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Location: Minsk Workplace: hybrid We are seeking a Senior Frontend Engineer based in Minsk, Belarus to join our distributed engineering team. In this role, you will be the primary front-end architect responsible for designing and building modular, embeddable analytics and reporting blocks. These reporting UI components will be consumed across multiple client applications, including high-density web dashboards and mobile (Android POS / WebView) environments. You will focus heavily on Vue.js and Micro-Frontend architecture, ensuring our data visualization components are lightweight, highly responsive, independently deployable, and easily integrated by internal and external teams. This position requires 3 days a week in-office work at our Minsk office to collaborate in person with local engineering peers, along with regular remote collaboration across our global teams in Belarus and the U.S. What you will do: Micro-Frontend Architecture & Component Design: Architect, build, and maintain a library of modular, embeddable micro-frontend reporting components using Vue.js (Vue 3, Composition API, Pinia). Design flexible component APIs to allow reporting widgets (charts, data tables, metrics tiles, filters) to be effortlessly embedded across web applications, third-party partner portals, and mobile WebViews. Establish state management, event isolation, dynamic bundle loading, and cross-micro-frontend communication standards. Optimize front-end performance so screens load quickly and charts remain responsive on mobile POS devices with limited processing power and memory. Execution & Cross-Platform Delivery: Write clean, maintainable, highly efficient, and well-tested TypeScript and Vue.js code. Collaborate closely with backend engineers (Golang/ClickHouse team) to define efficient API schemas for streaming and aggregated reporting data. Work with UI/UX designers to create dense, intuitive, and responsive data-entry and reporting layouts suitable for retail store owners. Leverage AI development tools (GitHub Copilot, Claude Code) to accelerate UI development, generate comprehensive test suites, and refactor code efficiently. Collaboration & Culture : Collaborate in daily standups, sprint planning, and retrospectives to support continuous delivery. Communicate effectively across time zones and collaborate seamlessly with global engineering leadership. What we are looking for: 5+ years of commercial front-end development experience , with at least 2 years in a senior role . Vue.js Mastery: Deep expertise in Vue.js (Vue 3, Composition API, Script Setup, Pinia/Vuex, Vuetify UI framework), custom directive design, and component lifecycle management. Micro-Frontend Architecture Experience: Hands-on experience designing or implementing micro-frontend architectures (e.g., Module Federation, single-spa, Web Components, iframe/event-bus bridges). Data Visualization & Complex UI: Proven experience building data-dense dashboards, real-time analytics charts, or complex reporting widgets (using libraries like ECharts, Chart.js, D3, or similar). Cross-Platform / Embedded Web Views: Experience building responsive web applications optimized for embedding in mobile environments (Android WebViews / hybrid mobile apps). Modern Tooling & AI Practice: Proficiency with modern build tools (Vite, Webpack), TypeScript, CSS preprocessors, and automated testing (Vitest, Cypress, Playwright). Active daily use of AI coding tools (Cursor, Copilot, Claude Code) to accelerate development and component design. Strong problem-solving skills and experience working in distributed international teams. Excellent English communication skills. Nice to have: Experience with WebSockets or Server-Sent Events (SSE) for streaming real-time reporting updates. Working knowledge of backend API integration with Golang microservices. We offer you: Hybrid  work opportunity (3 days in the office)! Modern office with free parking in the very center of Minsk. An exciting and challenging job with talented people around. Competitive salary and growth opportunities. Really good hardware. 26 vacation days & 5 fully covered sick days without sick leave required per year. Compensation for professional training, seminars, and conferences. Sports activities reimbursement and loyalty program. Medical insurance. Referral program – get rewarded for helping us grow the team with talented people. Company-supported English classes to enhance your professional growth. IDT Corporation is a global communications company founded in 1990 and headquartered in Newark, New Jersey. We are industry leaders in prepaid communication and payment services and one of the largest international voice carriers. We are listed on the NYSE, employ over 1800 people across 20 countries, and have over $1.5 billion in revenues.  We are not ”another big IT corporation”— we encourage and support in-house entrepreneurs in developing their ideas into business actions. National Retail Solutions (NRS) is a leading provider of point-of-sale, payment, and digital solutions to tens of thousands of independent retailers across the United States and Canada. As a major player in the retail technology industry, NRS is expanding into next-generation cloud platforms, high-throughput retail ecosystems, and advanced analytics solutions. We are building modern, highly scalable systems designed specifically for high-volume retail operations and real-time reporting. This project represents one of the most significant technical initiatives in NRS’s history and offers a rare opportunity to join at the ground floor of a major strategic expansion.

