Solution Architecture Platforms Manager Jobs

The Datadog for Startups (DDFS) program helps the next generation of fast-scaling companies adopt best-in-class observability and security from day one. We're looking for the technical engine of this program - someone who can sit across from a startup CTO, earn credibility in the first five minutes, and help them see how Datadog fits into their stack before they've even finished describing it. You'll be the first technical member on a lean, five-person team, owning the technical motion end-to-end: discovery calls, demos, startup enablement, forward-deployed engineering projects, and representing Datadog at founder events across San Francisco. This isn't a traditional SE seat - it's part solutions architect, part technical consultant, part startup evangelist, and it requires someone adaptable, proactive, and ready to take initiative without being told what to do next. 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: Run discovery calls with startup CTOs and engineering leads to identify quick wins, validate technical needs, and position Datadog against alternatives like Grafana, New Relic, Sentry, and Clickhouse Deliver tailored Datadog demos and help startups get instrumented quickly - removing friction, showcasing value, and ensuring smooth technical onboarding, particularly around AI/ML observability, infrastructure scaling, and security Build automation to improve internal team workflows - EX: outreach, reporting, the application process, and website updates Represent Datadog for Startups at accelerator demo days, hackathons, conferences, founder dinners, and workshops across San Francisco Build relationships across SF's startup ecosystem - founders, VCs, accelerator partners, and technical communities - and develop thought leadership content for tech

Datadog is seeking a Director of Product Management for Platforms to lead the internal platforms that power our global engineering organization. This is both a customer and internal platform leadership role, focused on enabling Datadog customers to maximize value with Datadog but also to enable other Datadog products to build, scale, and operate products efficiently and reliably. In this role, you will bring a combination of technical expertise, product management experience, and a deep understanding of platform and shared capabilities to help Datadog grow its leadership position. You will lead a team of product managers and collaborate with senior leadership in product, engineering and design. Your scope includes driving product features shared across all Datadog but also large-scale Datadog’s platform solutions. What You’ll Do Own the vision and strategy for platform products, ensuring alignment with overall company goals and customer needs. Identify new opportunities for innovation and drive them from concept to execution, ensuring they have a measurable impact on customers and the business. Define product roadmaps and manage the prioritization of features and initiatives to ensure the team's efforts are aligned with business goals. Drive Platform Adoption: Partner with engineering and product teams to ensure widespread adoption of shared platforms and shared features, reducing duplication and accelerating delivery. Improve Operational Efficiency: Improve developer velocity, time-to-production, and operational efficiency across Datadog’s engineering ecosystem. Collaborate with cross-functional teams including engineering, design, data science, marketing, and sales to deliver infrastructure product solutions that meet customer needs and business objectives. Define and Track Success Metrics: Define and track platform success metrics, including adoption of platform capabilities, reduction in internal toil, time-to-production improvements, cost efficienc

As a Senior Enterprise Customer Success Manager, you will be responsible for driving the healthy adoption and positive experience of some of Datadog’s largest and most strategic customers. 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: Partner with Sales and Technical Solutions to proactively drive adoption from onboarding through to maturity. Own and project manage the on-boarding process for new customers. Discover, own and manage the customer’s success plan. Ensure consistent alignment with decision makers on the impact of their investment in Datadog. Proactively build and maintain targeted relationships with people of influence throughout the customer base. Collaborate cross-functionally with internal Datadog teams (sales, support, enablement, product, finance, and legal). Monitor and analyze usage trends to uncover potential renewal opportunities and risks. Act as the primary owner of customer adoption and health. Support your colleagues and cross functional teammates in the development of best practices. With demonstrated understanding of observability and security platforms, align customers technical and business objectives to our platform offerings Who You Are: Min of 5+ years in a Customer Success or Account Management role in B2B SaaS (Exp in serving a technical audience a plus). Strong experience working with a portfolio of accounts that included large Enterprise. Excellent in driving discovery to understand your customers key pain points, objectives and priorities. Demonstrate expert level in communicating complex concepts and aligning them to the pains and objectives of your customers. Experienced in shifting your message effectively to align with the expectations of the audience. You’re excited to work i

