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Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About The Team The Service Stability Engineering Team envisions service stability as one of the core competitive strengths of the company's products. By building end-to-end, link-level risk management capabilities, the team aims to achieve sustainable automatic identification and analysis of stability risks, transforming from "reactive governance" to "proactive governance." This approach shifts more stability-related matters forward and addresses them early, preventing issues before they arise and enhancing user experience. What You’ll Be Doing Oversee non-functional aspects of relevant business lines, closely collaborate with business units to ensure service stability. Based on data analysis, identify stability risks throughout the entire chain, detect unreasonable architectural designs in advance, uncover root causes of issues, and systematically address problems; Explore new technologies, tools, and architectural patterns, and promote the implementation of best practices in application architecture. What We Look For In You Bachelor's degree or higher in Computer Science or a related field, with over 8 years of experience in development and architecture. Proficiency in Java, hands-on experience with the Spring Cloud microservices technology stack, solid computer science fundamentals, and a grasp of Linux, storage, and network I/O principles. Possess experience in high-concurrency distributed system architecture or high-concurrency scenario component design and development, with an understanding of Java concurrency libraries. Understanding of core Middleware technologies like Nginx, Redis, ElasticSearch, Kafka, MySQL, Docker and Kubernetes. In-depth understanding of the business architecture currently managed, along with a strong methodology for architectural design. Capable of rationalizing architectural designs for new business lines and providing targeted optimization suggestions. Nice-To-Haves Proficiency in speaking, reading and writing in both English and Mandarin to collaborate effectively with global and cross-functional team members. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependents More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our Inference team is responsible for building and maintaining the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researchers to develop next-generation models Integrate new AI accelerator platforms and support inference for new model architectures Minimum qualifications Significant software engineering experience, particularly with distributed systems Results-oriented, with a bias towards flexibility and impact Willingness to pick up slack, even if it goes outside your job description Desire to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Preferred qualifications Experience with high-performance, large-scale distributed systems Experience implementing and deploying machine learning systems at scale Experience with load balancing, request routing, or traffic management systems Familiarity with LLM inference optimization, batching, and caching strategies Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure) Proficiency in Python or Rust Representative projects Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production-grade deployment pipelines for releasing new models to millions of users reliably Contributing to new inference features Supporting inference for new model architectures Analyzing observability data to tune performance based on real-world production workloads Managing multi-region deployments and geographic routing for global customers Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Security Risk team is responsible for how Anthropic identifies, prioritizes, and drives treatment of its most important security risks. We are rebuilding risk management to operate as an engineering function through automation and AI-native platforms to enable decision making. The systems we assess span Anthropic’s full security landscape, from authorization primitives to cryptographic foundations, so the team needs breadth across domains and the ability to go deep in any of them. Security Risk, in deep partnership with Security Engineering, will help define the security program to shape how both engineers and non-engineers build and ship software. The conventional GRC playbook was not built for a company shipping frontier AI. You will help define what replaces it, with a direct line to CISO-level decisions and the mandate to build the AI-native platform underneath. You’ll work across a breadth of areas from identity and secrets management to infrastructure security, with your focus shaped by your strengths, ability to learn quickly, and the team’s priorities. This is largely greenfield work, and you will help define the architecture and discipline. Key responsibilities Take ownership of Anthropic’s most complex security risk problems and drive them end to end with minimal oversight, turning ambiguous signals into a defensible view of severity and likelihood and seeing them through escalation, treatment decisions, and remediation Build the systems that make risk measurable and let risk work scale, including quantification tooling, automated intake and triage, and the observability that partner teams use to understand their own risk posture Work alongside Security Engineering as a calibrated technical peer who pressure tests architectures and treatment plans, translates findings into prioritized remediation roadmaps, and makes the investment case for what to fix now, what to accept and track, and what to defer Mentor engineers and risk practitioners across Security and the broader engineering organization, and help build a risk engineering culture in which teams own their risks and our team provides the visibility and judgment that supports the Security risk engineering Work across the breadth of Anthropic’s security landscape, spanning areas like identity and secrets management, developer security and supply chain, infrastructure security, and secure frameworks, and build the context needed to reason about risk credibly in each Go deep where a risk demands it, understanding how these systems are built and how they fail so that assessments and treatment plans reflect engineering reality rather than abstraction Risk assessment and quantification Identify systematic risks through threat modeling and structured assessment, then drive the severity calibration and escalation conversations that follow, bringing leadership a defensible position and a clear recommendation that holds up under pointed questions Contribute to the team’s quantitative risk work, applying methods such as calibrated estimation and Monte Carlo simulation where they meaningfully change a resource or treatment decision Risk platform and automation Design and build AI-native risk tooling that uses Claude to classify incoming risks, augment triage, and continuously sense changes in our risk landscape as teams ship Create the dashboards and data pipelines that give engineering and product teams real-time visibility into their risk posture and make distributed ownership of risk practical Remediation strategy and investment Partner with Security Engineering and risk owners to design remediation roadmaps that are explicit about sequencing, ownership, and the investment required Measure outcomes rather than activity, focusing on decisions made and risk reduced Minimum qualifications At least 8 years of software engineering or security engineering experience, including leading and remediating complex security risks independently Bachelor’s degree in a related field or equivalent experience Strong programming skills in Python or at least one systems language such