{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/at/typeform/"},"x-facet":{"type":"company","slug":"typeform","display":"Typeform","count":10},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8daaab94-869"},"title":"Staff AI Engineer - US","description":"<p><strong>Who we are</strong></p>\n<p>Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year,and integrates with essential tools like Slack, Zapier, and Hubspot.</p>\n<p><strong>About the team</strong></p>\n<p>The AI Engineering team builds the systems and capabilities behind Typeform’s AI products, including Research Flow, our platform for combining quantitative research with deeper qualitative insights. We use machine learning, large language models, RAG, and agentic systems to help customers collect, understand, and act on information in more conversational and personalised ways.</p>\n<p><strong>About the role</strong></p>\n<p>As a Staff AI Engineer at Typeform, you will play a central role in shaping the technical direction of Research Flow and the AI systems that support our broader products. You will take ownership of complex engineering challenges that span teams, from defining architecture and testing new approaches to delivering and operating production systems.</p>\n<p><strong>Things you will do</strong></p>\n<p><strong>Shape the technical direction of Research Flow</strong></p>\n<ul>\n<li>Partner with Product and Engineering leaders to translate Research Flow’s product ambitions into a clear technical direction and delivery priorities.</li>\n<li>Lead architectural decisions across AI-assisted study design, adaptive conversations, and research synthesis.</li>\n<li>Identify the technical constraints and dependencies that matter most, and help teams address them early.</li>\n<li>Define how AI capabilities, data flows, and services work together as the product evolves.</li>\n<li>Balance immediate delivery needs with longer-term reliability, scalability, and maintainability.</li>\n</ul>\n<p><strong>Lead and deliver complex AI engineering work</strong></p>\n<ul>\n<li>Take technical ownership of ambiguous problems, from defining the problem and exploring approaches through to production delivery.</li>\n<li>Design and build generative AI applications using large language models, RAG, vector search, tool use, and agentic systems.</li>\n<li>Stay close to implementation through prototyping, production code, design reviews, and debugging.</li>\n<li>Lead initiatives that require coordination across Product, Engineering, Data Science, and Data Engineering.</li>\n<li>Build reusable services and APIs that help product teams deliver AI capabilities consistently.</li>\n<li>Make pragmatic decisions about when to build, buy, simplify, or stop an approach.</li>\n</ul>\n<p><strong>Build scalable AI foundations</strong></p>\n<ul>\n<li>Guide the architecture of machine learning services and workflows using Python, Docker, Kubernetes, and AWS.</li>\n<li>Design reliable pipelines for batch and real-time processing using technologies such as Kafka and Airflow.</li>\n<li>Establish patterns for retrieval, vector search, model orchestration, and working with structured and unstructured data.</li>\n<li>Improve how we manage experiments, model versions, registries, and deployments using tools such as MLflow.</li>\n<li>Identify and resolve performance, reliability, and cost bottlenecks across our AI systems.</li>\n<li>Help teams choose infrastructure and tools that fit the problem and can be operated sustainably.</li>\n</ul>\n<p><strong>Set the standard for AI quality</strong></p>\n<ul>\n<li>Define evaluation strategies and release criteria for generative AI applications, including Research Flow’s conversational and analytical capabilities.</li>\n<li>Guide the development of automated benchmarks covering accuracy, relevance, reliability, fairness, latency, and cost.</li>\n<li>Establish ways to assess whether AI-generated follow-up questions are useful and whether summaries and insights are grounded in participants’ responses.</li>\n<li>Lead improvements to retrieval quality, including chunking, embeddings, context selection, and reranking.</li>\n<li>Connect offline evaluation with production monitoring and customer feedback to guide improvements.</li>\n<li>Build security, privacy, and safeguards against unexpected model behaviour into system design.</li>\n</ul>\n<p><strong>Raise engineering standards across teams</strong></p>\n<ul>\n<li>Establish reusable patterns and technical standards for building, evaluating, deploying, and operating AI systems.</li>\n<li>Help engineers reason through difficult technical decisions and make trade-offs explicit.</li>\n<li>Mentor engineers and support other technical leads in growing their ownership and judgement.</li>\n<li>Improve engineering practices across testing, observability, security, incident response, and deployment.</li>\n<li>Build alignment around technical decisions through clear proposals, constructive discussion, and evidence.</li>\n<li>Evaluate relevant AI research and emerging tools, and help teams adopt what delivers practical value.</li>\n</ul>\n<p><strong>Connect technical work to customer outcomes</strong></p>\n<ul>\n<li>Work with Product and Engineering partners to prioritise AI investments based on customer needs, technical feasibility, and business impact.</li>\n<li>Help define measurable outcomes for AI initiatives and use them to assess whether an approach is working.</li>\n<li>Communicate technical concepts, risks, and trade-offs clearly to technical and nontechnical partners.</li>\n<li>Contribute to planning across teams, making dependencies and sequencing clear.</li>\n<li>Help shape the broader direction of AI at Typeform through lessons learned from building and scaling Research Flow.</li>\n</ul>\n<p><strong>What you bring</strong></p>\n<ul>\n<li>Significant experience building and operating machine learning or AI systems in production, with evidence of technical leadership beyond your own projects.</li>\n<li>A track record of leading complex engineering initiatives across teams, from ambiguous requirements to measurable production outcomes.</li>\n<li>Strong Python and software engineering skills, with the ability to contribute directly to production code.</li>\n<li>Experience designing production services and APIs using frameworks such as FastAPI.</li>\n<li>Practical experience building generative AI applications using large language models, RAG, tool use, or agentic systems.</li>\n<li>A strong understanding of enterprise RAG systems, including retrieval architecture, chunking, embeddings, reranking, evaluation, and monitoring.</li>\n<li>Experience defining evaluation approaches and using evidence to guide model, architecture, and release decisions.</li>\n<li>Experience with frameworks such as PyTorch, LangChain, LangGraph, or similar technologies.</li>\n<li>Strong experience designing and operating cloud systems using AWS, Docker, Kubernetes, Terraform, and continuous integration and deployment practices.</li>\n<li>Familiarity with services such as AWS SageMaker or AWS Bedrock.</li>\n<li>Experience with event-driven processing, vector databases, and machine learning lifecycle tools such as Kafka and MLflow, or comparable technologies.