Senior Enterprise Customer Success Managerとして、Datadogの中でも最も重要度の高いエンタープライズ顧客を担当し、プロダクトの健全な活用と優れた顧客体験の実現を牽引していただきます。 Datadogでは、Enterprise Customer Success Managerと同様に、オフィスカルチャーとハイブリッドワークを重視しています。 Datadogでは、オフィスカルチャーを大切にしています。人と人との関係性やコラボレーション、そこから生まれる創造性を重視し、ハイブリッドワークを通じて、一人ひとりに合ったワークライフバランスを実現しています。 主な業務内容（What You’ll Do） SalesおよびTechnical Solutionsと連携し、オンボーディングから活用成熟フェーズまでの戦略的な活用促進を主導 新規顧客オンボーディングの全体設計およびプロジェクトマネジメント 顧客サクセスプランの策定・管理・高度化 Datadogへの投資価値・成果について、エグゼクティブレベルの意思決定者と継続的にアライン 顧客組織内で影響力を持つステークホルダーとの戦略的関係構築 • 社内のクロスファンクショナルチーム（Sales、Support、Enablement、Product、Finance、Legal）との連携 利用状況データの分析を通じた更新機会・リスクの特定 顧客活用・健全性の最終責任者としての対応 チームメンバーや他部門と連携し、ベストプラクティスの構築・展開をリード 求める人物像（Who You Are） B2B SaaSにおけるCustomer SuccessまたはAccount Managementの実務経験5年以上（技術者向け顧客対応の経験があれば尚可） 大規模エンタープライズ顧客を含むアカウントポートフォリオの担当において、豊富な実績をお持ちの方 顧客の課題・目的・優先順位を深く理解するためのディスカバリーを高いレベルで実行できる方 複雑な概念を分かりやすく伝え、顧客の課題・目的に結びつけるエキスパートレベルのコミュニケーション力かつ、相手に応じてメッセージを柔軟に調整できる方 スピード感のある環境で、自身のスキルを継続的に高めながら、チーム全体のレベルアップに積極的に関与できる方 必要に応じて顧客訪問やイベント対応のための出張が可能な方 日本語：読み書き・会話ともに流暢 英語：読み書き・会話ともにビジネスレベル以上 Datadogは、さまざまな立場の人々を大切にしています。誰もが初日から上記の資格をすべて満たすわけではないことは理解しています。それでも構いません。テクノロジーに情熱を持ち、スキルを伸ばしたいと思っている方は、ぜひご応募ください。 利益と成長： 最高のオンボーディング MEDDICとCommand of Messageの営業研修 包括的な企業文化、コミュニティ・ギルドに参加する機会 社内ネットワークのための部門内メンターおよびバディ・プログラム 継続的な専門能力開発、製品トレーニング、キャリアパスの提供 新規雇用株式（RSU）および従業員株式購入制度（ESPP） 手厚く競争力のある福利厚生パッケージ 上記の福利厚生と成長は、雇用国やDatadogでの雇用内容によって異なる場合があります。 #LI-Hybrid About Datadog: Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram , LinkedIn, and Dat

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection , error outliers and faulty deployment analysis . As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performance You are excited to work on

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Position Overview We are seeking a Staff Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. This role can be based out of our Palo Alto office, or remotely in the United States. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues Strong background in machine learning, deep learning, and natural language processing Experience building complex neural networks for language and visual understanding Capable of conducting rigorous empirical studies to validate theoretical results Excellent leadership, problem-solving, and communication ski

