Content And Copy Manager Jobs

We’re looking for a hunter-minded Incubation Account Executive to help launch Command by Asana - our new product purpose-built for software development teams to stay in flow, catalog context, and de-risk releases in real time . In this ground-floor role, you will operate as an extended member of the GM’s team, building repeatable sales plays, navigating complex technical sales cycles, and bringing customer insights directly to Product, Marketing, and Pricing . You will partner closely with CTOs, VPs of Engineering, and cross-functional account teams to show how modern software teams can plan and execute with clarity, not theater . This role is based in our London office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays and Friday . If you're interviewing for this role, your recruiter will share more about the in-office requirements . What you’ll achieve Build and maintain a healthy pipeline of engineering, product, developer productivity, and technology leaders . Partner closely with Asana AEs and CSMs to identify expansion opportunities inside accounts where Asana is already used by business, product, or cross-functional teams . Become a trusted advisor to CTOs, VPs of Engineering, Heads of Product, Engineering Operations, Developer Productivity, Platform, and Technical Program Management leaders . Translate customer pain around sprint planning, backlog health, release forecasting, GitHub handoffs, AI-created work, bug routing, and status visibility into clear Command value narratives . Collaborate with Product Marketing, Product Management, Sales Engineering, and Customer Success to refine the Command sales motion, surface customer feedback, and support successful adoption . Develop and execute territory plans targeting engineering-heavy accounts with strong expansion signals . Document customer learnings, objection patterns, competitive takeaways, an

Command by Asana is a new product purpose-built for software development teams that helps engineers stay in flow Command automatically catalogs the decisions, context, and next steps agents need to stay efficient and keep moving. Engineers spend less time unblocking agents and more time on what’s next. Assists EMs with releases that de-risk themselves Command monitors scope, dependencies, pacing, and risks in real time, surfacing blockers and adjusting plans before they cascade into delays. Enables leaders to always know the status, without the meetings required Command gives leaders a custom, queryable view of the strategic work that's important to them, so they know what is truly at risk and why without waiting for a status update. We are building the first Solutions Engineering overlay team to support Command's go-to-market motion, partnering closely with customers to demonstrate how modern software teams can plan and execute with clarity, not theater. The Opportunity We're seeking a driven, entrepreneurial Solutions Engineer to join a newly formed team bringing Command to product development and Engineering teams. This is a unique opportunity to be on the ground floor of an emerging go-to-market motion, partnering with a dedicated Account Executive and cross-functional teammates to build repeatable technical plays that will scale across Asana's field organization. You will be an extended part of the Product Lead/General Manager's team, helping bring customer feedback to the product team and shape how the product, demos, and technical positioning evolve. You'll work with Engineering leaders, product development teams, and cross-functional stakeholders who are looking to modernize how they coordinate work, deflect repetitive requests, and deliver better employee experiences. This role requires strong technical curiosity and customer empathy—you'll lead discovery, technical validation, and solution design while partnering seamlessly with Asana's existin

This role will join Datadog’s Data Visualization organization, a team responsible for the visualization experiences that power dashboards, notebooks, investigations, and product workflows used across the platform. The team is a highly product-oriented organization, building AI-native experiences that help customers understand, investigate, and interact with complex operational data. As a Staff Software Engineer, you will provide technical leadership in applying AI technologies to customer-facing product experiences, helping shape how users interact with Datadog through agents, conversational interfaces, and intelligent investigation workflows. You will partner across engineering and product teams to develop reliable, scalable, and trustworthy AI-powered experiences while helping establish AI engineering expertise within the broader organization. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead the design and delivery of AI-powered product experiences across Datadog’s visualization and investigation surfaces. Develop systems that combine deterministic product capabilities with LLM-powered experiences to deliver trustworthy and explainable customer outcomes. Drive innovation in context engineering, prompt engineering, evaluation frameworks, and AI application reliability. Partner with product and engineering teams to improve investigation workflows and help customers discover insights more efficiently. Build experiences that enable Datadog capabilities to operate within third-party AI platforms, agents, and conversational environments. Provide technical leadership and mentorship while helping establish AI engineering best practices across the Data Visualization organization and broader Graphing group. Who You Are: You have extensive softw