as Go, Rust, or C/C++ Broad knowledge across the core security engineering domains, with depth in at least one, including identity and secrets management, developer security and supply chain, infrastructure and cloud security, and secure frameworks Calibrated risk judgment, meaning you can put a defensible severity and likelihood on an ambiguous problem and change your position when the evidence changes Experience leading cross-functional security initiatives and navigating complex organizational dynamics Outstanding communication skills, translating technical concepts effectively across all levels of the organization A track record of bringing clarity and ownership to ambiguous technical problems and driving them to resolution Low ego and high empathy, with a history of growing the engineers around you and supporting diverse, inclusive teams Passion for AI safety and the role security and risk management play in building trustworthy AI systems Preferred qualifications Owned a named security risk and driven it from discovery through remediation across multiple teams Briefed executives on risk decisions and defended accept, remediate, or transfer recommendations under challenge Built security automation, detection, or risk platforms adopted across an engineering organization Shipped LLM or agent-powered tooling and workflows that automate security or risk activities A security engineering, detection engineering, or offensive security background with a risk-based prioritization mindset Built or operated a quantified security risk program (FAIR-style decomposition, Monte Carlo simulation, loss exceedance analysis) whose outputs changed real resource decisions Enough familiarity with SOC 2, ISO 27001, or FedRAMP to know what compliance does and does not buy you The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: New York City We’re looking for a Staff Software Engineer to integrate and improve our AI developer experience so that engineers at Asana can use AI to increase their velocity. As part of the AI Developer Productivity team, you’ll set technical direction and build the next generation of AI-powered developer tools across editors, IDEs, CLIs, code review, and cloud and local coding agents. This role is based in our New York City 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. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Design and build AI-augmented workflows and systems that help coding agents understand the codebase, follow engineering practices, and enable Asana engineers to complete software development tasks faster and with more confidence. Design and scale autonomous cloud agents that take on complex, multi-step engineering tasks to reduce toil and enable engineers to focus on higher-leverage work. Build and refine IDE, editor, and CLI integrations that make AI-assisted development feel intuitive in engineers' daily work. Create reusable agent skills, tools, context, and integrations that teams across Asana can build on rather than reinvent. Improve AI-assisted code review workflows so engineers get faster, higher-quality feedback before and during review. Drive adoption of AI developer tools across engineering through usability improvements, measurement, documentation, and enablement. Set technical direction for the team, balancing experimentation with reliability, maintainability, and long-term platform thinking. Partner cross-functionally with teams across the engineering organization to understand engineering needs, identify workflow friction, and scale high-impact solutions. About you 8+ years of software engineering experience, including 3+ years of experience leading complex technical projects across teams. Experience building developer tools, internal platforms, infrastructure, IDE/editor integrations, CLIs, or workflow automation. Hands-on experience with AI-assisted development tools (such as Cursor, Claude Code, or Codex), or extending coding agents, MCP-based integrations, AI-powered code review systems, or agent skill/tool ecosystems. Experience building evaluation and quality frameworks for AI-generated outputs. Strong technical judgment and systems design skills, with the ability to make pragmatic tradeoffs in ambiguous or rapidly changing environments. Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making. What we’ll offer Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit. For this role, the estimated base salary range is between $248,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified. In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role. We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role. #LI-Hybrid #LI-AS2 About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Location: Canada; United States Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker is shipping a wave of new products this year, with R&D initiatives likely to lead to more, and we're investing heavily in the platform underneath all of it. That platform supports hundreds of engineers across many development teams and carries high-scale production traffic and data transfer every day. It has grown faster than its foundations, and this year is about closing that gap. Today, much of that work still leans on a handful of experts unblocking the same provisioning and operational workflows by hand. The top priority for this role is moving that work from expert-driven support to paved roads: self-service systems with clear ownership, safe defaults, strong guardrails, and adoption we can measure. The goal is a platform teams trust enough to stop thinking about it, one that just works, so they can focus on their own products instead of ours. The concrete version sits on this year's roadmap: spinning up a new global region or application environment should take hours, not days. Right now it takes days. Getting there means building the foundations underneath it. We need a real multi-region, cross-account network architecture and a testing and continuous-deployment flow teams can trust, then a self-service layer on top. We're the container company building our own internal platform, so the bar for "the easy path is also the safe path" is high. You'd be joining a team of four, growing to seven this year (this is one of those hires), and we're looking for a Staff engineer to set technical direction and lead it through real production adoption. _______________________________________________________________________ RESPONSIBILITIES This is a Staff-level role, so success is measured by leverage rather than just your own commits. On a team this size you'll stay hands-on in the codebase while also setting direction, aligning teams on pragmatic standards, and carrying platform investments through to adoption. Concretely, you will: - Take ambiguous infrastructure problems and turn them into proposals the org can rally around, then drive them through RFCs and architecture reviews across teams. - Design self-service capabilities and platform APIs (primarily in Go) for onboarding, provisioning, deployment, observability defaults, and day-2 operations, with contracts and docs teams actually use. - Set delivery standards using Terraform, GitOps with Argo CD, progressive rollout, and good testing, including building the continuous-deployment flow we're missing today. - Evolve the multi-tenant EKS foundations toward better reliability, security, scale, and cost: Envoy Gateway ingress, traffic routing, and the multi-region, cross-account connectivity we need. - Improve SLOs, alerting, and incident follow-up on Grafana Cloud so production gets safer and less dependent on heroics. We judge this work by outcomes the consuming teams feel: how fast they can provision and ship, how much they can do without us, and how reliably it all runs. AI-ASSISTED OPERATIONS We're actively investing