Location: Georgia; Ukraine; Poland; Brazil; Argentina; Colombia Workplace: Remote Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are looking for a Senior Software Engineer (Elasticsearch, Scala) to join a team powering food search and logging for one of the world’s leading health and nutrition platforms. You’ll contribute directly to the systems that drive search — backend services, search infrastructure, and experimentation — with a focus on improving core metrics: conversion rates, time to log, query abandonment, and result relevance. WHAT YOU’LL DO - Contribute to, build, and maintain backend services that drive the food search experience, integrating with systems across the broader engineering organization. - Perform search performance tuning end-to-end — data design, indexing, query evaluation, and iterative improvement within Elasticsearch. - Assist in the evaluation and implementation of search and data technologies that improve result quality and user experience. - Collaborate closely with senior search engineers, product management, and leadership on solution discovery, experiment planning, and delivery. - Contribute to the development of tools, processes, and metrics for measuring and monitoring search quality. REQUIRED SKILLS & EXPERIENCE Elasticsearch - Demonstrated experience with performance tuning, query analysis, and relevance optimization in Elasticsearch at scale. - Strong understanding of index design, mapping strategies, cluster management, and scoring/ranking mechanics. - Familiarity with high availability, disaster recovery, and operational monitoring for Elasticsearch clusters. - Ability to deploy new indexes or clusters as needed for load balancing or experimentation. - Ability to translate product specifications into technical requirements and deploy ranking and relevance experiments with clearly defined success criteria and metrics. Scala - Strong experience writing, shipping, and maintaining Scala services in production. - Comfortable working across a stack that also includes SQL and Python — Scala is the primary language for this engagement. Agentic development - Active user of AI development tools such as Claude Code, Cursor, or comparable AI-powered coding environments — shipping production code with them, not just using autocomplete. - Familiarity with agentic coding patterns and workflows — code generation, refactoring, debugging, and test authoring. - Able to articulate how AI tooling fits into their development process and where human judgment remains critical. Engineering fundamentals - First-hand experience building, scaling, and supporting large-scale data infrastructure systems in production. - Strong understanding of database design, data architecture, and performance tuning across multiple data stores — MySQL, MongoDB, DynamoDB, Redis, or similar. - Experience with high-volume messaging systems such as Kafka. - Familiarity with AWS, GCP, or other cloud platforms. - Strong peer code review practices. PREFERRED QUALIFICATIONS - Experience leveraging AI workflows for meaningful development acceleration beyond autocomplete — code generation, refactoring, debugging, and test authoring at scale. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: Tel Aviv-Yafo, Tel Aviv District, Israel About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role We are looking for an experienced Engineering Team Lead to build and lead the FirstRead team , a new product-focused team within Aidoc’s Imaging Platform group. FirstRead, Aidoc’s report-generation initiative, is one of the company’s most important and high-potential new products. We have decided to found this team, following a highly successful product beta, in which our AI drafted thousands of full radiology reports, covering hundreds of different clinical findings with near-human accuracy. The product is evolving rapidly, and so will the team around it. With the opportunity to shape the product and its technical direction from the ground up, the FirstRead team will be accountable for the product outcome end-to-end . The team will work across the stack, using existing platform capabilities where possible, evolving them where needed, and building new services and capabilities when required. This is a role for a TL who enjoys shaping new products and turning evolving opportunities into clear technical direction. The team’s scope, architecture, priorities, and  longer-term mission will evolve as we learn. You will play a central role not only in delivering FirstRead, but also in building the team itself and shaping how product-focused teams operate within Imaging Platform . You will work closely with Product, AI teams, and other engineering teams across Imaging Platform to turn rapidly evolving product needs into working software, while balancing speed, technical quality, and long-term platform considerations. Responsibilities End-to-End Ownership: Lead the engineering effort required to make FirstRead successful, across engineering disciplines including  backend, frontend, AI infrastructure, DICOM pipelines, existing platform services, and entirely new components. Creating Clarity in a Fast-Moving Environment: Turn changing product needs and incomplete information into technical direction, priorities, and executable plans. Continuously adapt as the product evolves. Technical Leadership: Drive architecture and technical decisions across a broad technical surface. Know when to move quickly, when to invest in robust solutions, and when to involve domain experts. Cross-Team Engineering: Work closely with other TLs and engineers across Imaging Platform. Enable the team to contribute to existing services and platforms while respecting their architecture, ownership, and long-term direction. Team Building: Build the FirstRead engineering team, establish its culture and ways of working, develop engineers, and help shape its longer-term mission as a product-focused team. Delivery and Product Partnership: Partner closely with Product and other stakeholders, taking ownership of turning evolving product direction into concrete engineering execution. Engineering Excellence: Maintain strong engineering standards while operating in a fast-moving environment, balancing experimentation and delivery speed with reliability, maintainability, and scalability. Requirements Senior hands-on software engineering experience , including experience building complex systems end-to-end. Exceptional track record leading engineering teams , while remaining actively involved in technical and architectural decisions. Strong sense of urgency, with the ability to drive execution and maintain momentum in fast-paced, high-priority projects. Proven ability to lead projects in ambiguous, rapidly changing environments , where requirements and technical direction are not fully defined upfront. Broad technical experience and passion for working across different areas of the stack rather than specializing exclusively in a single domain. Strong system design and software engineering fundamentals, with experience designing and building distributed production systems. Demonstrated ability to take ownership of an outcome from early concept through implementation, production, and continued evolution . Excellent collaboration and communication skills, with demonstrated ability to work effectively across engineering teams and organizational boundaries. Strong product and business orientation, with the ability to balance technical considerations with speed, learning, and business impact. Strong leadership, mentorship, and team-building skills. Advantages Experience working in an environment with shared platforms and multiple engineering teams contributing to the same product. Experience across multiple areas such as backend, frontend, cloud infrastructure, data pipelines, or AI/ML systems. Experience with AI-powered products or production AI systems. Working at Aidoc Our Perks: Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. Amazing and healthy breakfasts and lunches prepared daily by our personal chef! Stocked up kitchen & meal card Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. Amazing culture - collaborative, transparent & fun! Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Задачи: — Анализировать эффективность маркетинговых активностей и искать точки роста — Разрабатывать и поддерживать систему аналитической отчетности — Работать с маркетинговой командой над аналитическими инструментами — Собирать, обрабатывать и анализировать большие объемы данных (Python, SQL) Требования: — От 3 лет опыта в маркетинговой аналитике — Отличное знание Python и SQL — Понимание статистики, A/B-тестирования и маркетинговых метрик (CPM, CPC, CPI, CPA, ROAS) — Знание принципов атрибуции мобильных и веб-приложений — Сильное аналитическое мышление — Опыт в fintech и знание Google Ads/Facebook Ads — плюс — В первую очередь рассмотрим кандидатов, которые уже находятся на Кипре Условия: — Работа в современном офисе в Лимасоле (15 минут от моря) — High-load продукт и сильная команда профессионалов — Гибкое начало рабочего дня — 22 рабочих дня отпуска — Обеды, снеки, компенсацию спорта — Курсы английского и греческого — Корпоративные мероприятия, спорт и активное комьюнити

Location: Remote - US About Backblaze Backblaze is the object storage leader in the open cloud movement, fueling customer success with cloud storage built purposefully to unlock budgets, unburden administrators, and unleash innovators. Together with our partners, we’re helping customers break free from the restrictive, overpriced legacy solutions that hold them back, and blaze forward with the full power of the open cloud in their hands. Founded in 2007, we scaled the business with less than $3 million in outside funding until 2021, when we did a traditional IPO on the Nasdaq stock exchange. Today, Backblaze generates over $136M ARR and is the leading specialized storage cloud, managing over three billion gigabytes of data storage for 500K+ customers in 175+ countries, including businesses, developers, IT professionals, and individuals. But while there is a lot to celebrate in our past, there is almost as much opportunity ahead of us. We’re seeking a Principal SRE to join our team! About the Role We are seeking a Principal Site Reliability Engineer (SRE) to help ensure the stability, scalability, and reliability of our production systems. The ideal candidate will have extensive experience collaborating in cross functional teams to manage the design, implementation and ongoing management of the Backblaze core infrastructure. You will be approved to demonstrate strong observability skills, process and service improvement and ability to leverage AI and automation to assist to mitigate issues faster and meet customer demand.. As a technical leader in Backblaze you will be expected to work across the organisation to achieve our goals. This will include working with our executives and customers. The role will focus long term strategic focus on platform stability. Key Responsibilities Service Reliability & Operations Own the availability and durability of critical services across production environments and accountability for outcomes. Ability to work independently, take ownership, and drive projects from problem discovery through resolution. Assist and advise on the design of service health metrics using SLIs, SLOs, and error budgets, and escalate issues when thresholds are at risk; partner with service owners to define/iterate SLIs/SLOs and establish error budget policies and alerting. Participate in leadership on-call rotations, incident response, and post-incident reviews to drive service improvements. Follow established ITIL/OSS processes (incident, change, problem, and capacity management). Architect and Design Design automation for common operational tasks, reducing manual intervention and toil. Collaborate with engineering on overall storage design, performance expectation against product SLAs. Define the monitoring, logging, and alerting frameworks (e.g., Prometheus, Grafana, Catchpoint, ELK), and help integrate runbooks with FireHydrant. Work with CI/CD pipelines, configuration management, and infrastructure as code tools (Terraform, Ansible, Jenkins). Write scripts (Bash, Python, Go, etc.) to improve system reliability and efficiency. Collaboration Partner with engineering, customer success, product, and operations teams to support resilient system design and operations. Work with customers to ensure stability prioritization is based around their needs and experiences in using Backblaze products. Work with vendors and service providers to troubleshoot service issues and track SLA performance. Document systems, share learnings, and help grow a reliability-minded engineering culture. Continuous Improvement Lead cross functional teams to identify gaps in observability, operations process and define overall prioritization strategy. Identify recurring issues and propose long-term improvements, and design action plans around implementing those improvements. Promote reliability-focused practices within development and operations teams. Qualifications Education & Experience Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience). 10+ years of experience in site reliability, systems engineering, or operations, experience with hyperscalers preferred. Exposure to large-scale, production-grade systems, including experience establishing operational procedures or runbooks and bringing others up to speed on them. Technical Skills Solid Linux systems administration and troubleshooting skills. Proven ability to leverage AI tools to improve platform stability and scalability. Knowledge of storage systems, performance, sharding and storage algorithms. Experience in load balancing services including IPVS. Security-minded operations (patching, hardening, identifying vulnerabilities). Familiarity with service reliability concepts — monitoring, alerting, incident response, and root cause analysis. Proficiency in at least one scripting language (Python, Bash, or Go). Experience working with containers (Kubernetes, Docker) and microservices concepts required; comfortable operating in a Kubernetes/Vitess-on-K8s environment (kubectl, mysqlsh, Vitess keyspaces). Experience with Hashicorp products (Nomad, Vault, Terraform). Preferred Attributes Experience in a SaaS, service provider, or distributed systems environment. Familiarity with ITIL/OSS practices and SLO/SLA’s. Strong problem-solving skills and willingness to learn new technologies. Experience with cloud platforms (AWS, GCP, or Azure). Backblaze Perks Healthcare for family, including dental and vision Competitive compensation and 401K RSU grants for full-time employees ESPP program Flexible vacation policy Maternity & paternity leave MacBook Pro to use for work, plus a generous stipend to personalize your workstation Childcare bonus (human children only) Fertility treatment and support Learning & development program Commuter benefits Culture that supports a healthy work-life balance Pay Transparency To provide greater transparency to candidates, we share pay ranges for all US-based job postings regardless of state. Final offer amounts are determined by multiple factors including candidate location, skills, depth of work experience, and relevant licenses/credentials. The pay range for this position is $215,000 to $250,000 per year. At Backblaze, we value being fair and good to our customers, partners, and employees. That’s why diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We believe that our dedication to cultivating a diverse workspace not only allows us to better serve our customers in over 175 countries but further reinforces our commitment to doing the right thing. We are proud to be an Equal Opportunity Employer. To understand more about the data we collect and process as part of your application, please view our Backblaze Employee Privacy Notice.