</li>\n<li>Experience establishing observability and diagnosing production issues using tools such as Datadog or OpenSearch.</li>\n<li>Sound judgement when balancing delivery speed, quality, reliability, scalability, security, and cost.</li>\n<li>The ability to influence technical decisions across teams and build alignment without relying on formal authority.</li>\n<li>Experience mentoring engineers and improving the effectiveness of the teams around you.</li>\n</ul>\n<p><strong>Extra awesome</strong></p>\n<ul>\n<li>Experience working in a B2B SaaS product company.</li>\n<li>Experience building conversational AI, adaptive interviewing, or automated analysis and summarisation systems.</li>\n<li>Experience working with text, audio, or video in AI applications.</li>\n<li>Experience evolving shared AI infrastructure or platforms used by multiple product teams.</li>\n<li>Experience with orchestration tools such as Airflow or Argo Workflows.</li>\n<li>Familiarity with SQL, Spark, Snowflake, or other data processing technologies.</li>\n<li>Experience with AI security, privacy, responsible AI, prompt injection protection, or data leakage prevention.</li>\n<li>Experience materially improving the latency, reliability, or cost of AI systems operating at scale.</li>\n</ul>\n<p><strong>Salary information</strong></p>\n<p>No one likes a guessing game , that’s why we&#39;re transparent about the salary range for this role. In addition to the base, we offer a 5-10% bonus depending on your level and performance. The range is broad because we tailor total compensation based on your location, experience, education, and skillset. We also want to ensure equitable pay across the team and alignment with market data , but let us handle those details.</p>\n<p>Pay range $170,000-$210,000 USD</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_8daaab94-869/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://www.typeform.com/","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/8220062?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$170,000-$210,000 USD","x-skills-required":["Python","software engineering","machine learning","AI systems","large language models","RAG","agentic systems","AWS","Docker","Kubernetes","Terraform","FastAPI","PyTorch","LangChain","LangGraph","Kafka","MLflow","Datadog","OpenSearch"],"x-skills-preferred":["B2B SaaS product company","conversational AI","adaptive interviewing","automated analysis and summarisation systems","text, audio, or video in AI applications","shared AI infrastructure","Airflow","Argo Workflows","SQL","Spark","Snowflake","AI security","privacy","responsible AI","prompt injection protection","data leakage prevention"],"datePosted":"2026-10-26T15:03:00.135Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"United States (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, software engineering, machine learning, AI systems, large language models, RAG, agentic systems, AWS, Docker, Kubernetes, Terraform, FastAPI, PyTorch, LangChain, LangGraph, Kafka, MLflow, Datadog, OpenSearch, B2B SaaS product company, conversational AI, adaptive interviewing, automated analysis and summarisation systems, text, audio, or video in AI applications, shared AI infrastructure, Airflow, Argo Workflows, SQL, Spark, Snowflake, AI security, privacy, responsible AI, prompt injection protection, data leakage prevention","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":170000,"maxValue":210000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_09b971ba-bb2"},"title":"Staff AI Engineer - EU","description":"<p><strong>Who we are</strong></p>\n<p>Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year,and integrates with essential tools like Slack, Zapier, and Hubspot.</p>\n<p><strong>About the team</strong></p>\n<p>The AI Engineering team builds the systems and capabilities behind Typeform’s AI products, including Research Flow, our platform for combining quantitative research with deeper qualitative insights. We use machine learning, large language models, RAG, and agentic systems to help customers collect, understand, and act on information in more conversational and personalised ways.</p>\n<p><strong>About the role</strong></p>\n<p>As a Staff AI Engineer at Typeform, you will play a central role in shaping the technical direction of Research Flow and the AI systems that support our broader products. You will take ownership of complex engineering challenges that span teams, from defining architecture and testing new approaches to delivering and operating production systems.</p>\n<p><strong>Responsibilities</strong></p>\n<p><strong>Shape the technical direction of Research Flow</strong></p>\n<ul>\n<li>Partner with Product and Engineering leaders to translate Research Flow’s product ambitions into a clear technical direction and delivery priorities.</li>\n<li>Lead architectural decisions across AI-assisted study design, adaptive conversations, and research synthesis.</li>\n<li>Identify the technical constraints and dependencies that matter most, and help teams address them early.</li>\n<li>Define how AI capabilities, data flows, and services work together as the product evolves.</li>\n<li>Balance immediate delivery needs with longer-term reliability, scalability, and maintainability.</li>\n</ul>\n<p><strong>Lead and deliver complex AI engineering work</strong></p>\n<ul>\n<li>Take technical ownership of ambiguous problems, from defining the problem and exploring approaches through to production delivery.</li>\n<li>Design and build generative AI applications using large language models, RAG, vector search, tool use, and agentic systems.</li>\n<li>Stay close to implementation through prototyping, production code, design reviews, and debugging.</li>\n<li>Lead initiatives that require coordination across Product, Engineering, Data Science, and Data Engineering.</li>\n<li>Build reusable services and APIs that help product teams deliver AI capabilities consistently.</li>\n<li>Make pragmatic decisions about when to build, buy, simplify, or stop an approach.</li>\n</ul>\n<p><strong>Build scalable AI foundations</strong></p>\n<ul>\n<li>Guide the architecture of machine learning services and workflows using Python, Docker, Kubernetes, and AWS.</li>\n<li>Design reliable pipelines for batch and real-time processing using technologies such as Kafka and Airflow.</li>\n<li>Establish patterns for retrieval, vector search, model orchestration, and working with structured and unstructured data.</li>\n<li>Improve how we manage experiments, model versions, registries, and deployments using tools such as MLflow.</li>\n<li>Identify and resolve performance, reliability, and cost bottlenecks across our AI systems.</li>\n<li>Help teams choose infrastructure and tools that fit the problem and can be operated sustainably.</li>\n</ul>\n<p><strong>Set the standard for AI quality</strong></p>\n<ul>\n<li>Define evaluation strategies and release criteria for generative AI applications, including Research Flow’s conversational and analytical capabilities.</li>\n<li>Guide the development of automated benchmarks covering accuracy, relevance, reliability, fairness, latency, and cost.