in AI-assisted and agentic workflows to cut operational toil. We care that they stay safe, auditable, and human-reviewed. You'll help shape where these earn their place and where they don't. Early targets include: - Alert enrichment and incident context-gathering: assembling the relevant signals, history, and runbook so the on-call engineer starts with context instead of a blank page. - Runbook-assisted diagnosis and remediation recommendations, with a human in the loop on anything that changes production. - Onboarding and readiness assistants that answer the questions our experts answer today. If you've built operational automation and have a healthy skepticism about where automation belongs, this is a place to put both to work. ON-CALL Operational ownership is part of the job. You'll join the rotation after onboarding and shadowing. As a Staff engineer, you'll also improve the health of on-call itself, with better alerts, stronger runbooks, less toil, and blameless postmortems aimed at prevention. _______________________________________________________________________ QUALIFICATIONS - 8+ years of professional, hands-on, full-time software engineering experience in backend, infrastructure, or platform engineering. - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience - Strong software engineering in Go or a similar language: design, testing, debugging, review, long-term maintainability. - A track record designing, shipping, and operating cloud services or infrastructure platforms in production. We hire for skill and impact, not years. - Deep expertise in at least one of: Kubernetes, networking, cloud platforms, reliability engineering, or developer platforms, plus solid Linux, networking, and production-ops fundamentals. - Experience setting technical direction and leading work that needs cross-team alignment. - Clear written and verbal communication in a remote environment (RFCs, design docs, incident writeups). Nice to have: EKS and ingress/CNI/service-mesh experience; observability with OpenTelemetry/Prometheus/Grafana; CI/CD and progressive delivery (GitHub Actions, Argo CD, canaries); experience leading migrations or adoption programs across teams. You don't need every item here. We value deep expertise in one area, strong systems judgment, and curiosity across the rest. _______________________________________________________________________ WHAT TO EXPECT FIRST 30 DAYS - Build context, meet partner teams, ship your first change, shadow on-call. FIRST 90 DAYS - Own a strategic platform problem with a clear plan and metrics; lead an improvement from design to production. ONE YEAR OUTLOOK - Lead a major cross-team initiative (for example, self-service provisioning of new regions and environments, or the multi-region networking and CD foundations behind it) and establish durable patterns that change how Docker engineers build and operate services. Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________ COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. Canada: CA$238,250 – CA$382,250 base United States: $170,350 – $275,550 base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the team The Finance Data Team is responsible for the data infrastructure that powers OKX's compliance, regulatory, and financial reporting operations globally. Our Finance Data domain covers everything from raw transaction ingestion to consolidated group financials — supporting statutory reporting, board-level financials, and audit readiness across 100+ markets. This is a team that treats data correctness as a non-negotiable. We operate at the intersection of engineering rigour, financial domain knowledge, and regulatory accountability. About the role We are looking for a Staff Data Engineer to be the technical anchor for Finance Data at OKX. You will define how Finance data is architected, validated, and delivered, and set the standard for how the team operates in an AI-native way. You will work directly with Finance, Accounting, and Treasury stakeholders to ensure that financial data is complete, reconciled, traceable, and audit-ready. You will also be the domain's primary escalation point and the technical voice of Finance Data within the broader engineering organisation. This role suits someone who has operated as a de facto domain lead before — someone who has built financial data systems that have been reviewed by auditors, regulators and who knows what "good" looks like in a regulated financial data environment. Responsibilities: Domain Architecture & Technical Direction Own the end-to-end Finance data architecture: from ODS ingestion through CDM transformation to reporting mart, with clear data lineage documented at every layer Define and enforce data modelling standards for Finance: period cut-off immutability, multi-entity consolidation logic, revenue recognition alignment, and audit trail completeness Lead the design of scalable pipelines supporting trading data, asset positions, P&L, and cost accounting across multiple legal entities and jurisdictions (SG, EU, US, and others) Make architectural decisions independently and articulate trade-offs clearly to both engineering peers and non-technical Finance stakeholders Financial Reporting & Audit Readiness Partner with Accounting, Finance PMO, and Treasury to deliver datasets for month-end close, statutory reporting, and board-level financials on time and to audit standard Ensure every financial figure is traceable back to the source system with full transformation history — no black boxes Build the data foundation that supports OKX's regulatory reporting obligations and long-term financial reporting maturity Data Quality & Controls Design proactive, self-validating DQC frameworks — reconciliation logic, SLA monitoring, and anomaly detection built into pipelines, not bolted on after incidents Own incident response for Finance-critical pipeline failures; conduct structured post-mortems and drive permanent fixes Define "done" for financial correctness in partnership with Accounting; hold the line on data quality standards even under delivery pressure AI-Native Finance Data Lead the team's adoption of AI-assisted engineering: LLM-assisted development, automated anomaly detection, intelligent reconciliation, AI-generated reporting summaries Evaluate and introduce AI tooling into Finance data workflows with production evidence — not POC demos Set the bar for what an AI-native Finance data team looks like, and bring junior engineers along Technical Leadership & Influence Be the go-to escalation point for Finance data domain questions across the team Mentor and grow engineers working in the Finance domain; translate domain complexity into learnable patterns Represent Finance Data in cross-team architecture discussions, sprint planning, and stakeholder reviews Document domain knowledge that outlasts any individual — data dictionaries, pipeline specs, onboarding guides Requirements: 6+ years in data engineering, with at least 3 years owning a Finance, Accounting, or financial reporting data domain end-to-end Deep understanding of financial data fundamentals: period close and cut-off rules, revenue recognition, multi-entity consolidation, reconciliation, and audit trail requirements Demonstrated experience building data systems that have been reviewed in a statutory audit or regulatory review Strong SQL and Python; proven ability to design and maintain complex production pipelines at scale Experience designing for immutability and lineage — financial data that can be rolled back, re-run, and traced without manual intervention Track record of operating with significant autonomy: defining requirements from ambiguous stakeholder input, not just executing tickets Preferred Qualifications: Experience at a crypto exchange, fintech, or company that has