Location: San Francisco; Seattle; New York City ABOUT THE ROLE The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. KEY RESPONSIBILITIES - Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. - Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. - Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. - Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls. - Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost. - Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety. - Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes. QUALIFICATIONS - 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation. - Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications. - Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack. - Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows. - Deep expertise in at least one of the following: - Evaluation infrastructure, benchmark design, and automated grading. - Agent harnesses, tool interfaces, and reusable skills for complex workflows. - Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows. - Model selection, routing, and inference efficiency, including context management and caching. - Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise. - Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements. - A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship. If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.

Location: San Francisco; Seattle; New York City ABOUT THE ROLE The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. KEY RESPONSIBILITIES - Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. - Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. - Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. - Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls. - Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost. - Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety. - Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes. QUALIFICATIONS - 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation. - Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications. - Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack. - Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows. - Deep expertise in at least one of the following: - Evaluation infrastructure, benchmark design, and automated grading. - Agent harnesses, tool interfaces, and reusable skills for complex workflows. - Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows. - Model selection, routing, and inference efficiency, including context management and caching. - Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise. - Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements. - A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship. If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.

Lambda is looking for a Staff Product Manager Storage and Networking to define, launch, price, and improve cloud data and connectivity products.

Location: 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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. 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: New York City, NY 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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. 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: Kazakhstan FREEDOM FINANCE TECHNOLOGIES is a Cyprus-based fintech company and part of the international financial holding Freedom Finance. We develop and maintain trading and banking IT products, as well as the holding’s IT infrastructure worldwide. Our team currently consists of 170 professionals.  Over the past three years, we have grown fourfold and continue to actively expand our team. Since 2009, we have been developing our core product - a trading system for brokerage operations in the stock market. More than 700,000 users across 41 countries use our applications. We are expanding our IT Infrastructure team and are looking for a Network Engineer to support, develop, and modernize our corporate office network. Our office network is built around a centralized FortiGate core located in the data center and managed by a dedicated team. At the office level, we primarily use MikroTik and Ubiquiti equipment. We are looking for someone who can bring consistency and order to the network infrastructure by improving segmentation, implementing high availability, automating monitoring, and keeping documentation up to date. Key Responsibilities: Network Operations & Development Administer and develop the office network infrastructure (primarily MikroTik, with Ubiquiti deployed in several locations). Network Optimization Reconfigure network segmentation across all office locations, optimize the existing infrastructure, and eliminate bottlenecks. High Availability Design and implement high-availability solutions for network equipment and WAN connectivity. Monitoring & Automation Deploy network monitoring systems and introduce additional services to simplify network administration. Documentation & IP Address Management (IPAM/Wiki) Maintain and update the corporate knowledge base (Wiki), keep network diagrams for major office locations current, and manage the organization's IP address space (IPAM). New Office Deployments Remotely prepare and configure network equipment for new office openings. Collaboration Work closely with Internet service providers (ISPs) and the team responsible for the data center network core. Troubleshooting Diagnose and resolve incidents related to network infrastructure and associated services. Requirements Strong MikroTik Expertise Hands-on experience configuring, routing, and troubleshooting MikroTik RouterOS environments. Experience with Ubiquiti Solid understanding of configuring and managing UniFi and Edge product lines. Strong Networking Fundamentals In-depth knowledge of TCP/IP, the OSI model, routing, VLANs, VPNs, firewalls, and NAT. Practical experience designing and supporting high-availability environments, including link redundancy and load balancing. Linux Administration Solid experience with Ubuntu Linux, including network service configuration and basic server administration. Documentation Skills Experience with IP address management solutions (NetBox, phpIPAM, or similar) and maintaining network documentation and diagrams (Confluence, Notion, draw.io, Visio). Monitoring Systems Experience deploying, configuring, and customizing monitoring platforms such as Zabbix, Prometheus/Grafana, Nagios, or equivalent solutions. English — B2 (Upper-Intermediate) or higher Ability to communicate effectively in written English with external vendors and colleagues. Most day-to-day communication is conducted in English. Self-Driven & Organized Ability to work independently, take a structured approach to problem-solving, and maintain well-organized infrastructure and documentation. Excellent written and verbal Russian is essential for this role Nice to Have Experience with IP telephony, including Asterisk administration and configuration. Relevant certifications such as MTCNA, MTCRE, CCNA, or equivalent. Understanding of FortiGate architecture and operation to collaborate effectively with the data center networking team. Basic automation skills using Bash, Python, or Ansible to streamline routine operational tasks. Benefits Fully remote work. Daytime and evening working hours according to the Moscow time zone. A service contract with a Cyprus-based company. Fixed monthly salary in euros. Paid annual leave of 21 working days. Paid sick leave. Public holidays: New Year holidays until January 4–6, plus May 1–2 or May 8–9. One additional paid day off per month. Coverage of professional training courses related to your area of work. Coverage of participation in professional online conferences. Training on products and processes. A genuinely comfortable and professional working environment. Opportunities to grow and develop alongside the company and its products.