</li>\n<li>Establish ways to assess whether AI-generated follow-up questions are useful and whether summaries and insights are grounded in participants’ responses.</li>\n<li>Lead improvements to retrieval quality, including chunking, embeddings, context selection, and reranking.</li>\n<li>Connect offline evaluation with production monitoring and customer feedback to guide improvements.</li>\n<li>Build security, privacy, and safeguards against unexpected model behaviour into system design.</li>\n</ul>\n<p><strong>Raise engineering standards across teams</strong></p>\n<ul>\n<li>Establish reusable patterns and technical standards for building, evaluating, deploying, and operating AI systems.</li>\n<li>Help engineers reason through difficult technical decisions and make trade-offs explicit.</li>\n<li>Mentor engineers and support other technical leads in growing their ownership and judgement.</li>\n<li>Improve engineering practices across testing, observability, security, incident response, and deployment.</li>\n<li>Build alignment around technical decisions through clear proposals, constructive discussion, and evidence.</li>\n<li>Evaluate relevant AI research and emerging tools, and help teams adopt what delivers practical value.</li>\n</ul>\n<p><strong>Connect technical work to customer outcomes</strong></p>\n<ul>\n<li>Work with Product and Engineering partners to prioritise AI investments based on customer needs, technical feasibility, and business impact.</li>\n<li>Help define measurable outcomes for AI initiatives and use them to assess whether an approach is working.</li>\n<li>Communicate technical concepts, risks, and trade-offs clearly to technical and nontechnical partners.</li>\n<li>Contribute to planning across teams, making dependencies and sequencing clear.</li>\n<li>Help shape the broader direction of AI at Typeform through lessons learned from building and scaling Research Flow.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Significant experience building and operating machine learning or AI systems in production, with evidence of technical leadership beyond your own projects.</li>\n<li>A track record of leading complex engineering initiatives across teams, from ambiguous requirements to measurable production outcomes.</li>\n<li>Strong Python and software engineering skills, with the ability to contribute directly to production code.</li>\n<li>Experience designing production services and APIs using frameworks such as FastAPI.</li>\n<li>Practical experience building generative AI applications using large language models, RAG, tool use, or agentic systems.</li>\n<li>A strong understanding of enterprise RAG systems, including retrieval architecture, chunking, embeddings, reranking, evaluation, and monitoring.</li>\n<li>Experience defining evaluation approaches and using evidence to guide model, architecture, and release decisions.</li>\n<li>Experience with frameworks such as PyTorch, LangChain, LangGraph, or similar technologies.</li>\n<li>Strong experience designing and operating cloud systems using AWS, Docker, Kubernetes, Terraform, and continuous integration and deployment practices.</li>\n<li>Familiarity with services such as AWS SageMaker or AWS Bedrock.</li>\n<li>Experience with event-driven processing, vector databases, and machine learning lifecycle tools such as Kafka and MLflow, or comparable technologies.</li>\n<li>Experience establishing observability and diagnosing production issues using tools such as Datadog or OpenSearch.</li>\n<li>Sound judgement when balancing delivery speed, quality, reliability, scalability, security, and cost.</li>\n<li>The ability to influence technical decisions across teams and build alignment without relying on formal authority.</li>\n<li>Experience mentoring engineers and improving the effectiveness of the teams around you.</li>\n</ul>\n<p><strong>Nice to have</strong></p>\n<ul>\n<li>Experience working in a B2B SaaS product company.</li>\n<li>Experience building conversational AI, adaptive interviewing, or automated analysis and summarisation systems.</li>\n<li>Experience working with text, audio, or video in AI applications.</li>\n<li>Experience evolving shared AI infrastructure or platforms used by multiple product teams.</li>\n<li>Experience with orchestration tools such as Airflow or Argo Workflows.</li>\n<li>Familiarity with SQL, Spark, Snowflake, or other data processing technologies.</li>\n<li>Experience with AI security, privacy, responsible AI, prompt injection protection, or data leakage prevention.</li>\n<li>Experience materially improving the latency, reliability, or cost of AI systems operating at scale.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_09b971ba-bb2/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://www.typeform.com/","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/8220052?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","machine learning","large language models","RAG","agentic systems","AWS","Docker","Kubernetes","Terraform","FastAPI","PyTorch","LangChain","LangGraph","Kafka","MLflow","Datadog","OpenSearch"],"x-skills-preferred":["B2B SaaS product company","conversational AI","adaptive interviewing","automated analysis and summarisation systems","text, audio, or video in AI applications","shared AI infrastructure or platforms","Airflow","Argo Workflows","SQL","Spark","Snowflake","AI security","privacy","responsible AI","prompt injection protection","data leakage prevention"],"datePosted":"2026-10-26T14:58:16.518Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"United Kingdom (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, machine learning, large language models, RAG, agentic systems, AWS, Docker, Kubernetes, Terraform, FastAPI, PyTorch, LangChain, LangGraph, Kafka, MLflow, Datadog, OpenSearch, B2B SaaS product company, conversational AI, adaptive interviewing, automated analysis and summarisation systems, text, audio, or video in AI applications, shared AI infrastructure or platforms, Airflow, Argo Workflows, SQL, Spark, Snowflake, AI security, privacy, responsible AI, prompt injection protection, data leakage prevention"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_5872a3ac-0c3"},"title":"Senior Paid Marketing Strategist","description":"<p>Typeform is seeking a Senior Paid Marketing Strategist to help rethink its approach to paid acquisition. The successful candidate will own and grow key channels including TikTok, YouTube, Google Performance Max, and Uber Ads, while testing new opportunities across areas such as audio and CTV.