gone through IPO preparation or public company financial reporting Familiarity with regulatory reporting requirements across multiple jurisdictions (MAS SG, SEC, FCA, or equivalent) AI/ LLM tooling applied to data engineering workflows in production — concrete examples required; "exploring" does not count Experience with Spark, Airflow, or equivalent orchestration at scale Prior experience as a de facto domain lead or tech lead without formal people management title Background working with Accounting/Controllership teams as a technical counterpart Perks & Benefits: Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: San Francisco; Palo Alto Perplexity is seeking experienced ML engineers to design, build, and optimize the recommendation systems that power core experiences on Perplexity. Perplexity builds AI for those who expect more. Our products are designed to help people find answers, make their most consequential decisions, and complete increasingly ambitious work. Across these use cases, the Perplexity experience must feel deeply personal. Great recommendations and user understanding are central to delighting and delivering for each user. To do this, we are reimagining recommendation systems for the LLM era. Our goal is to combine the intelligence of frontier LLMs, the personalization context that comes from real product usage, and the continual learning capabilities of modern recommendation systems. We build systems that draw on past context and connected data sources to deeply understand each user's needs and recommend the actions that help them get the most out of Perplexity. WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both AI native and AI curious users. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others’ strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Own the personalization and ranking behind key product surfaces to make Perplexity more useful and drive impact on core user and business metrics. - Build user modeling that captures intent, preference, and propensity, and powers more relevant, more personalized experiences. - Design the decision layer that balances competing objectives to produce the best overall experience for the user. - Build the data and evaluation foundations that let these systems learn and improve with usage. - Help shape the technical direction of ranking, recommendations, and personalization at Perplexity. WHAT WE'RE LOOKING FOR - Deep, hands-on experience building production recommendation, ranking, or personalization systems at scale. - Strong ML fundamentals, covering areas such as engagement modeling, model calibration, offline and online metrics, and online experimentation. - Experience integrating LLMs into ranking, retrieval, or personalization pipelines. - Taste and judgment for how personalization should work in an LLM-native product, and curiosity about reimagining it from first principles. - For tech leadership roles, we will also look for prior experience setting technical direction for recommendation/ranking projects. NICE TO HAVE - Experience with large-scale ranking and training infrastructure (multi-stage retrieval and ranking, feature stores, real-time serving). - Background in user understanding, feed ranking, notifications, growth, or lifecycle modeling. OUR MISSION Perplexity’s mission is to power curiosity. Curious people are the people who drive change in the world. Driving change is a continuous cycle of learning, building, and integrating. Learn: curious people constantly learn new things by asking more. They question the status quo in their own expertise and they constantly learn outside of it. Research is essential to them and never ending. Build: curious people make and create things, to show the world their new answers to problems no one else ever questioned. They take action on what they’ve learned. Makers need tools to create their products, their companies, their reality. Integrate: they must interact with the world as it is to drive change and adoption. True leaders do not simply build something and hope. They must have armies of agents and workers who can constantly work in millions of small ways. Repeat. For curious people this is a cycle that never ends.

Location: San Francisco; Palo Alto Perplexity is seeking experienced ML engineers to design, build, and optimize the recommendation systems that power core experiences on Perplexity. Perplexity builds AI for those who expect more. Our products are designed to help people find answers, make their most consequential decisions, and complete increasingly ambitious work. Across these use cases, the Perplexity experience must feel deeply personal. Great recommendations and user understanding are central to delighting and delivering for each user. To do this, we are reimagining recommendation systems for the LLM era. Our goal is to combine the intelligence of frontier LLMs, the personalization context that comes from real product usage, and the continual learning capabilities of modern recommendation systems. We build systems that draw on past context and connected data sources to deeply understand each user's needs and recommend the actions that help them get the most out of Perplexity. WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both AI native and AI curious users. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others’ strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Own the personalization and ranking behind key product surfaces to make Perplexity more useful and drive impact on core user and business metrics. - Build user modeling that captures intent, preference, and propensity, and powers more relevant, more personalized experiences. - Design the decision layer that balances competing objectives to produce the best overall experience for the user. - Build the data and evaluation foundations that let these systems learn and improve with usage. - Help shape the technical direction of ranking, recommendations, and personalization at Perplexity. WHAT WE'RE LOOKING FOR - Deep, hands-on experience building production recommendation, ranking, or personalization systems at scale. - Strong ML fundamentals, covering areas such as engagement modeling, model calibration, offline and online metrics, and online experimentation. - Experience integrating LLMs into ranking, retrieval, or personalization pipelines. - Taste and judgment for how personalization should work in an LLM-native product, and curiosity about reimagining it from first principles. - For tech leadership roles, we will also look for prior experience setting technical direction for recommendation/ranking projects. NICE TO HAVE - Experience with large-scale ranking and training infrastructure (multi-stage retrieval and ranking, feature stores, real-time serving). - Background in user understanding, feed ranking, notifications, growth, or lifecycle modeling. OUR MISSION Perplexity’s mission is to power curiosity. Curious people are the people who drive change in the world. Driving change is a continuous cycle of learning, building, and integrating. Learn: curious people constantly learn new things by asking more. They question the status quo in their own expertise and they constantly learn outside of it. Research is essential to them and never ending. Build: curious people make and create things, to show the world their new answers to problems no one else ever questioned. They take action on what they’ve learned. Makers need tools to create their products, their companies, their reality. Integrate: they must interact with the world as it is to drive change and adoption. True leaders do not simply build something and hope. They must have armies of agents and workers who can constantly work in millions of small ways. Repeat. For curious people this is a cycle that never ends.