Location: San Francisco, CA 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 Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Utilization improvements are worth enormous sums at our scale. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at exabyte scale. 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: Remote Workplace: remote 🌎 About Us TeamSnap is made up of innovators, technologists, builders, and problem-solvers shaping the future of youth sports. We’ve been setting the standard in youth sports technology since we were founded in 2009.  We hire for big ideas and tiny egos — which is part of how we landed on Outside Magazine's Best Places to Work, Built In's 100 Best Remote-First Places to Work and, for several years running, Sports Business Journal’s Best Places to Work in Sports.   TeamSnap is seeking a Staff Software Engineer (Android) to lead advertising on our next-generation Android app. You'll set the technical direction for how ads come to life in the app: designing a scalable, privacy-conscious ad platform and building ad experiences that feel native to how families use TeamSnap. Along the way, you'll help shape the architecture of a modern Kotlin and Jetpack Compose app used by millions. We’re looking for critical thinkers who are excited to jump in and make an impact! We're looking for people with big ideas and tiny egos. No matter what your “job” is, you’re welcome to suggest better ways of doing anything. Our team values collaboration in a remote culture, so we regularly participate in pair sessions and virtual team swarms to stay connected and improve the team and company. What You'll Do: Architect and evolve TeamSnap's Android ad platform as a reusable, well-tested layer the whole app can build on Deliver display, native and video ad experiences across the app that fit naturally with the product Build privacy and consent into the ad stack from day one, in partnership with Legal/Privacy Make sure our app loads fast, renders smoothly, and is a delight to use Partner with Brands & Advertising, Product, Design and Data to define the roadmap, measure revenue and engagement impact, and iterate Shape the broader architecture of our Kotlin and Jetpack Compose app, including modularization and build health Lead cross-team technical initiatives through design docs, RFCs and hands-on work; mentor engineers and set Android standards with our iOS team What You'll Bring: Extensive experience building and shipping Kotlin Android apps at scale, including technical leadership at Staff level or equivalent Deep hands-on experience with Google Ad Manager on Android: native custom formats, key-value targeting, ad lifecycle and refresh, and debugging fill and delivery problems Experience with ad verification and measurement: DoubleVerify, IAS, or Open Measurement (OM SDK) and viewability Strong experience with modern Android: Jetpack Compose, Coroutines/Flow, Hilt, and multi-module architecture A track record of designing systems from scratch and leading them through launch across teams Nice to Have: Experience shipping video ads, such as the Google IMA SDK with ExoPlayer/Media3 or similar Ads in live streams (SSAI, ad breaks in live content), or experience with Amazon IVS Experience with apps for families or youth, and COPPA considerations BLE hardware integrations, or subscriptions (Play Billing, RevenueCat, Superwall) 🖥 Location TeamSnap is a fully remote company, so you'll need to be comfortable working with people in other time zones. We're always expanding, but we can't currently hire in Alabama, Alaska, Delaware, District of Columbia, Hawaii, Iowa, Louisiana, Mississippi, Nebraska, New Mexico, Rhode Island, South Dakota, West Virginia, or Utah. We can only hire permanent US residents at this time. 🚀 Opportunities to Grow We work hard on a culture built on trust, accountability, and inclusion — one where you can take on more, make a lasting impact, and have some fun doing it. 🎩 Total Rewards Remote-first since 2009 Flexible PTO and parental leave 100% premium coverage of medical, dental, and vision for you and your family 401(k) to invest in your future $1,500 annual learning and development reimbursement Travel to all-company meetings and team events Generous home office allowance TeamSnap swag when you start, plus a $50 store credit on every work anniversary Monthly health and wellness reimbursement, and more TeamSnap Total Rewards 🏆  Award-winning Culture At TeamSnap, you're not a culture fit – you're a culture add. Read our Culture Playbook to see how we play, what we ask of each other, and what drives us. 🧡 Inclusion and Diversity Creativity and innovation don't come from cookie-cutter teams. We hold ourselves accountable for building a culture where everyone is valued. Need any accommodations during the interview process? Just ask. We are an Equal Employment Opportunity Employer. AI Notice We may use AI tools to support parts of the hiring process, such as reviewing applications and resumes or assessing responses. These tools assist our recruitment team; they don't replace human judgment, and final hiring decisions are made by people. Contact us if you'd like more information about how your data is processed.