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Own the strategy and day-to-day performance of key paid social and display channels</li>\n<li>Build a multichannel strategy to reduce reliance on paid search and find new sources of efficient growth</li>\n<li>Manage six-figure monthly media budgets based on customer acquisition, revenue, CAC, and LTV to CAC performance</li>\n<li>Build, launch, and optimise campaigns that drive Typeform signups and new paid customers</li>\n<li>Turn creative ideas into campaigns by briefing and partnering with copywriters and designers</li>\n<li>Run A/B tests across creative, copy, landing pages, placements, audiences, and bidding strategies</li>\n<li>Explore and test new channels such as audio and CTV</li>\n<li>Develop and own the paid marketing measurement approach, including Marketing Mix Modelling and incrementality studies</li>\n<li>Design experiments to understand the incremental impact of campaigns</li>\n<li>Work closely with the Tracking and Data teams to strengthen measurement capabilities</li>\n<li>Share insights, results, and recommendations across Marketing and the wider business</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>Around six or more years of hands-on and strategic experience in performance marketing and media buying</li>\n<li>Strong experience managing paid social and video channels, ideally including TikTok, YouTube, and Meta</li>\n<li>Experience owning campaigns from initial idea and creative brief through implementation, optimisation, and measurement</li>\n<li>A track record of managing six-figure budgets and delivering efficient performance</li>\n<li>Experience working with MMM, incrementality testing, or other measurement methods</li>\n<li>Strong analytical skills and confidence working with campaign performance, conversion funnels, CAC, and LTV</li>\n<li>A strong understanding of digital measurement, from tagging and attribution through to incrementality</li>\n<li>Experience developing creative and UGC assets for paid social channels</li>\n<li>The ability to balance creative thinking with strong commercial judgement</li>\n<li>Curiosity and a willingness to figure things out</li>\n<li>Confidence working across teams and influencing partners</li>\n<li>Comfort operating with uncertainty</li>\n</ul>\n<p>Nice to have:</p>\n<ul>\n<li>Experience working in SaaS or B2B lead generation</li>\n<li>Experience across sales technology or marketing technology</li>\n<li>Experience managing external agencies or digital production partners</li>\n<li>Experience with ad servers and campaign trafficking</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_5872a3ac-0c3/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://www.typeform.com","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/8134637?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["performance marketing","media buying","paid social","video channels","TikTok","YouTube","Meta","Marketing Mix Modelling","incrementality testing","digital measurement","campaign performance","conversion funnels","CAC","LTV"],"x-skills-preferred":["SaaS","B2B lead generation","sales technology","marketing technology","ad servers","campaign trafficking"],"datePosted":"2026-10-26T14:57:35.517Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Germany (Remote) ; Ireland (Remote); Netherlands (Remote) ; Portugal (Remote) ; Spain (Remote) ; United Kingdom (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Marketing","industry":"Technology","skills":"performance marketing, media buying, paid social, video channels, TikTok, YouTube, Meta, Marketing Mix Modelling, incrementality testing, digital measurement, campaign performance, conversion funnels, CAC, LTV, SaaS, B2B lead generation, sales technology, marketing technology, ad servers, campaign trafficking"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cc84699a-83e"},"title":"Senior AI Engineer - US","description":"<p><strong>Who we are</strong></p>\n<p>Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year,and integrates with essential tools like Slack, Zapier, and Hubspot.</p>\n<p><strong>About the team</strong></p>\n<p>The AI Engineering team builds the systems and capabilities behind Typeform’s AI products, including Research Flow, our platform for combining quantitative research with deeper qualitative insights. We use machine learning, large language models, RAG, and agentic systems to help customers collect, understand, and act on information in more conversational and personalised ways.</p>\n<p><strong>About the role</strong></p>\n<p>As a Senior AI Engineer at Typeform, you will be instrumental in building and evolving the AI capabilities behind Research Flow, alongside our broader AI products. Your work will help customers understand the “why” behind responses and move from research questions to informed decisions faster.</p>\n<p><strong>Responsibilities</strong></p>\n<p><strong>Build and deliver AI products</strong></p>\n<ul>\n<li>Design, build, and deploy generative AI capabilities across Typeform’s products, with a key contribution to Research Flow.</li>\n<li>Develop applications using large language models, RAG, vector search, and agentic systems.</li>\n<li>Build services and APIs that allow product teams to integrate AI capabilities into customer experiences.</li>\n<li>Turn prototypes into reliable production systems with clear measures of performance and quality.</li>\n<li>Explore new ways for customers to collect, understand, and act on information using AI.</li>\n</ul>\n<p><strong>Build scalable AI systems</strong></p>\n<ul>\n<li>Design and operate machine learning services and workflows using Python, Docker, Kubernetes, and AWS.</li>\n<li>Build reliable pipelines for batch and real time processing using technologies such as Kafka and Airflow.</li>\n<li>Design solutions using vector databases to support retrieval, recommendations, personalisation, and semantic search.</li>\n<li>Use MLflow to manage experiments, model versions, registries, and deployments.</li>\n<li>Improve the reliability, performance, scalability, and cost efficiency of our AI systems.</li>\n</ul>\n<p><strong>Evaluate and improve AI quality</strong></p>\n<ul>\n<li>Build automated evaluation pipelines for generative AI applications, including the conversational and analytical capabilities behind Research Flow.</li>\n<li>Develop benchmarks that measure accuracy, relevance, reliability, fairness, latency, and cost.</li>\n<li>Evaluate retrieval strategies, including chunking, embeddings, context selection, and reranking.</li>\n<li>Monitor AI systems in production and identify opportunities to improve their quality and performance.</li>\n<li>Create safeguards that reduce unexpected behaviour and protect customer data.</li>\n</ul>\n<p><strong>Shape our AI engineering practice</strong></p>\n<ul>\n<li>Establish reusable patterns and technical standards for building, evaluating, and releasing AI systems.</li>\n<li>Help teams make informed decisions about models, frameworks, infrastructure, performance, and cost.</li>\n<li>Apply strong engineering practices across testing, security, observability, version control, and deployment.</li>\n<li>Share technical knowledge and support the development of other engineers.</li>\n<li>Keep up with relevant AI research, tools, and engineering practices, applying what is useful to Typeform.</li>\n</ul>\n<p><strong>Collaborate across Typeform</strong></p>\n<ul>\n<li>Partner with Product, Engineering, Data Science, Data Engineering, and Analytics teams to connect AI investments with customer and business needs.</li>\n<li>Work with Data Scientists to turn experiments and models into reliable production services.</li>\n<li>Communicate technical concepts, risks, and tradeoffs clearly to technical and nontechnical partners.</li>\n<li>Contribute to technical planning and help shape the direction of AI across Typeform.