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

Enterprise Customer Success Managerとして、Datadogの中でも最大規模かつ戦略的に重要な顧客を担当し、プロダクトの健全な活用促進と、ポジティブな顧客体験の実現をリードしていただきます。 Datadogでは、オフィスカルチャーを大切にしています。人と人との関係性やコラボレーション、そこから生まれる創造性を重視し、ハイブリッドワークを通じて、一人ひとりに合ったワークライフバランスを実現しています。 主な業務内容（What You’ll Do） SalesおよびTechnical Solutionsと連携し、オンボーディングから活用成熟フェーズまでのプロダクト利用促進を主体的に推進 新規顧客のオンボーディングプロセスをオーナーとして設計・推進・プロジェクト管理 顧客のサクセスプランを策定し、主体的に管理・実行 Datadogへの投資価値・成果について、意思決定者と継続的に認識をすり合わせ 顧客組織内のキーパーソン・影響力のあるステークホルダーとの関係構築・維持 社内の各部門（Sales、Support、Enablement、Product、Finance、Legal）との密な連携 利用状況データをモニタリング・分析し、更新機会やリスクの早期把握 顧客のプロダクト活用および健全性（Customer Health）の最終的な責任者として対応 求める人物像（Who You Are） B2B SaaSにおけるCustomer SuccessまたはAccount Managementの実務経験3年以上 大手エンタープライズ顧客を含むアカウントポートフォリオの担当経験 顧客の課題・目的・優先順位を理解するためのディスカバリーを主導できる方 複雑な内容を分かりやすく伝え、顧客の課題・目的と結びつけて説明できる高いコミュニケーション力 また、相手に応じてメッセージを柔軟に調整できる方 スピード感のある環境で、自身のスキルを継続的に高めながら、チームのベストプラクティス形成にも積極的に関与できる方 必要に応じて顧客訪問やイベント対応のための出張が可能な方 本ポジションでは、日本国内およびグローバルの社内関係者・社外のお客様とのコミュニケーションが発生するため、日本語・英語ともに、読み書きおよび会話においてビジネスレベル以上の語学力をお持ちの方 Datadogは、さまざまな立場の人々を大切にしています。誰もが初日から上記の資格をすべて満たすわけではないことは理解しています。それでも構いません。テクノロジーに情熱を持ち、スキルを伸ばしたいと思っている方は、ぜひご応募ください。 利益と成長： 最高のオンボーディング MEDDICとCommand of Messageの営業研修 包括的な企業文化、コミュニティ・ギルドに参加する機会 社内ネットワークのための部門内メンターおよびバディ・プログラム 継続的な専門能力開発、製品トレーニング、キャリアパスの提供 新規雇用株式（RSU）および従業員株式購入制度（ESPP） 手厚く競争力のある福利厚生パッケージ 上記の福利厚生と成長は、雇用国やDatadogでの雇用内容によって異なる場合があります。 #LI-Hybrid About Datadog: Datadog is the leading observability and security platform for the AI era, providing businesses with unified visibility across the technology stack to manage complexity at scale. It brings applications, infrastructure, data, models, and security into one place, using AI to detect and resolve issues before they impact customers. Trusted globally by Fortune 500 companies and high-growth AI leaders, Datadog enables businesses to move faster with clarity and confidence. Learn more about #DatadogLife on Instagram , LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to

As an Enterprise Customer Success Manager, you will be responsible for driving the healthy adoption and positive experience of some of Datadog’s largest and most strategic customers. 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: Partner with Sales and Technical Solutions to proactively drive adoption from onboarding through to maturity. Own and project manage the on-boarding process for new customers. Discover, own and manage the customer’s success plan. Ensure consistent alignment with decision makers on the impact of their investment in Datadog. Proactively build and maintain targeted relationships with people of influence throughout the customer base. Collaborate cross-functionally with internal Datadog teams (sales, support, enablement, product, finance, and legal). Monitor and analyze usage trends to uncover potential renewal opportunities and risks. Act as the primary owner of customer adoption and health. With demonstrated understanding of observability and security platforms, align customers technical and business objectives to our platform offerings Who You Are: 3+ years in a Customer Success or Account Management role in B2B SaaS. Experience working with a portfolio of accounts that included large Enterprise. Experienced in driving discovery to understand your customers key pain points, objectives and priorities. Excellent in communicating complex concepts and aligning them to the pains and objectives of your customers. Experienced in shifting your message effectively to align with the expectations of the audience. You’re excited to work in a fast paced environment, where you’re expected to consistently develop your skill set and play an active role in the development of the team’s best practices. Able to t