Location: San Francisco; New York City In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, and the Growth team owns the product loops that help them discover, adopt, and build lasting habits around our most important AI experiences. As a growth engineer at Perplexity, you'll work across the full funnel — activation, onboarding, SEO, lifecycle, conversion, retention, and paid upgrade moments — while also building the applied AI systems that make those experiences smarter. Engineers are responsible for end-to-end projects from training and productionizing classifiers to identify high-intent users, personalizing value discovery, shipping contextual onboarding experiments, or wiring new AI capabilities into measurable adoption and revenue outcomes. Growth at Perplexity goes beyond incremental funnel optimization. The team sits close to the core product - we translate behavioral signals, model outputs, and fast experimentation into durable product surfaces used across consumer and enterprise workflows. You'll move fast, run many experiments in parallel, and own the outcome end-to-end. Tech Stack: TypeScript | Next.js | React | Python | PostgreSQL | Eppo | AWS WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Design, build, and own growth surfaces across the full funnel — activation, onboarding, SEO, lifecycle, conversion, retention, and paid upgrade moments — for Computer and every Perplexity product. - Lead experiments end-to-end, from hypothesis and instrumentation through implementation, analysis, and rollout, shipping many in parallel and learning quickly from each. - Build applied AI systems that power growth: classifiers for high-intent segments, personalization for value discovery, and AI-driven onboarding and recommendation surfaces. - Launch vertical-specific experiences (e.g., students, enterprise organizations) that connect new AI capabilities to measurable adoption and revenue outcomes. - Hill-climb on the metrics that matter: activation rate, paid conversion, retention, and habit formation, instrumented with clean data and trustworthy experiment readouts. - Partner closely with Product, Design, Data Science, Monetization, Marketing, and Applied AI to translate behavioral signals and model outputs into durable product surfaces. QUALIFICATIONS - 2+ years of professional software engineering experience (we're open to strong junior and mid-level candidates with a track record of shipping). - Full-stack engineering skills, with comfort across a modern web stack (we use Next.js, React, TypeScript on the frontend and Python on the backend). - Strong execution: you ship many experiments and product improvements in parallel and drive them to a clear outcome. - Familiarity with A/B testing and experimentation platforms (Eppo, Statsig, Optimizely, or in-house equivalents). - Comfort with SQL and data-informed decision-making — you can pull, segment, and interpret your own funnel data. - Strong product judgment; you translate user behavior and growth opportunities into simple, effective technical solutions. - Self-motivated with strong ownership instincts; you propose experiments, ship features ahead of schedule, and drive improvements without asking for permission. - Genuine interest and adoption of AI products and willingness to learn quickly. NICE TO HAVE - Direct experience on a growth, activation, conversion, retention, or lifecycle team at a consumer or PLG/self-serve SaaS company. - Experience training and productionizing ML models (classifiers, ranking, personalization) and connecting them to product surfaces. - Experience with SEO, lifecycle marketing tooling, or paid acquisition surfaces. - Familiarity with subscription and/or usage based billing products, paywalls, or paid upgrade experimentation. - Experience shipping for both consumer and enterprise audiences. - Time spent at a fast-growing startup or on a high-ownership engineering team. - Familiarity with mobile development - Swift/Objective-C/Kotlin/Java, in-app payments, mobile release cycles, Apple App Store and/or Google Play Store guidelines, and rollout monitoring

Location: San Francisco; New York City In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, and the Growth team owns the product loops that help them discover, adopt, and build lasting habits around our most important AI experiences. As a growth engineer at Perplexity, you'll work across the full funnel — activation, onboarding, SEO, lifecycle, conversion, retention, and paid upgrade moments — while also building the applied AI systems that make those experiences smarter. Engineers are responsible for end-to-end projects from training and productionizing classifiers to identify high-intent users, personalizing value discovery, shipping contextual onboarding experiments, or wiring new AI capabilities into measurable adoption and revenue outcomes. Growth at Perplexity goes beyond incremental funnel optimization. The team sits close to the core product - we translate behavioral signals, model outputs, and fast experimentation into durable product surfaces used across consumer and enterprise workflows. You'll move fast, run many experiments in parallel, and own the outcome end-to-end. Tech Stack: TypeScript | Next.js | React | Python | PostgreSQL | Eppo | AWS WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Design, build, and own growth surfaces across the full funnel — activation, onboarding, SEO, lifecycle, conversion, retention, and paid upgrade moments — for Computer and every Perplexity product. - Lead experiments end-to-end, from hypothesis and instrumentation through implementation, analysis, and rollout, shipping many in parallel and learning quickly from each. - Build applied AI systems that power growth: classifiers for high-intent segments, personalization for value discovery, and AI-driven onboarding and recommendation surfaces. - Launch vertical-specific experiences (e.g., students, enterprise organizations) that connect new AI capabilities to measurable adoption and revenue outcomes. - Hill-climb on the metrics that matter: activation rate, paid conversion, retention, and habit formation, instrumented with clean data and trustworthy experiment readouts. - Partner closely with Product, Design, Data Science, Monetization, Marketing, and Applied AI to translate behavioral signals and model outputs into durable product surfaces. QUALIFICATIONS - 2+ years of professional software engineering experience (we're open to strong junior and mid-level candidates with a track record of shipping). - Full-stack engineering skills, with comfort across a modern web stack (we use Next.js, React, TypeScript on the frontend and Python on the backend). - Strong execution: you ship many experiments and product improvements in parallel and drive them to a clear outcome. - Familiarity with A/B testing and experimentation platforms (Eppo, Statsig, Optimizely, or in-house equivalents). - Comfort with SQL and data-informed decision-making — you can pull, segment, and interpret your own funnel data. - Strong product judgment; you translate user behavior and growth opportunities into simple, effective technical solutions. - Self-motivated with strong ownership instincts; you propose experiments, ship features ahead of schedule, and drive improvements without asking for permission. - Genuine interest and adoption of AI products and willingness to learn quickly. NICE TO HAVE - Direct experience on a growth, activation, conversion, retention, or lifecycle team at a consumer or PLG/self-serve SaaS company. - Experience training and productionizing ML models (classifiers, ranking, personalization) and connecting them to product surfaces. - Experience with SEO, lifecycle marketing tooling, or paid acquisition surfaces. - Familiarity with subscription and/or usage based billing products, paywalls, or paid upgrade experimentation. - Experience shipping for both consumer and enterprise audiences. - Time spent at a fast-growing startup or on a high-ownership engineering team. - Familiarity with mobile development - Swift/Objective-C/Kotlin/Java, in-app payments, mobile release cycles, Apple App Store and/or Google Play Store guidelines, and rollout monitoring