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>At least four years of experience building and deploying machine learning or AI systems in production.</li>\n<li>Strong Python and software engineering skills.</li>\n<li>Experience building production services using Python frameworks such as FastAPI.</li>\n<li>Practical experience developing generative AI applications using large language models, RAG, tool use, or agentic systems.</li>\n<li>Experience with frameworks such as PyTorch, LangChain, LangGraph, or similar technologies.</li>\n<li>A strong understanding of enterprise RAG systems, including chunking, embeddings, retrieval, reranking, evaluation, and monitoring.</li>\n<li>Experience creating automated evaluations for generative AI applications.</li>\n<li>Experience with AWS, Docker, Kubernetes, Terraform, and continuous integration and deployment practices.</li>\n<li>Experience using services such as AWS SageMaker or AWS Bedrock.</li>\n<li>Experience with Kafka, vector databases, or other technologies used for real time and high dimensional data processing.</li>\n<li>Experience managing machine learning workflows using MLflow.</li>\n<li>Experience monitoring production systems with tools such as Datadog or OpenSearch.</li>\n<li>The ability to balance quality, speed, reliability, scalability, and cost when making technical decisions.</li>\n<li>Strong communication skills and experience collaborating with Product, Engineering, and Data teams.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_cc84699a-83e/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://typeform.com","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/8220046?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","software engineering","machine learning","AI systems","large language models","RAG","agentic systems","PyTorch","LangChain","LangGraph","AWS","Docker","Kubernetes","Terraform","MLflow","Datadog","OpenSearch","Kafka","vector databases"],"x-skills-preferred":["Experience working in a B2B SaaS product company","orchestration tools","SQL","Spark","Snowflake","data processing technologies","AI security","privacy","responsible AI","prompt injection protection","data leakage prevention"],"datePosted":"2026-10-26T14:57:16.737Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"United States (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, software engineering, machine learning, AI systems, large language models, RAG, agentic systems, PyTorch, LangChain, LangGraph, AWS, Docker, Kubernetes, Terraform, MLflow, Datadog, OpenSearch, Kafka, vector databases, Experience working in a B2B SaaS product company, orchestration tools, SQL, Spark, Snowflake, data processing technologies, AI security, privacy, responsible AI, prompt injection protection, data leakage prevention"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_3d2f708d-d2a"},"title":"Senior AI Engineer - EU","description":"<p><strong>Who we are</strong></p>\n<p>Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year,and integrates with essential tools like Slack, Zapier, and Hubspot.</p>\n<p><strong>About the team</strong></p>\n<p>The AI Engineering team builds the systems and capabilities behind Typeform’s AI products, including Research Flow, our platform for combining quantitative research with deeper qualitative insights. We use machine learning, large language models, RAG, and agentic systems to help customers collect, understand, and act on information in more conversational and personalised ways.</p>\n<p><strong>About the role</strong></p>\n<p>As a Senior AI Engineer at Typeform, you will be instrumental in building and evolving the AI capabilities behind Research Flow, alongside our broader AI products. Your work will help customers understand the “why” behind responses and move from research questions to informed decisions faster.</p>\n<p><strong>Responsibilities</strong></p>\n<p><strong>Build and deliver AI products</strong></p>\n<ul>\n<li>Design, build, and deploy generative AI capabilities across Typeform’s products, with a key contribution to Research Flow.</li>\n<li>Develop applications using large language models, RAG, vector search, and agentic systems.</li>\n<li>Build services and APIs that allow product teams to integrate AI capabilities into customer experiences.</li>\n<li>Turn prototypes into reliable production systems with clear measures of performance and quality.</li>\n<li>Explore new ways for customers to collect, understand, and act on information using AI.</li>\n</ul>\n<p><strong>Build scalable AI systems</strong></p>\n<ul>\n<li>Design and operate machine learning services and workflows using Python, Docker, Kubernetes, and AWS.</li>\n<li>Build reliable pipelines for batch and real time processing using technologies such as Kafka and Airflow.</li>\n<li>Design solutions using vector databases to support retrieval, recommendations, personalisation, and semantic search.</li>\n<li>Use MLflow to manage experiments, model versions, registries, and deployments.</li>\n<li>Improve the reliability, performance, scalability, and cost efficiency of our AI systems.</li>\n</ul>\n<p><strong>Evaluate and improve AI quality</strong></p>\n<ul>\n<li>Build automated evaluation pipelines for generative AI applications, including the conversational and analytical capabilities behind Research Flow.</li>\n<li>Develop benchmarks that measure accuracy, relevance, reliability, fairness, latency, and cost.</li>\n<li>Evaluate retrieval strategies, including chunking, embeddings, context selection, and reranking.</li>\n<li>Monitor AI systems in production and identify opportunities to improve their quality and performance.</li>\n<li>Create safeguards that reduce unexpected behaviour and protect customer data.</li>\n</ul>\n<p><strong>Shape our AI engineering practice</strong></p>\n<ul>\n<li>Establish reusable patterns and technical standards for building, evaluating, and releasing AI systems.</li>\n<li>Help teams make informed decisions about models, frameworks, infrastructure, performance, and cost.</li>\n<li>Apply strong engineering practices across testing, security, observability, version control, and deployment.</li>\n<li>Share technical knowledge and support the development of other engineers.</li>\n<li>Keep up with relevant AI research, tools, and engineering practices, applying what is useful to Typeform.</li>\n</ul>\n<p><strong>Collaborate across Typeform</strong></p>\n<ul>\n<li>Partner with Product, Engineering, Data Science, Data Engineering, and Analytics teams to connect AI investments with customer and business needs.</li>\n<li>Work with Data Scientists to turn experiments and models into reliable production services.</li>\n<li>Communicate technical concepts, risks, and tradeoffs clearly to technical and nontechnical partners.</li>\n<li>Contribute to technical planning and help shape the direction of AI across Typeform.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>At least four years of experience building and deploying machine learning or AI systems in production.</li>\n<li>Strong Python and software engineering skills.</li>\n<li>Experience building production services using Python frameworks such as FastAPI.