The IT Go-to-Market (GTM) organization builds and operates the technology platforms that enable the end-to-end customer lifecycle, spanning Sales, Revenue Operations, Customer Support, Customer Success, and Professional Services. As a Senior Product Manager on the IT GTM team, you will own the product strategy and roadmap for post-sales technology platforms, including CRM, Service Cloud, support operations, customer portals, AI-enabled support capabilities, and enterprise integrations. You will partner with business and engineering leaders to define product vision, prioritize investments, and deliver scalable solutions that improve customer and agent experiences, drive operational efficiency, and support business growth. We are looking to speak to candidates who are based in Palo Alto, New York City, Seattle, or Austin for our hybrid working model. Responsibilities Domain Expertise Proven experience modernizing Technical Support platforms, including workforce planning, workflow automation and optimization, customer and partner collaboration and i, and knowledge-sharing solutions Strong understanding of end-to-end support user journey, including case creation and management, omni-channel case routing, prioritization, system integrations, and AI-driven proactive customer engagement Extensive knowledge of integration patterns across Salesforce Sales Cloud, Service Cloud, external support portals, and analytics platforms to deliver seamless customer and agent experiences Broad understanding of the post-sales ecosystem spanning Professional Services, Technical Support, and Customer Success, with the ability to design solutions that optimize cross-functional workflows Understanding of expertise in customer and support agent journeys, support processes, and operational workflows, with a track record of leading large-scale digital transformations and delivering custom solutions that address complex business challenges Expertise in building and scaling technology solutions f

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. Position Overview We are seeking a Senior Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field Strong background in machine learning, deep learning, and natural language processing Familiarity with training distributed training of neural networks for language and visual understanding What We Offer Opportunity to work on real-world problems at the cutting edge of AI research Opportunity to utilize research vision to innovate the entire company and make real-world impact Exposure to the full lifecycle of AI model development, from research to production Our compensation (base + equity) for this position is competitive with frontier AI labs About MongoDB

MongoDB is seeking a Vice President, Global Specialization Leader to build and scale a world-class specialist organization focused on our highest-growth, highest-innovation product surfaces: Agentic applications, Voyage AI, Vector Search, and Analytics. This is a foundational, builder-oriented leadership role for someone who thrives at the intersection of emerging technology, early-stage product-market fit, and enterprise go-to-market execution. This leader will own the global specialist motion end-to-end — driving revenue, shaping product direction through frontline signal, and building a team of Specialist Sales and Specialist Solutions/Systems Architects that can sell, demo, and pilot next-generation AI-native workloads with speed and credibility. We are looking to speak to candidates who are based in Austin, NYC, Palo Alto, or San Francisco for our hybrid working model. What You'll Do Own a global number; Take full accountability for a consumption and/or bookings target across Agentic, Voyage AI, Vector Search, and Analytics, and build the plans, forecasting discipline, and pipeline hygiene needed to hit it predictably Build and lead a global specialization team; Recruit, manage, and develop a team of Specialist Sales leaders and Specialist Systems/Solutions Architects across regions, ensuring consistent coverage, quality, and career growth Operate like a startup inside MongoDB; These are early product-market fit motions — build the playbooks, qualification criteria, and champion strategies from scratch rather than inheriting mature process. Move fast, test, and iterate Drive fast, structured product feedback loops. Serve as the connective tissue between the field and Product/Engineering, translating customer and prospect signal into prioritized feedback that shapes the roadmap for Agentic, Voyage AI, Vector Search, and Analytics Own demo and pilot excellence; Ensure the team has best-in-class demo assets and a repeatable, fast pilot/PoC meth

The Team This role can sit in our NYC HQ on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones. We are looking for an experienced Senior Engineer for our SRE, Atlas team to support, maintain and grow the Atlas platform. As a senior SRE, you will be expected to be able to design & build complex systems, operate with autonomy and act as owner for everything you do. The SRE Atlas team works alongside the various Atlas software engineering teams to provide expertise about running systems at scale, build new tooling and automation and perform essential maintenance of the Atlas fleet. This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions that have the ability to impact our customer’s most crucial workloads. Role Overview We are seeking a talented Site Reliability Engineer (SRE) with a strong infrastructure background. This role requires engineers to have a customer-first mindset to ensure that everything we do results in a stronger product and a better experience for all Atlas customers. The ideal candidate should Have 5+ years of experience running critical systems at scale Value efficiency in processes and operations, and display a preference for automation over manual processes (“allergic to ops work”) Be familiar with a major cloud provider (AWS, Azure, or GCP) and possess the ability to build and operate systems in a multi-cloud environment A strong understanding of how to run a large scale Linux environment, including low level fundamentals Firm grasp of at least one modern programming language, beyond basic scripting (Go, Ruby, Python) Solid understanding of web and network protocols and standards (HTTP, TLS, DNS, etc) Special Requirements: Be a US Citizen Expectations Participate in the development of a reliable and resilient multi-cloud platform that hosts business critic