Location: Noida, India Workplace: hybrid TeamViewer provides a leading Digital Workplace platform that connects people with technology—enabling, improving and automating digital processes to make work work better. Our software solutions harness the power of AI and shape the future of digitalization. We believe that our diverse teams and strong company culture are key to the success of our products and technologies, that hundreds of millions of users around the world and around 645,000 customers across all industries rely on. With more than 1,900 employees worldwide, we celebrate the unique perspectives and talents that each individual brings to the table and foster a dynamic work environment where new ideas thrive. Are you ready to join our team and make an impact? Responsibilities We’re looking for a Staff Software Engineer (all genders) with focus on fullstack engineering to play a key role in enhancing and actively contribute to the development of new features for our remote access, control and support solutions using modern technologies. The position will report to a Team Lead Software Development and provides an excellent opportunity to create impact and add value in an agile, modern environment. As part of an Agile team, you’ll work as an individual contributor, primarily with C# .NET, TypeScript/JavaScript and React. Your work will power both containerized services running on Azure Kubernetes and web applications hosted on IIS in on-prem environments. You will also guide junior members of the team in best practices in software development & Secure SDLC. Define the architecture, design and develop new features for our software in .NET C# Continuously integrate, build and deploy our solution from test system to production Design and implement common APIs based on architecture guidelines and frameworks Design and build common database systems of high availability and quality Optimize and enhance our software with new, efficient algorithms and state-of-the-art software tools and technologies Work independently on solutions for specified requirements and be responsible for complying with time and quality specifications Ensure that our software is secure, stable, scalable and runs efficiently Monitor the latest technical developments in your field and make proposals for improvement Guide and assist other team members in engineering topics relevant for the team Coach & mentor junior members in the team Act as an advisor for product owners (feasibility studies and time estimates for new functionality to be implemented) Communicate with customers to analyze & fix product defects, or during major implementations Requirements A university degree in the field of information technology, computer science and engineering or a related subject 10+ years of professional experience in the field of software development Solid knowledge of .NET (C#), JavaScript/TypeScript, React and SQL is mandatory Must have hands on experience in Docker & Kubernetes ecosystem and should be able to work on them locally in docker desktop. Must have experience in any of the unit test casing framework Experience in taking architectural decisions about the development and maintenance of large-scale distributed systems and integrations with applications and user interfaces Solid knowledge of Secure SDLC principles, OWASP Top-10 vulnerabilities & remediation, and Threat Modeling Experience in quick feasibility studies, POC & prototyping to arrive at firm estimates Experience in build v/s buy evaluations and total cost of ownership of software systems Understanding of Clean Code and Design Patterns for object-orientated programming A positive and solution-oriented mindset paired with a structured and analytical way of thinking/working, being a team player, as well as motivated to learn new things Experience in any of the following is desirable: parallel programming (multi-threading), test automation, network communications, digital certificates/PKI Knowledge in C++ is a plus Familiarity with AI tools for coding (like Co-pilot) is a plus Familiarity with concepts of end-user computing and software asset management is a plus Fluency in English is mandatory, further languages are a plus TeamViewer is an equal opportunities employer and is committed to building an inclusive culture where everyone feels welcome and supported. We C-A-R-E and understand that our diverse, values-driven culture makes us stronger. As we continue to grow as a company, we also focus on enabling our employees to grow both personally and professionally. We are proud to have an open and embracing workplace environment that will empower you to be your best no matter your gender, civil or family status, sexual orientation, religion, age, disability, education level, or race.

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . The Onboarding team owns the first experience every user has after signing up for Reddit. Every new Redditor, on every platform, walks through a flow we design, and our job is to make those first interactions feel streamlined, delightful, and personal. We guide each user through the signals we need to tailor their experience, then use those signals to help them quickly discover the magic of Reddit: valuable content and communities that feel approachable, relevant, and immediately rewarding from their very first session. Few teams at Reddit sit closer to the company's growth than this one. The decisions we make in the first session compound for the entire lifetime of a user, and the difference between a flow that connects and one that doesn't is the difference between someone becoming a lifelong Redditor or never coming back. That kind of leverage is rare, and it's why this work is some of the most impactful product engineering happening at the company. We get there by combining polished product engineering, ML-powered personalization, and rigorous product experimentation, in close partnership with product, design, and data science cross functional partners. We move fast, we ship to learn, and we measure everything we ship. If you want your work to genuinely shape how millions of people experience Reddit for the first time, this is the team to do it on. What You'll Do 🏗️ Foster and Guide the Technical Strategy for Onboarding Define and accelerate the backend architecture for a newly onboarded user: the signal-collection systems that learn who a new Redditor is, the personalization pipelines that turn those signals into a tailored first feed, and the experimentation infrastructure that lets us iterate on the moments that decide whether someone becomes a lifelong user. You won't be following a roadmap; you'll shape how we build the systems that compound for every user's lifetime. 🤝Partner With the EM to Cultivate a Growth Engineering Mindset Growth teams operate differently than platform teams. We prioritize experimentation and iteration, which means sometimes we throw things away to move faster. You'll help the team internalize that operating model: what it means to build for learning, how to balance velocity with reliability, and how to stay rigorous when moving fast. 🤖Scale Impact Through Collaborative Engineering You'll build and maintain deep partnerships with the engineering teams whose surfaces directly shape a newly onboarded user's experience: Relevance, Feeds, Notifications, and beyond. Many of these collaborations will touch ML-powered systems that surface the right content to the right users. You'll be the bridge that ensures Onboarding has a technical representation for the team and a collaborative influence on their roadmaps. 📊Instrument, Measure, and Iterate Establish the instrumentation and experimentation foundations that let the team run rigorous A/B tests on growth levers. Use metrics to make the case for the bets worth taking, and deprioritize efforts that don't meet goals. 