MongoDB is seeking a Software Engineer 3 to join the Documentation Platform Engineering Team. The Documentation Platform delivers 60M page views a year and is critical to our users’ understanding of MongoDB products.It is also increasingly the context engine that helps AI tools understand, surface, and recommend MongoDB correctly. You will contribute to the evolution of our documentation platform by building and improving internal infrastructure, integrations, and applications that support our documentation and learning experience. This role can be based out of one of our offices in Canada or the USA, or remotely in Canada or the USA. Our ideal candidate Hands-on experience and understanding of Git, TypeScript, React, Next.js, CI/CD, MDX and other markup languages Experience with MongoDB (or a strong track record of working with other databases) Has worked on complex, in-production web applications Deep understanding of TypeScript or JavaScript, preferably TypeScript Can write, discuss, and review code in a collaborative way Understands how to make resilient, scalable, and maintainable software Has 2+ years of professional experience building and maintaining production software systems At MongoDB, you will Contribute to the development and enhancement of the MongoDB Documentation Platform Explore ways to improve documentation accessibility, discoverability, and user engagement Develop features that enhance the user experience for documentation consumers and contributors Contribute to and occasionally lead small-to-medium scoped features and platform improvements, collaborating with partner teams as needed Analyze user

MongoDB is seeking a Software Engineer 3 to join the Documentation Platform Engineering Team. The Documentation Platform delivers 60M page views a year and is critical to our users’ understanding of MongoDB products.It is also increasingly the context engine that helps AI tools understand, surface, and recommend MongoDB correctly. You will contribute to the evolution of our documentation platform by building and improving internal infrastructure, integrations, and applications that support our documentation and learning experience. This role can be based out of one of our offices in Canada or the USA, or remotely in Canada or the USA. Our ideal candidate Hands-on experience and understanding of Git, TypeScript, React, Next.js, CI/CD, MDX and other markup languages Experience with MongoDB (or a strong track record of working with other databases) Has worked on complex, in-production web applications Deep understanding of TypeScript or JavaScript, preferably TypeScript Can write, discuss, and review code in a collaborative way Understands how to make resilient, scalable, and maintainable software Has 2+ years of professional experience building and maintaining production software systems At MongoDB, you will Contribute to the development and enhancement of the MongoDB Documentation Platform Explore ways to improve documentation accessibility, discoverability, and user engagement Develop features that enhance the user experience for documentation consumers and contributors Contribute to and occasionally lead small-to-medium scoped features and platform improvements, collaborating with partner teams as needed Analyze user

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The Ideal Candidate Will Have 3+ years of commercial software development experience with strong proficiency in Python and/or Java Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query optimisation Good und

MongoDB is growing its team in Sydney, focusing on building intelligent tools that help customers understand and modernise their application codebases. The Application Modernisation Platform (AMP) guides customers through the entire journey of modernising their applications — from legacy relational platforms to modern, scalable systems built on MongoDB. The App Analysis & Modelling team owns the critical first stage of this journey: building the context that powers everything downstream. The team builds code analysis tools that construct code dependency graphs and generate deep insights for codebases, giving customers a clear understanding of their existing applications before transformation begins. The team also designs schema recommendation engines that analyse signals such as existing relational schemas and query patterns to inform data modelling decisions. Our work sits at the intersection of analysis, data modelling, and AI — helping developers make confident, data-driven decisions as they transition to MongoDB. We are looking for a Senior Software Engineer who is passionate about building scalable backend systems and applications. As we expand our use of AI to power smarter analysis and recommendations, the ideal candidate will bring strong backend engineering fundamentals with the ability to contribute across the full stack. You will collaborate closely with product management and other engineering teams to design and deliver cutting-edge features that guide customers through complex modernisation journeys. We are looking to speak to candidates who are based in Sydney for our hybrid working model. The ideal candidate will have 5+ years of commercial software development experience with strong proficiency in Python and/or Java Extensive Experience designing and building scalable, high-performance APIs and backend services Solid understanding of relational data modelling and SQL (Oracle, PostgreSQL, MySQL, or similar), including schema design and query opti

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

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes Drive collaboration and coordination with cross-functional teams

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is seeking a Senior Analyst to join our Business Forecast & Planning team within Customer Care Operations. This role sits at the center of forecasting and capacity strategy for our global support organization, translating complex operational and business signals into clear, actionable plans. You'll partner closely with operations leadership to keep resourcing aligned with the business, separating what truly matters from the noise, and helping shape decisions that affect how we staff and scale support. Responsibilities: Support the development and upkeep of the models and frameworks that connect business drivers to staffing and resourcing decisions Translate large, complex, and sometimes ambiguous data into clear, actionable insights that support leadership recommendations Own day-to-day planning execution, from dashboards maintenance and reporting to business reviews, with a sharp focus on accuracy and the details that matter Leverage AI tools to build and maintain dashboards, reports, and analyses that support the team's recommendations and insights Identify and help drive opportunities to improve how the team plans and operates Move quickly on ambiguous, time-sensitive requests, using modern tools to work smarter and faster Experience: 2+ years in planning, forecasting, capacity/resource management, or a related analytical role; consulting, investment banking, FP&A, or ops strategy backgrounds also fit well Sharp analytical mindset with hands-on SQL and Python skills AI fluency, comfortable using AI tools to accelerate analysis and problem-solving Strong business acumen paired with genuine curiosity about how large, complex business systems work; fast learner with a bias towards action, comfortable building context quickly across new systems and stakeholders Self-directed, with a track