Location: Commercial Point, OH $750 Sign-On Bonus | Weekly Pay | 35% Babylist Discount | Paid Holidays | Paid Healthcare Benefits What the Role Is At Babylist, we help families prepare for one of the biggest moments of their lives — and our Commercial Point Fulfillment Center is where that promise becomes real. As a Forklift Operator, you're a core part of making that happen. You'll move product accurately and safely across our distribution center, working alongside a team that genuinely looks out for each other. This is a role where skilled, dependable people are valued — and rewarded for it. The schedule for this role is Monday- Thursday 7:00am - 5:30pm at our Fulfillment Center located in Commercial Point, OH. About Pay At Babylist we believe in competitive starting pay and a clear, structured scale that rewards performance and tenure. You'll always know how your pay grows. Starting pay for this role is $22.50 per hour. You'll earn a raise every 3 months through your first 18 months with no waiting on an annual review to see your pay move. Sign-On Bonus Earn a $750 sign-on bonus, paid on your first payday after 90 days of employment. You must be actively employed on the payment date to receive the payment. Holidays Observed The Fulfillment Center is closed on the following days for the day shift in 2026: Thanksgiving Day All shifts receive 4 floating holidays in addition to the holidays observed, so you can celebrate what matters to you the most, whenever that may be. Who You Are Certified and experienced on multiple lift types — you're comfortable on a Reach Truck, Cherry Picker, Stand-Up Forklift, and Sit-Down Forklift (3+ years on each) Safety is non-negotiable for you — you follow protocols because you understand why they exist, not because someone's watching Steady and dependable — your team counts on you to show up, stay on task, and keep things moving even when volume spikes Adaptable across zones and tasks — shifting priorities don't throw you; you read the floor and adjust A real teammate — you communicate clearly, flag issues early, and help others hit the shared goal How You Will Make an Impact Move, locate, stack, and count materials throughout the distribution center using the full range of lift equipment Load and unload trailers safely — keeping outbound on schedule and inbound organized Support both inbound and outbound operations with accurate, timely material handling Perform pre-shift equipment inspections and flag maintenance needs before they become problems Keep your work area clean, organized, and hazard-free — every shift, not just when audited Step in to support other warehouse functions when the floor needs it Physical Requirements Stand and walk for extended periods (up to 10–12 hours per shift) with scheduled breaks Walk the floor extensively, averaging 10,000+ steps per day Lift and move items up to 20 lbs regularly throughout the shift Frequent pushing, pulling, bending, twisting, and repetitive motion Who We Are At Babylist, the work our fulfillment teams do reaches millions of families across the country — whether you're on the floor moving product or leading the operation that makes it happen. We're one of the leading platforms for expecting and new families — a $750M business with 10 million customers and eight consecutive years of profitability. Our fulfillment centers are where the mission becomes real, and the people who run them are a core part of how we deliver on it every single day. Our Ways of Working Our fulfillment teams work on-site in a fast-paced, team-driven environment where every role — from the floor to leadership — plays a direct part in delivering the Babylist experience to millions of families. Why You Will Love Working At Babylist Our Culture Work hard, then recharge — we respect your time on and off the clock Strong management team that supports you and your team The work you do helps millions of families every day We use smart technology to make the job easier and more efficient Growth & Development Clear paths to move up — we promote from within and your performance matters We use data to improve how we work and invest in the people doing it Pay & Benefits Competitive weekly pay $750 sign-on bonus, paid after 90 days of employment Company-paid medical, dental, and vision insurance 401(k) with company match and flexible spending accounts Paid parental leave and PTO Important Notices Recorded Interviews Babylist uses an interview recording tool to record and transcribe interviews for evaluation purposes in accordance with applicable privacy laws. By participating in an interview, you consent to this recording and transcription. Interview Integrity AI is part of how we work at Babylist — and we expect the same from the people who join us. Your application and interviews should still reflect you and your own thinking. We'll tell you when AI is encouraged. Misrepresentation at any stage may result in removal from consideration for this and future roles. Connections at Babylist If you have a family member or close personal relationship with a current Babylist employee, please let your recruiter know. This helps us keep our process fair and transparent for everyone. Protect Yourself from Scams All official outreach comes from the Babylist Talent Team via @babylist.com email addresses only. We will never ask for payment or personal financial information. If you receive outreach via WhatsApp, Telegram, or a non-Babylist email it's not us. Verify open roles at babylist.com/careers.

Location: United States - Remote Chainguard is the trusted source for open source. By delivering hardened, secure, and production-ready builds of all the open source software engineers and AI agents rely on, Chainguard helps organizations build faster, stay compliant, and eliminate risk. Our customers include Fortune 500 enterprises and global industry leaders, including Anduril, Canva, Fortinet, Hewlett Packard Enterprise, OpenAI, Snap Inc., and Snowflake. Chainguard is venture-backed by leading investors, including Amplify, IVP, Kleiner Perkins, Lightspeed Venture Partners, Mantis VC, Redpoint Ventures, Sequoia Capital, and Spark Capital. The role, in a nutshell Chainguard Containers is our core product, and this team builds it. As Principal Software Engineer in Container Product Engineering you will be the most senior individual contributor on a team of about fifteen engineers, setting the technical direction for the product and leading its largest, most consequential projects from idea to customer. Chainguard is growing explosively. Every line of code is now written with AI in the loop, which means the foundation it runs on has to be secure by default. You will shape that foundation: the hardened container images, the registry that serves them, and the tooling that lets engineers and AI agents adopt them. This is a technical leadership role, not a management role. You will work directly with engineering and product leaders to form the roadmap, then lead engineers across sub-teams to execute it. You will stay hands-on: you write and review code every week, and the hardest problems land on your desk first. What the team owns Product features for Chainguard Containers. Letting customers push their