</li>\n<li>Practical experience developing generative AI applications using large language models, RAG, tool use, or agentic systems.</li>\n<li>Experience with frameworks such as PyTorch, LangChain, LangGraph, or similar technologies.</li>\n<li>A strong understanding of enterprise RAG systems, including chunking, embeddings, retrieval, reranking, evaluation, and monitoring.</li>\n<li>Experience creating automated evaluations for generative AI applications.</li>\n<li>Experience with AWS, Docker, Kubernetes, Terraform, and continuous integration and deployment practices.</li>\n<li>Experience using services such as AWS SageMaker or AWS Bedrock.</li>\n<li>Experience with Kafka, vector databases, or other technologies used for real time and high dimensional data processing.</li>\n<li>Experience managing machine learning workflows using MLflow.</li>\n<li>Experience monitoring production systems with tools such as Datadog or OpenSearch.</li>\n<li>The ability to balance quality, speed, reliability, scalability, and cost when making technical decisions.</li>\n<li>Strong communication skills and experience collaborating with Product, Engineering, and Data teams.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_3d2f708d-d2a/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://www.typeform.com/","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/8185412?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","software engineering","machine learning","AI","large language models","RAG","agentic systems","AWS","Docker","Kubernetes","Terraform","MLflow","Kafka","vector databases","FastAPI","PyTorch","LangChain","LangGraph"],"x-skills-preferred":["orchestration tools","Airflow","Argo Workflows","SQL","Spark","Snowflake","data processing technologies","AI security","privacy","responsible AI","prompt injection protection","data leakage prevention"],"datePosted":"2026-10-26T14:56:40.786Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Germany (Remote) ; Ireland (Remote); Netherlands (Remote) ; Portugal (Remote) ; Spain (Remote) ; United Kingdom (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, software engineering, machine learning, AI, large language models, RAG, agentic systems, AWS, Docker, Kubernetes, Terraform, MLflow, Kafka, vector databases, FastAPI, PyTorch, LangChain, LangGraph, orchestration tools, Airflow, Argo Workflows, SQL, Spark, Snowflake, data processing technologies, AI security, privacy, responsible AI, prompt injection protection, data leakage prevention"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f2c4252a-8ed"},"title":"Senior Account Executive","description":"<p><strong>Job Description</strong></p>\n<p>We&#39;re a refreshingly different form builder, helping over 150,000 businesses collect data with enjoyable forms, surveys, and quizzes. Our goal is to grow our sales presence in London.</p>\n<p>As a Senior Account Executive, you&#39;ll be a key driver of our outbound engine, owning the full sales cycle, and thriving on proactive outreach. You&#39;ll focus on Mid-Market and Enterprise customers, generating leads, qualifying prospects, and closing deals.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Conduct outreach and engagement through email, cold calls, conferences, and more</li>\n<li>Generate leads and build a consistent outbound sales pipeline</li>\n<li>Qualify and close new customers, building proposals and ROI cases</li>\n<li>Improve internal sales processes and run weekly Sales Review meetings</li>\n<li>Collaborate with Customer Success, Engineering, and Product teams</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>5-8+ years of quota-carrying experience in B2B SaaS</li>\n<li>Experience selling into enterprise or upper mid-market accounts</li>\n<li>Proven ability to run consultative sales cycles and close meaningful deals</li>\n<li>Strong discovery and storytelling skills</li>\n<li>Ability to balance inbound and outbound pipeline generation</li>\n</ul>\n<p><strong>What We Offer</strong></p>\n<ul>\n<li>Opportunity to work with a growing company</li>\n<li>Collaborative and transparent work environment</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_f2c4252a-8ed/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://www.typeform.com","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/8208256?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["B2B SaaS sales","consultative sales","lead generation","pipeline management","CRM workflows"],"x-skills-preferred":[],"datePosted":"2026-10-26T14:55:52.567Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Sales","industry":"Technology","skills":"B2B SaaS sales, consultative sales, lead generation, pipeline management, CRM workflows"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2c7357c0-dd5"},"title":"Senior Account Executive","description":"<p><strong>Job Description</strong></p>\n<p>We&#39;re a refreshingly different form builder, helping over 150,000 businesses collect data with enjoyable forms, surveys, and quizzes. Our goal is to drive 500 million responses yearly, integrating with key tools like Slack, Zapier, and Hubspot.</p>\n<p><strong>About The Role</strong></p>\n<p>As a Senior Account Executive at Typeform, you&#39;ll play a crucial role in our sales team, operating with a start-up mindset within a scaling company. You&#39;ll report directly to the Head of Sales and be a key driver of our outbound sales engine. Your focus will be on strategic selling, owning the full sales cycle, and thriving in proactive outreach.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Outreach and engagement: Contact leads via various channels, manage inbound and referral leads.</li>\n<li>Lead generation and prospecting: Research potential customers, generate leads, and build a consistent outbound sales pipeline.</li>\n<li>Qualification and closing: Run discovery calls, demos, and follow-ups to qualify and close new customers.</li>\n<li>Process improvement: Enhance internal sales processes and run weekly &#39;Sales Review&#39; meetings.</li>\n<li>Cross-team work: Collaborate with Customer Success, Engineering, and Product teams.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>5–8+ years of quota-carrying closing experience in B2B SaaS.</li>\n<li>Experience selling into enterprise or upper mid-market accounts.</li>\n<li>Proven ability to run consultative, multi-stakeholder sales cycles.</li>\n<li>Track record of closing significant deals and expanding accounts.</li>\n<li>Strong discovery and storytelling skills.</li>\n<li>Ability to balance inbound and outbound pipeline generation.</li>\n<li>Highly organized and proactive in managing deals.</li>\n</ul>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>Salary range: $180,000-$240,000 USD.</li>\n<li>Bonus: 5-10%, depending on level and performance.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_2c7357c0-dd5/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://www.typeform.com/","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/8207823?