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.&n

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data is at the heart of Lyft Business's products and decision-making. We're looking to hire a Data Analyst to build the tools and analytics that drive revenue for the sales organization behind Lyft's B2B portfolio — a multi-billion-dollar book of business spanning healthcare, business travel, corporate commute, automotive, and transit. This team has real say in what gets built. You will be the analytical partner to our Sales and account teams — someone who can translate findings into a clear narrative for both technical and non-technical audiences. Responsibilities: Build the tools and analytics sales leaders use to grow their accounts — pacing views, account-health signals, territory and segment views that change what a rep or manager does next Field requests from Sales, Product, Finance, Legal, leadership, and external stakeholders, and decide what's worth building, what's worth a sharp piece of analysis, and what's out of scope Build and maintain production data pipelines, and automate recurring workflows, with documentation and validation clear enough that a teammate — or an AI agent — can use them without asking you first Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question Contribute to the internal tools and semantic layer — prompts, context, and guardrails — that let stakeholders query B2B data in natural language and trust what comes back Translate insights into a cohesive narrative and present technical findings to senior leadership and non-technical audiences Experience: Degree (or related work experience) with a focus in analytics, statistics, economics, computer science, or other quantitative fields 3+ years of experience in a data analytics or business intelligence role, ideally supporting a sales

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is in a defining moment — from turnaround to international growth, from traditional rideshare to the autonomous future. The Chief of Staff to the CEO sits at the center of that transformation, serving as a force multiplier for CEO David Risher and the senior leadership team. This is a rare opportunity for a builder, strategist, and trusted advisor who can operate at altitude while staying close to the detail. The Chief of Staff to the CEO is the CEO's most trusted operational and strategic partner. You will: Own the rhythms, narrative, strategy, and operations of the Executive Office, translating the CEO’s vision into organizational execution across Lyft. Work in lockstep with our Executive Business Partner to ensure the CEO and executive team operate at their highest and best use at all times. Lead the internal community of Chiefs of Staff that act as the operational backbone for the company This role demands exceptional range: you'll build organizational frameworks, draft corporate strategy, manage high-stakes communications, run executive meetings and offsites, hold confidential context with grace, and know when to drive decisions and when to get out of the way. You are here to make the organization smarter, faster, and more aligned. Responsibilities: Executive partnership & decision support Serve as a strategic thought partner and sounding board for the CEO on organizational strategy, business priorities, and leadership effectiveness Prepare the CEO for high-stakes meetings, board sessions, investor engagements, and external appearances — including briefing materials, talking points, and post-meeting follow-through, whether drafted by you or in partnership with cross-functional partners Identify decisions that need to be made, surface the right information at the right

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data is at the heart of Lyft Business's products and decision-making. We're looking to hire a Data Analyst to build the tools and analytics that drive revenue for the sales organization behind Lyft's B2B portfolio — a multi-billion-dollar book of business spanning healthcare, business travel, corporate commute, automotive, and transit. This team has real say in what gets built. You will be the analytical partner to our Sales and account teams — someone who can translate findings into a clear narrative for both technical and non-technical audiences. Responsibilities: Build the tools and analytics sales leaders use to grow their accounts — pacing views, account-health signals, territory and segment views that change what a rep or manager does next Field requests from Sales, Product, Finance, Legal, leadership, and external stakeholders, and decide what's worth building, what's worth a sharp piece of analysis, and what's out of scope Build and maintain production data pipelines, and automate recurring workflows, with documentation and validation clear enough that a teammate — or an AI agent — can use them without asking you first Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question Contribute to the internal tools and semantic layer — prompts, context, and guardrails — that let stakeholders query B2B data in natural language and trust what comes back Translate insights into a cohesive narrative and present technical findings to senior leadership and non-technical audiences Experience: Degree (or related work experience) with a focus in analytics, statistics, economics, computer science, or other quantitative fields 3+ years of experience in a data analytics or business intelligence role, ideally supporting a sales

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.&n