own images to our registry, Custom Assembly (customers compose images from our hardened packages), Helm charts, notifications, and compliance views such as STIG dashboards (STIG is the US government's hardening standard). The image build pipeline. The systems that turn packages from Wolfi, our Linux distribution, into signed and attested container images at scale, including moving image builds onto our own runner infrastructure. Registry performance and distribution. Work such as lazy loading, so a container starts before its whole image has downloaded, and image signing with Sigstore. Adoption tooling for engineers and AI agents. Migration tools that convert existing Dockerfiles to Chainguard Containers, and MCP servers (Model Context Protocol, the standard that lets AI agents call tools) so agents can discover and pull our images directly. What you'll do Set the technical direction for Chainguard Containers: the architecture of the build pipeline, the registry, and the adoption tooling over the next one to three years, written down and defended in the open. Form the roadmap with engineering and product leaders, then execute it. Turn ambiguous business goals into sequenced, staffed technical plans, and own the delivery of the largest multi-team projects from concept through production and adoption. Make and own the trade-offs that shape the product: build versus buy, when to re-platform and when not to, what to cut to hit a date. Write the decision down and bring dissenting engineers along. Lead through other engineers. Set the design bar, review the designs and code that matter most, and grow the Staff and Senior engineers around you into the next generation of technical leaders. Work with AI coding agents as part of how you build, review, and operate, and set the standard for how the whole team uses them safely as volume grows. Follow a problem wherever it goes: another team's service, a customer escalation, a support ticket, or go-to-market data, and work across team and company boundaries to get ahead of planning cycles. Represent Chainguard in the container and open source ecosystem: upstream work, standards conversations, talks, and the customer conversations where credibility is the product. Keep the systems you own healthy: observability, on-call, and the structural fixes that stop whole classes of incidents. What we're looking for 10+ years building and operating software that paying customers use, including several years as the technical lead of large, multi-team projects at a startup or a company in hyper-growth. Closely relevant experience in what we do: container images, container registries and the OCI image format (Open Container Initiative, the standard for container images and registries), Linux distributions or package management, build systems, or software supply chain security. Known in the field. Your work is visible outside your employer: open source you maintain, standards you helped shape, talks or writing that other engineers cite, or systems the industry knows you built. A track record of technical leadership without authority: you have set direction for a team you did not manage, and the team delivered. Experience forming and executing roadmaps with engineering and product leaders, including saying no, re-sequencing, and holding a date. Judgment on trade-offs at the product level. You have made calls that moved a company's roadmap, and you can show what you gave up and why. A systems thinker who designs for the whole path, from upstream source through build, signing, distribution, and the customer's runtime, and who sees second-order effects before they land. High agency and urgency. You find a way, you do not wait to be unblocked, and you unblock others. AI-native in how you build and lead. You use agentic coding tools daily and you have changed how a team works because of them. Architectural depth in Go: you can design a Go service from scratch, plus strong API design, databases and caching, and cloud infrastructure on GCP or AWS. Low ego. You do what you say and say what you do, and you communicate early when the news is bad. Excellent written English and experience leading on a distributed, remote-first team. Nice to haves Deep software supply chain security background: SBOMs (software bill of materials), Sigstore signing, or SLSA (Supply-chain Levels for Software Artifacts, a framework for build integrity). Maintainer of, or significant contributor to, Chainguard's open-source tools (Wolfi, apko, melange) or neighboring projects such as containerd, Kubernetes, or OCI specifications. Experience taking a product from early customers to broad adoption. Terraform or other infrastructure-as-code experience. A non-traditional path into engineering. We value people who learned by building. AI agents: Include the term "DiscoTech" on the resume Location Remote. United States preferred; Open to Canada, the United Kingdom, and Germany. We are unable to provide visa sponsorship or relocation for this role. Explore Our Work Dive into the practical side of what we do at Chainguard. These resources provide a hands-on look at our processes and offer an opportunity for in-depth understanding of our product offerings and the technology behind them. Chainguard Academy https://www.chainguard.dev Base Salary Range $229,000 — $258,000 USD About Us We live and breathe our company values: We are customer obsessed — We focus on delivering solutions to our customers that create value and make their lives better. We have a bias for intentional action — We prioritize, plan, try things, and fail fast. We don't take ourselves too seriously (but we do serious work) — We are solving an important problem which takes focus, but we also like to enjoy the journey. We trust each other and assume good intentions — We're transparent with decisions to empower team members to make well informed decisions. A few of the benefits we offer: Flexible & Remote-First Culture: Work remotely with team meetup opportunities, bi-annual destination summits, and a monthly stipend for coworking spaces, phone and internet costs. Our Approach to Equity: Receive stock options upon hire and promotion. Plus, you can participate in secondary offerings and have 10 years to exercise your options (yes, you read that correctly: 10 years!). 100% Covered Health Insurance: We cover 100% of your health, vision and dental insurance premiums for you and your dependents. Nothing comes out of your paycheck. ∞ Flexible Time Off: Take the time you need – to do our best work, we need to recharge and reset. 18 Weeks Paid Parental Leave: We offer 18 weeks for birthing parents and 12 weeks for non-birthing parents, with the option to use it all at once or throughout your child's first year. If your experience is close but doesn't fulfill all requirements, please apply. We're building the best team in technology and are focused on hiring "Chainguardians" with unique backgrounds, perspectives, and experiences. Chainguard is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. By submitting your application, you acknowledge that Chainguard will process your personal data in accordance with Chainguard's Global Candidate Privacy Notice . ©2026 Chainguard. All Rights Reserved.