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$180,000-$240,000 USD","x-skills-required":["B2B SaaS sales","strategic selling","outbound sales","lead generation","prospecting","consultative sales","multi-stakeholder sales","discovery calls","storytelling"],"x-skills-preferred":[],"datePosted":"2026-10-26T14:55:23.564Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Sales","industry":"Technology","skills":"B2B SaaS sales, strategic selling, outbound sales, lead generation, prospecting, consultative sales, multi-stakeholder sales, discovery calls, storytelling","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":240000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_cf5f92d8-106"},"title":"Senior Account Executive","description":"<p><strong>Job Description</strong></p>\n<p>We&#39;re a refreshingly different form builder, helping over 150,000 businesses collect data with enjoyable forms, surveys, and quizzes. Our goal is to drive 500 million responses yearly, integrating with key tools like Slack, Zapier, and Hubspot.</p>\n<p><strong>About The Role</strong></p>\n<p>As a Senior Account Executive at Typeform, you&#39;ll play a crucial role in our sales team, operating with a start-up mindset within a scaling company. You&#39;ll report directly to the Head of Sales and be a key driver of our outbound sales efforts.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Outreach and engagement: Contact leads via email, cold calls, conferences, and more, managing inbound and referral leads.</li>\n<li>Lead generation and prospecting: Research potential customers, generate leads, and build a consistent outbound sales pipeline by attending industry events and developing connections.</li>\n<li>Qualification and closing: Run discovery calls, demos, and follow-ups to qualify and close new customers, build proposals, and negotiate contract terms when needed.</li>\n<li>Process improvement: Enhance our internal sales processes, run weekly &#39;Sales Review&#39; meetings, and collaborate with teams to delight customers.</li>\n<li>Cross-team work: Collaborate with Customer Success, Engineering, and Product teams.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>5–8+ years of quota-carrying closing experience in B2B SaaS.</li>\n<li>Experience selling into enterprise or upper mid-market accounts.</li>\n<li>Proven ability to run consultative, multi-stakeholder sales cycles.</li>\n<li>Track record of closing meaningful deals ($50K–$250K+) and expanding accounts.</li>\n<li>Strong discovery and storytelling skills.</li>\n<li>Comfortable balancing inbound and outbound pipeline generation.</li>\n<li>Highly organized and proactive in managing deals end-to-end.</li>\n</ul>\n<p><strong>Compensation</strong></p>\n<p>The salary range for this role is $180,000-$240,000 USD, with a 5-10% bonus depending on your level and performance.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_cf5f92d8-106/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://www.typeform.com","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/8208253?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$180,000-$240,000 USD","x-skills-required":["B2B SaaS sales","consultative sales","multi-stakeholder sales","pipeline generation","sales process improvement"],"x-skills-preferred":[],"datePosted":"2026-10-26T14:54:50.920Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Sales","industry":"Technology","skills":"B2B SaaS sales, consultative sales, multi-stakeholder sales, pipeline generation, sales process improvement","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":240000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_4f9a9657-4ce"},"title":"Full Stack Developer","description":"<p><strong>Who we are</strong></p>\n<p>Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year,and integrates with essential tools like Slack, Zapier, and Hubspot.</p>\n<p>Typeform is fully remote by design. For this role, we can hire candidates based in the UK, Ireland, Germany, Portugal, Spain or The Netherlands</p>\n<p><strong>About the team</strong></p>\n<p>This team sits at the center of how Typeform builds product experiences, creating the shared foundations, tooling, and infrastructure that support scalable and consistent development across the platform.</p>\n<p><strong>About the role</strong></p>\n<p>We’re looking for a Mid level Full Stack Engineer with a stronger backend focus to help evolve the internal systems and infrastructure that support our product development ecosystem.</p>\n<p>This role is ideal for someone who enjoys building scalable internal platforms and developer tooling, while still being comfortable contributing across the frontend when needed. You’ll work on APIs, automation, release pipelines, and engineering infrastructure that improve how teams build and ship product experiences across Typeform.</p>\n<p>You’ll partner closely with engineers and designers to improve tooling, workflows, and developer experience across the company.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Build and maintain backend services, APIs, and internal tooling used across product development teams</li>\n</ul>\n<ul>\n<li>Improve infrastructure powering component distribution, asset management, documentation, and release workflows</li>\n</ul>\n<ul>\n<li>Support and evolve the engineering monorepo, helping improve scalability, maintainability, and developer experience</li>\n</ul>\n<ul>\n<li>Collaborate with frontend engineers and designers to ensure shared patterns and tooling are implemented consistently across products</li>\n</ul>\n<ul>\n<li>Contribute to CI/CD pipelines, automation, testing, and deployment processes using tools like GitHub Actions</li>\n</ul>\n<ul>\n<li>Help improve the reliability and performance of internal systems, including observability and monitoring workflows</li>\n</ul>\n<ul>\n<li>Support engineers across product teams with adoption and integration of shared tooling and services</li>\n</ul>\n<ul>\n<li>Contribute to documentation and developer tooling to improve discoverability and onboarding</li>\n</ul>\n<ul>\n<li>Work on ongoing platform improvements, including:</li>\n</ul>\n<ul>\n<li>Migration of legacy code and tooling</li>\n</ul>\n<ul>\n<li>Documentation platform enhancements</li>\n</ul>\n<ul>\n<li>Automation improvements</li>\n</ul>\n<ul>\n<li>Sandbox and developer tooling improvements</li>\n</ul>\n<ul>\n<li>Participate in architecture discussions and contribute practical, scalable engineering solutions</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Experience working with JavaScript or TypeScript in production environments</li>\n</ul>\n<ul>\n<li>Good understanding of backend development principles and experience building APIs or internal services</li>\n</ul>\n<ul>\n<li>Familiarity with Node.js and modern web frameworks such as React or Next.js</li>\n</ul>\n<ul>\n<li>Experience working with relational databases and understanding of database design fundamentals</li>\n</ul>\n<ul>\n<li>Understanding of testing practices and software quality principles</li>\n</ul>\n<ul>\n<li>Familiarity with CI/CD workflows and developer tooling</li>\n</ul>\n<ul>\n<li>Experience working with Git and collaborative engineering workflows</li>\n</ul>\n<ul>\n<li>Strong communication skills and the ability to work cross functionally with designers and engineers</li>\n</ul>\n<ul>\n<li>Interest in developer experience, platform engineering, or internal tooling</li>\n</ul>\n<p><strong>Nice to have</strong></p>\n<ul>\n<li>Experience working in a product led SaaS company</li>\n</ul>\n<ul>\n<li>Exposure to frontend infrastructure or shared platform tooling</li>\n</ul>\n<ul>\n<li>Familiarity with observability and monitoring tooling</li>\n</ul>\n<ul>\n<li>Experience contributing to monorepos or internal platform tooling</li>\n</ul>\n<ul>\n<li>Degree in Computer Science or a related technical field</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_4f9a9657-4ce/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://www.typeform.com","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/7942504?