, and agentic frameworks to power intelligent workflows Ship quickly through tight experimentation loops while maintaining high quality and reliability Adapt across the stack and learn new tools as needed to solve real problems end-to-end Ideal Experience 3+ years of full-tim

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: As an AI Product Counsel on the Product and IP Legal team, you’ll focus on advising our AI product development team as they build and ship AI functionality—covering everything from product counseling for launches to accelerating AI partnership deals. This role exists because Notion is building the AI workspace that helps every person and team get more done, with intelligence embedded across the tools they use to think, create, and collaborate. We’re bringing frontier intelligence to the “Fortune 5 million,” across an unusually broad surface area (models, workflows, features, and platform). This role is central to that effort. This role reports to our Head of Product and IP Legal and will work closely day-to-day with our Lead AI Product Counsel. This role will be based in San Francisco. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You'll Achieve: Accelerate partnerships for AI product development: collaborate with cross functional st

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role We’re looking for an AI Applications Engineer to help drive Notion’s business transformation efforts. In this role, you’ll be a strategic partner to our internal stakeholders (primarily GTM, Finance and People teams) and deliver and scale creative AI-driven solutions to multi-faceted problems with measurable business impact. You’ll also build reusable components, evaluation patterns, and operational guardrails that make AI delivery repeatable across teams. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You’ll Achieve Work with stakeholders to discover opportunities from ambiguous problem statements, translate them into scoped solutions, and drive iterative releases from idea to adoption Build and ship end‑to‑end AI solutions—from problem framing through data readiness, modeling, evaluation, and production rollout Establish evaluation and production-readiness patterns (met

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

AI Engineer - Enterprise Search Overview We are looking for an experienced Enterprise Search Lead to build and optimize our multi-tenant enterprise search solution. This role focuses on creating scalable systems that integrate seamlessly with customer environments, leveraging cutting-edge AI and ML technologies. You will design and manage the enterprise knowledge graph, implement personalized search experiences, and drive AI- powered innovations to enhance search relevance and ITSM workflows. What You Will Do: Build and structure our enterprise knowledge graph to organize content, people, and activity into meaningful relationships for better search relevance. Develop and refine personalized ranking models that adapt to user behavior and improve search results over time. Design ways to adapt AI language models to each customerʼs data for enhanced accuracy and context. Explore innovative methods to combine LLMs with search engines for answering complex queries Write clean, robust, and maintainable code that integrates smoothly with multi-tenant systems. Collaborate with cross-functional teams to align search capabilities with ITSM workflows. Mentor junior engineers or learn from experienced ones to grow as a technical leader. What You Should Have 3-5 years of experience working on enterprise search products with AI/ML integration. Expertise in multi-tenant systems and securely integrating with external customer systems. Hands-on experience with tools like Elasticsearch, Solr, or similar search platforms. Strong coding skills in Python, Java, or equivalent languages. A passion for solving complex problems with AI and delivering intuitive user experiences. Important notice for candidates: Job scams are on the rise. Please keep these guidelines in mind when applying for any open roles at Atomicwork. Only apply through official Atomicwork channels. We do not use third-party agencies or individuals who ask for payments in exchange for interviews or offer letter

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Backend Engineer on GitLab’s External Agents team, you’ll design and build integrations that bring GitLab agents into tools such as Slack and connect external solutions such as Claude Code or Codex with GitLab. You’ll take end-to-end ownership of complex features, help shape architectural patterns for how GitLab exposes its AI functionality, and collaborate with engineers across the Agent Foundations stage and adjacent AI engineering teams. This is a high-visibility area at the intersection of GitLab’s core platform and AI strategy. What you’ll do Develop, ship, and maintain secure, well-teste

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Software Engineer on the Duo CLI functional team, part of the Developer Clients group within GitLab's AI Clients stage, you'll design and build tools that bring GitLab Duo into developers' daily terminal workflows. You'll shape AI-assisted experiences across GitLab Duo CLI and its supporting infrastructure, working mainly in TypeScript across the frontend and backend and making key architectural decisions about the CLI's future direction. You'll also have opportunities to contribute across Developer Clients, including our JetBrains plugin in Kotlin and our VS Code extension in TypeScript, when

AI/ML Dev - Chatbots • 8+ years of experience in Data/AI Projects • Understanding of end-to-end architecture for Generative AI solutions aligned with business goals. • Experience in Azure OpenAI integration (GPT models, embeddings) with prompt engineering and model tuning. • Programming experience in Python for AI project is a must • Designs scalable RAG systems using Azure AI Search, vector databases, and secure data pipelines. • Knowledge of MLOps and CI/CD workflows using Azure DevOps and automated testing frameworks. • Establishes Python coding standards, reviews code, and mentors development teams. • Knowledge of deployment and governance of AI applications across Azure infrastructure. • Work with cross function teams (IT/ Non IT) to help the development teams build the solutions faster and more efficiently.

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Backend Engineer on the Chat Engine team, you'll build the engine behind GitLab Duo Chat, the conversational AI experience for GitLab. You'll work primarily in Python to build and maintain our agentic runtime: the Flow Registry, LangGraph flows, and the Duo Workflow Service. You'll also work in the GitLab Rails monolith, where Chat connects with the product. You'll own scoped parts of the system, ship small features and improvements with minimal guidance, and collaborate with the team on larger projects. You'll work alongside senior and staff engineers who will partner with you on design and support

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Fullstack Engineer on the Duo Client SDK team at GitLab, you'll build the shared foundation for every GitLab Duo client. Today, the logic that powers Duo in editors lives inside the GitLab Language Server. We're extracting it into a true software development kit (SDK): a set of well-versioned TypeScript packages that editor extensions, our web-based Duo Chat on GitLab.com, and eventually external applications can use. You'll work in TypeScript across frontend and backend systems. You'll design the SDK's Node.js core and public application programming interface (API), and work in the clients that use

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As an AI Transformation Owner at GitLab, you'll shape your function's AI strategy and build the solutions that deliver it. You are the person responsible for identifying where AI can fundamentally change how your org operates, partnering with your Executive Sponsor to align on the biggest challenges, and driving measurable outcomes against them. Think of this as a product management role where the product is your org's way of working. You'll manage the full lifecycle: understanding how work flows today, deciding where AI should reshape it, prioritizing what gets built and in what order, and ensuring what