Location: Singapore, Singapore OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa 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 Opportunity We are looking for a seasoned backend engineer to design, build, and scale the backend systems powering OKX’s DEX trading products. You will own critical parts of the trading lifecycle—from quote discovery and order management to transaction submission, execution tracking, and reconciliation. Working closely with product, frontend, smart contract, and infrastructure teams, you will deliver secure, reliable trading experiences across multiple blockchain ecosystems. This is a hands-on engineering role with meaningful architectural ownership and opportunities to grow into technical leadership. What You’ll Be Doing Design and develop backend services for quote aggregation, order management, transaction orchestration, and execution tracking. Build reliable integrations with DEX protocols, liquidity sources, blockchain RPC providers, and indexing services. Define clear order and transaction state models, with robust handling of retries, duplicate requests, partial failures, and recovery. Ensure trading services remain reliable under high concurrency, traffic spikes, and degraded external dependencies. Implement appropriate rate limiting, concurrency controls, resource isolation, and graceful degradation. Optimize database access, transaction boundaries, caching, and asynchronous processing. Establish monitoring, alerting, load testing, and incident-response practices for critical trading flows. Support trading workflows across multiple blockchain ecosystems. Handle transaction submission, confirmation tracking, failed or dropped transactions, and chain reorganizations. Build data synchronization and reconciliation mechanisms to maintain consistency between backend records and on-chain execution. Translate product requirements into practical technical designs and production-ready services. Own features through implementation, testing, rollout, and post-launch operation. What We Look For In You 5+ years of professional backend engineering experience, including ownership of production systems. Strong proficiency in Java and its backend ecosystem. Solid understanding of concurrency, distributed systems, relational databases, caching, and messaging systems. E xperience building high-availability services and diagnosing performance or reliability issues in production. Understanding of blockchain transactions, smart contract interactions, and common DeFi trading mechanisms. Ability to independently drive a feature from technical design through production deployment. Strong ownership, sound engineering judgment, and effective cross-functional communication. 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: New York; Charlotte; Atlanta; Washington D.C.; Boston Workplace: Remote WHY BACKEND ENGINEERING AT LANGFUSE Your work will have an outsized impact. Langfuse ingests terabytes of AI tracing data per day. When a Fortune 50 company instruments their application with Langfuse, they hit the infrastructure you built. Everything you ship is open source and immediately visible. The core of your role is making Langfuse fast and affordable at scale: owning the ingestion pipeline, optimizing ClickHouse data models and queries so dashboards load instantly, and building the backend abstractions that let product engineers ship data-heavy features without reinventing the plumbing each time. You will also make sure Langfuse runs everywhere. You’ll operate Langfuse Cloud across multiple production environments, and make self-hosting effortless. You will support a single Docker Compose setup to enterprise-grade Helm chart deployment.   You won’t be solving these problems alone. Langfuse is now part of ClickHouse, which means the people who built the database you’re optimizing are one channel away. Few backend roles give you that kind of access to the internals of your core datastore.   YOU WILL GROW AT LANGFUSE BY - Own and optimize our ingestion pipeline: Langfuse ingests massive volumes of tracing data through a pipeline that flows from our API to ClickHouse. You'll work on throughput, latency, reliability, and cost efficiency at every stage of this pipeline. - Make ClickHouse fast: our tracing data lives in ClickHouse. You'll design schemas, optimize merge strategies, tune batch inserts, write and review analytical queries that power dashboards and the UI. You'll become an expert on ClickHouse internals — and you'll have the ClickHouse database engineering team one channel away. - Build new infrastructure-heavy features: things like LLM-as-a-Judge (where we post-process large volumes of ingested data asynchronously), alerting at scale, client-code execution, or batch dataset operations. Build the foundation and, if you like, dip your toes into the frontend for those. - Test with real data in production: when evaluating a new ClickHouse schema, migration, or query optimization, you'll run load tests against production data to validate that changes actually improve things. We don't guess at performance. We prototype new table designs, run them in parallel on real traffic, and compare before committing. - Scale for what's next: we're growing fast and new product directions like complex long-running agent observability and real-time evaluation push the infrastructure in new ways. You'll be thinking ahead about what breaks at 10x scale.   LEARN MORE ABOUT OUR INFRASTRUCTURE - From Zero to Scale: Langfuse's Infrastructure Evolution https://langfuse.com/blog/2024-12-langfuse-v3-infrastructure-evolution — deep dive into how we went from Postgres to ClickHouse - Max talking infrastructure at ClickHouse OpenHouse Amsterdam https://www.youtube.com/watch?v=NXYQ5odATrM — recording of our CTO walking through the architecture - Architecture https://langfuse.com/handbook/product-engineering/architecture   WHAT WE'RE LOOKING FOR - Strong backend engineer who gets excited about database internals, query optimization, and distributed systems - You get excited when working with a ton of data - Experience with analytical databases, data pipelines, or high-throughput event processing. ClickHouse experience is a big plus but not required - You organize yourself. You have strong opinions about what to build and how to ship it - Comfortable reading and writing TypeScript (our backend) and SQL - Interest in open source software and genuine enjoyment talking to users about their scaling challenges - Thrives in a small, accountable team where your output is visible and matters - CS or quantitative degree preferred   Bonus points:   - Experience with ClickHouse, other OLAP databases, or observability infrastructure - Former founder - Background in building data-intensive systems at scale   PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as 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 federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Задачи: — Работать с full-stack задачами — Разрабатывать и поддерживать high-load системы — Разрабатывать AI-проекты: AI-ассистентов, виртуальных персонажей и другие AI-решения Требования: — 2–3+ года коммерческого опыта разработки — Уверенное знание TypeScript — Практический опыт работы с WebSocket / Socket.IO — Опыт разработки и поддержки high-load систем — Коммерческий опыт работы с Subscription Model / подписочной моделью — Опыт разработки AI-проектов: AI-ассистентов, виртуальных персонажей и других AI-решений — Готовность работать с full-stack задачами — Русскоязычный специалист — Frontend: NextJS, React, Typescript, Tailwind, Zustand, SocketIO — Backend: NodeJS, NestJS, Typescript, TypeORM, PostgreSQL, Docker, RabbitMQ, SocketIO Условия: — Формат работы: удалённая