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["JavaScript","TypeScript","Node.js","React","Next.js","Git","CI/CD workflows","API development","Database design"],"x-skills-preferred":["Experience working in a product led SaaS company","Exposure to frontend infrastructure or shared platform tooling","Familiarity with observability and monitoring tooling","Experience contributing to monorepos or internal platform tooling","Degree in Computer Science or a related technical field"],"datePosted":"2026-10-26T14:54:26.382Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Germany (Remote) ; Ireland (Remote); Netherlands (Remote) ; Portugal (Remote) ; Spain (Remote) ; United Kingdom (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"JavaScript, TypeScript, Node.js, React, Next.js, Git, CI/CD workflows, API development, Database design, Experience working in a product led SaaS company, Exposure to frontend infrastructure or shared platform tooling, Familiarity with observability and monitoring tooling, Experience contributing to monorepos or internal platform tooling, Degree in Computer Science or a related technical field"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_319d92bb-602"},"title":"AI Product Operations Lead","description":"<p><strong>Who we are</strong></p>\n<p>Typeform is a refreshingly different form builder. We help over 150,000 businesses collect the data they need with forms, surveys, and quizzes that people enjoy. Designed to look striking and feel effortless to fill out, Typeform drives 500 million responses every year,and integrates with essential tools like Slack, Zapier, and Hubspot.</p>\n<p><strong>About the team</strong></p>\n<p>Product Operations sits at the center of how our Product and wider R&amp;D teams work. We help create the systems, practices, and connections that allow teams to focus on solving the right problems and delivering great products. AI is becoming an increasingly important part of that work. Across R&amp;D, teams are already experimenting with tools like Glean and Claude, building automations, testing agents, and finding new ways to use AI throughout the product development lifecycle.</p>\n<p><strong>About the role</strong></p>\n<p>We&#39;re looking for an AI Product Operations Lead to build and operate the internal AI Operations capability for R&amp;D. This is a hands-on role for someone who can take an ambiguous opportunity and turn it into a reliable, adopted solution. You&#39;ll help us identify the highest-value problems AI can solve, understand how people work today, design the right solution, build or coordinate its delivery, and then stay accountable for how it performs after launch.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Build and continuously improve our backlog of AI opportunities across R&amp;D, helping teams identify, prioritize, and sequence the jobs where AI can have the greatest impact.</li>\n<li>Take ambiguous problems from initial discovery through to delivery: understand the user and workflow, explore options and trade-offs, design the right system, build or coordinate implementation, test, document, launch, measure, and improve.</li>\n<li>Design simple, AI-native solutions that fit naturally into how people work.</li>\n<li>Help R&amp;D get more value from enterprise AI tools such as Glean and Claude, partnering with IT and InfoSec on areas including access, configuration, connectors, enablement, and support.</li>\n<li>Own the lifecycle of the AI systems within your portfolio, including automations, skills, agents, and internal web applications.</li>\n<li>Establish practical approaches to evaluation, testing, reliability, observability, security, and maintenance,using evidence and feedback to improve systems over time.</li>\n<li>Partner with teams across R&amp;D to uncover needs, unblock delivery, clarify ownership, and bring the right experts into the work.</li>\n<li>Help run and evolve our R&amp;D AI governance and enablement practices, giving leaders better visibility into active work, risks, adoption, and outcomes.</li>\n<li>Participate in Typeform&#39;s broader AI governance efforts as an R&amp;D contributor.</li>\n<li>Work with Finance and other partners to improve visibility into AI tool usage, spend, and value, helping inform investment decisions.</li>\n<li>Explore and support the development of autonomous agents that can improve how we plan, discover, design, build, evaluate, and manage work across the product development lifecycle.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Strong practical experience applying AI to real-world problems,not just experimenting with models, but building solutions that people actually use.</li>\n<li>A track record of taking ambiguous problems from discovery through implementation, testing, adoption, and ongoing improvement.</li>\n<li>Excellent systems thinking.</li>\n<li>Strong user and workflow discovery skills.</li>\n<li>Hands-on technical fluency and comfort building, modifying, and troubleshooting internal workflows, automations, agents, or applications.</li>\n<li>Practical experience with modern development practices and tools such as GitHub, repositories and pull requests, basic application hosting, deployment, logging, and operational troubleshooting.</li>\n<li>Experience managing work independently: prioritizing a backlog, handling dependencies and risks, documenting decisions, and communicating clearly with stakeholders.</li>\n<li>A strong approach to evaluation and reliability.</li>\n<li>The ability to work effectively across technical and non-technical teams.</li>\n<li>Good judgment around responsible AI, security, access, and governance, and an understanding of when to bring in the right partners.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_319d92bb-602/","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Typeform","sameAs":"https://www.typeform.com/","logo":"https://logos.yubhub.co/typeform.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/typeform/jobs/8184931?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["AI","Product Operations","Systems Thinking","User Discovery","Technical Execution","Operational Ownership"],"x-skills-preferred":[],"datePosted":"2026-10-26T14:53:51.143Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Germany (Remote) ; Ireland (Remote); Netherlands (Remote) ; Portugal (Remote) ; Spain (Remote) ; United Kingdom (Remote)"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Product Management","industry":"Technology","skills":"AI, Product Operations, Systems Thinking, User Discovery, Technical Execution, Operational Ownership"}]}