🔗Guide Cross-Functional Alignment Serve as the engineering voice in XFN partnerships with Product, Design, Data Science, and other Consumer platform teams. You'll align stakeholders on technical feasibility and tradeoffs, co-author roadmaps that bridge user experience goals with backend realities, and represent Onboarding Engineering in Reddit-wide technical forums. ⚡Raise the Bar on Engineering Excellence Advocate for reliability, scalability, and maintainability across a complex, high-scale distributed system. Lead design reviews, establish patterns that the broader organization can learn from, and ensure that moving fast never becomes an excuse for accruing crippling tech debt. You'll define what "great" looks like on this team. Who You Might Be At least 7 years of experience . You’ve steered cross-team projects that solved tangible business problems, rather than just hitting a 'ship' date. A strategic partner, not just a technologist . A systems thinker. You see how the code, the product, and the team dynamics all influence each other. You can plan for next year while still helping an engineer through a blocker today. You're a mentor who helps other engineers level up . You don't just assign tasks; you help the team work through complex problems more effectively. You're energized by the opportunity to build culture and craft on a team, not just software. You're deeply data-informed and logical. You ensure metrics are part of the design process, not just an afterthought in a dashboard. Your architectural directions are traceable back to product and business outcomes, and you're fluent in the language of experimentation, funnels, and retention. Comfortable with growth-team ambiguity . You navigate ambiguity with confidence when the goal is clear but the path is not. You're comfortable with growth-team speed—prototyping fast, moving on when the data doesn't back a bet, and keeping the team focused when the plan changes. A focus on clear, transparent communication. You can effectively distill complex technical trade-offs for any audience—whether you’re collaborating on a whiteboard with peers or presenting a roadmap review to executive stakeholders. Experience with ranking, recommendations, and personalization . You have a proven track record of working on ML-heavy products. You can design the backend architectures, retrieval systems, and inference pipelines required to scale them. You understand the nuances of candidate generation and scoring, and you can partner effectively with Machine Learning engineers to turn model outputs (such as Two-Tower models) into high-impact product features. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $217,000 — $303,000 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: San Francisco; Palo Alto; New York City ABOUT THE ROLE The Backend Platform team is the backbone of Perplexity’s product reliability, scalability, and performance, enabling every product and AI team to build with confidence. This high‑impact group builds and maintains critical infrastructure, including backend systems for authentication, authorization, real-time data flows, service orchestration, and sandboxing, to ensure fast, reliable, and secure user experiences. By setting rigorous standards for code quality, uptime and performance, the Platform team ensures everyone at Perplexity can innovate at speed on top of a robust, well-architected foundation. KEY RESPONSIBILITIES - Lead the design and implementation of our sandboxing platform to safely execute untrusted and user‑generated code while meeting strict performance and reliability requirements. - Define and extend our RBAC and authorization primitives, ensuring they scale with new product capabilities and enterprise controls. - Own key backend services involved in authentication and encryption flows (including BYOK‑related pieces), partnering with Security and Infra on defense‑in‑depth. - Set the technical bar for backend platform design and operations, driving best practices in reliability, observability, and incident response for always‑on systems. - Partner with product and AI teams to define clear platform interfaces, SLAs, and integration patterns so new features can reliably build on shared backend capabilities. - Provide technical leadership across the backend platform area, mentoring other engineers and making long‑term architectural decisions that keep the foundation simple, secure, and evolvable. QUALIFICATIONS - Experience designing and building backend systems that run in production (typically 4+ years for mid-level, more for senior and staff). - Strong system design skills, with a track record of creating efficient, reliable, and scalable architectures. - Hands-on experience with modern infrastructure (for example AWS, Kubernetes, and related cloud technologies). - Strong proficiency in at least one backend language such as Python, Go, or Rust, and the ability to work effectively in a multi-language environment. - Collaborative mindset and eagerness to solve challenging technical problems with other experienced engineers. - Comfort working in security‑sensitive areas (auth, authorization, encryption) and making pragmatic trade-offs between safety, simplicity, and velocity. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: San Francisco; Palo Alto; New York City ABOUT THE ROLE The Backend Platform team is the backbone of Perplexity’s product reliability, scalability, and performance, enabling every product and AI team to build with confidence. This high‑impact group builds and maintains critical infrastructure, including backend systems for authentication, authorization, real-time data flows, service orchestration, and sandboxing, to ensure fast, reliable, and secure user experiences. By setting rigorous standards for code quality, uptime and performance, the Platform team ensures everyone at Perplexity can innovate at speed on top of a robust, well-architected foundation. KEY RESPONSIBILITIES - Lead the design and implementation of our sandboxing platform to safely execute untrusted and user‑generated code while meeting strict performance and reliability requirements. - Define and extend our RBAC and authorization primitives, ensuring they scale with new product capabilities and enterprise controls. - Own key backend services involved in authentication and encryption flows (including BYOK‑related pieces), partnering with Security and Infra on defense‑in‑depth. - Set the technical bar for backend platform design and operations, driving best practices in reliability, observability, and incident response for always‑on systems. - Partner with product and AI teams to define clear platform interfaces, SLAs, and integration patterns so new features can reliably build on shared backend capabilities. - Provide technical leadership across the backend platform area, mentoring other engineers and making long‑term architectural decisions that keep the foundation simple, secure, and evolvable. QUALIFICATIONS - Experience designing and building backend systems that run in production (typically 4+ years for mid-level, more for senior and staff). - Strong system design skills, with a track record of creating efficient, reliable, and scalable architectures. - Hands-on experience with modern infrastructure (for example AWS, Kubernetes, and related cloud technologies). - Strong proficiency in at least one backend language such as Python, Go, or Rust, and the ability to work effectively in a multi-language environment. - Collaborative mindset and eagerness to solve challenging technical problems with other experienced engineers. - Comfort working in security‑sensitive areas (auth, authorization, encryption) and making pragmatic trade-offs between safety, simplicity, and velocity. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: San Francisco; Palo Alto; New York City ABOUT THE ROLE The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. KEY RESPONSIBILITIES - Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. - Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. - Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. - Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. - Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. - Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. - Drive architectural decisions across storage, compute, orchestration, and data APIs, partnering closely with product engineering and data science to align the data ecosystem with Perplexity’s roadmap. - Mentor engineers, review designs, and raise the technical bar for data infrastructure through thoughtful feedback, documentation, and hands-on collaboration. QUALIFICATIONS - 5+ years (Senior) or 8+ years (Staff) of software engineering experience. - Strong experience building production data infrastructure systems. - Hands-on experience with batch and/or streaming data processing at scale. - Deep familiarity with data orchestration systems (Airflow, Dagster, or similar). - Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.). - Strong systems thinking around reliability, latency, cost, and complexity tradeoffs. - Experience supporting ML/AI workflows, training pipelines, or evaluation systems. - Familiarity with data quality, lineage, observability, and governance tooling. - Prior ownership of internal platforms used by many teams. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: San Francisco; Palo Alto; New York City ABOUT THE ROLE The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company’s data lake. The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse. In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem. KEY RESPONSIBILITIES - Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation. - Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation. - Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows. - Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences. - Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction. - Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams. - Drive architectural decisions across storage, compute, orchestration, and data APIs, partnering closely with product engineering and data science to align the data ecosystem with Perplexity’s roadmap. - Mentor engineers, review designs, and raise the technical bar for data infrastructure through thoughtful feedback, documentation, and hands-on collaboration. QUALIFICATIONS - 5+ years (Senior) or 8+ years (Staff) of software engineering experience. - Strong experience building production data infrastructure systems. - Hands-on experience with batch and/or streaming data processing at scale. - Deep familiarity with data orchestration systems (Airflow, Dagster, or similar). - Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.). - Strong systems thinking around reliability, latency, cost, and complexity tradeoffs. - Experience supporting ML/AI workflows, training pipelines, or evaluation systems. - Familiarity with data quality, lineage, observability, and governance tooling. - Prior ownership of internal platforms used by many teams. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: San Francisco; Palo Alto; London; Berlin; Belgrade; New York City ABOUT THE ROLE The Cloud Infrastructure team owns the foundational cloud primitives and deployment models that power Perplexity's products, from multi-tenant public cloud to single-tenant and on-premises solutions for enterprise customers. As Perplexity grows its Computer and Enterprise products, this team builds and operates the security, isolation, and compliance layers that customers depend on. We provide the deployment topologies, multi‑region infrastructure, and core services that enable Perplexity to run reliably and efficiently for both consumer traffic and large enterprises. KEY RESPONSIBILITIES - Own the roadmap and technical strategy for agent-driven cloud infrastructure management. - Design and operate Perplexity’s cloud networking fabric, including VPC architectures, private connectivity, and peering with hyperscalers and neocloud providers to support low-latency, high-throughput AI workloads. - Architect and scale compute platforms (Kubernetes/EKS, autoscaling groups, and mixed CPU/GPU fleets) to efficiently serve online request traffic and background workloads across regions. - Build and maintain secure, isolated deployment topologies for multi-tenant, single-tenant, and customer‑owned cloud (BYOC) environments, including cross-account networking, identity, and policy guardrails. - Implement and evolve multi-region strategies for availability, failover, and data locality, including traffic routing, regional capacity planning, and disaster recovery playbooks. - Partner with security to deliver enterprise controls such as BYOK/KMS integrations, network isolation, and auditability required for regulated customers. - Develop automation, tooling, and runbooks that make day‑2 operations (provisioning, upgrades, incident response) predictable and repeatable for Perplexity products across all environments. QUALIFICATIONS - Deep experience designing and operating cloud infrastructure on AWS (VPC design, routing, security groups, load balancing, private connectivity). - Strong background with Kubernetes/EKS and container orchestration, including multi‑cluster, multi‑region, or multi‑account setups. - Hands-on experience with cloud networking and peering (VPC peering, Transit Gateway, private link/service endpoints, or similar constructs in neoclouds). - Experience building or operating secure, isolated environments for enterprise customers (single‑tenant, BYOC, or on‑prem), ideally including BYOK/KMS integrations and compliance constraints. - Proficiency with infrastructure as code (Terraform) and strong software engineering skills in at least one of Python, Go, or Rust for automation and tooling. - Strong debugging and incident management skills across distributed systems (networking, compute, and platform layers), with a track record of driving root‑cause analysis and long‑term fixes. - 7+ years of industry experience building and operating production cloud infrastructure, including leading the design of complex systems or migrations. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.

Location: San Francisco; Palo Alto; London; Berlin; Belgrade; New York City ABOUT THE ROLE The Cloud Infrastructure team owns the foundational cloud primitives and deployment models that power Perplexity's products, from multi-tenant public cloud to single-tenant and on-premises solutions for enterprise customers. As Perplexity grows its Computer and Enterprise products, this team builds and operates the security, isolation, and compliance layers that customers depend on. We provide the deployment topologies, multi‑region infrastructure, and core services that enable Perplexity to run reliably and efficiently for both consumer traffic and large enterprises. KEY RESPONSIBILITIES - Own the roadmap and technical strategy for agent-driven cloud infrastructure management. - Design and operate Perplexity’s cloud networking fabric, including VPC architectures, private connectivity, and peering with hyperscalers and neocloud providers to support low-latency, high-throughput AI workloads. - Architect and scale compute platforms (Kubernetes/EKS, autoscaling groups, and mixed CPU/GPU fleets) to efficiently serve online request traffic and background workloads across regions. - Build and maintain secure, isolated deployment topologies for multi-tenant, single-tenant, and customer‑owned cloud (BYOC) environments, including cross-account networking, identity, and policy guardrails. - Implement and evolve multi-region strategies for availability, failover, and data locality, including traffic routing, regional capacity planning, and disaster recovery playbooks. - Partner with security to deliver enterprise controls such as BYOK/KMS integrations, network isolation, and auditability required for regulated customers. - Develop automation, tooling, and runbooks that make day‑2 operations (provisioning, upgrades, incident response) predictable and repeatable for Perplexity products across all environments. QUALIFICATIONS - Deep experience designing and operating cloud infrastructure on AWS (VPC design, routing, security groups, load balancing, private connectivity). - Strong background with Kubernetes/EKS and container orchestration, including multi‑cluster, multi‑region, or multi‑account setups. - Hands-on experience with cloud networking and peering (VPC peering, Transit Gateway, private link/service endpoints, or similar constructs in neoclouds). - Experience building or operating secure, isolated environments for enterprise customers (single‑tenant, BYOC, or on‑prem), ideally including BYOK/KMS integrations and compliance constraints. - Proficiency with infrastructure as code (Terraform) and strong software engineering skills in at least one of Python, Go, or Rust for automation and tooling. - Strong debugging and incident management skills across distributed systems (networking, compute, and platform layers), with a track record of driving root‑cause analysis and long‑term fixes. - 7+ years of industry experience building and operating production cloud infrastructure, including leading the design of complex systems or migrations. If you’re excited about this role, we encourage you to apply even if your experience doesn’t match every qualification listed above.