Вакансии

Руководить командой SRE: нанимать и растить инженеров, честно давать обратную связь, в том числе трудную. Технические собеседования проводишь сам.

Location: Brazil; Peru; Colombia; Argentina; Mexico; Chile Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. Kraken's engineers build a lot of software. Developer Platform AI builds the AI systems they use to do it: agents that write and review code, simple access to the best models in the tools they already use, and the infrastructure that connects AI to our internal systems. This is a small team with a lot of reach. The tools you ship will change how engineers across Kraken work every day, and you'll see that happen directly. The work spans agent platforms, code review, LLM routing and cost controls, MCP integrations with tools like Slack, Jira and GitLab, and the security and observability that make all of it safe to run. If you want to work on applied AI with real users from day one, this is that job.   THE OPPORTUNITY - LLM traffic doesn't behave like normal API traffic. Requests are long-running, streaming and expensive. One prompt can cost a few cents or a few dollars. One team's burst can burn another team's budget. Providers change their rate limits, failure modes and pricing without warning. Running this well is a problem few companies have solved, and it's the job. - Own the reliability of the platform engineers depend on: the AI Gateway, the agent runtime and the connections to internal tools. Set the SLOs, own the error budgets and decide what happens when they're spent. - Design resilience across model providers: routing, failover, retries, rate limiting and graceful degradation when a provider is slow, throttling or down. - Make LLM traffic legible. Build observability that shows latency, errors, token usage and cost by team, model and use case, so engineers can see what their workloads cost and where they're spending their time waiting. - Treat capacity and cost as one problem. Routing decisions affect both latency and spend, and you'll own the tradeoff directly. - Work with Security, Finance and AI governance to put access controls, budgets, audit logging and data handling into the platform, not into a spreadsheet next to it. - Lead incident response and blameless post-incident reviews. Turn what breaks into fixes that stay fixed. - Automate operations with infrastructure as code, safe deployments and progressive rollouts, so the platform gets more reliable as it grows rather than more fragile. - Mentor engineers and raise the operating standard across the team. This is a Staff role. You'll set the technical direction for how the platform runs, not just keep it running. The platform is small enough that your decisions shape it directly, and used broadly enough that they affect every engineering team at Kraken. SKILLS YOU SHOULD HODL - Extensive experience in site reliability, infrastructure or platform engineering, with a track record of owning high-traffic, business-critical services in production - Deep hands-on experience with Kubernetes, a major cloud provider and infrastructure as code such as Terraform - Strong command of SLOs, observability and incident management, and the judgment to know which reliability work actually matters - Proficiency in Rust or Python, and comfort reading and changing a production service's code - Experience with API gateways, reverse proxies or traffic management: load balancing, rate limiting, failover and caching - Experience operating multi-tenant internal platforms, including authentication, authorization and per-tenant cost controls - Staff-level influence: you set direction across teams, write clear design documents and bring other engineers with you NICE TO HAVES - Experience operating LLM gateways or integrating LLM provider APIs at scale: streaming, token-based rate limiting, model routing and caching - Experience serving models yourself, including vLLM or Ray: GPU scheduling, batching, autoscaling and cost per token - Experience building Kubernetes controllers or operators with controller-runtime or kubebuilder - Experience with Consul and Vault for service discovery, configuration and secrets - Experience with model evaluation pipelines for catching quality regressions before and after rollout - Familiarity with coding agents and agent harnesses, and running them safely in sandboxed environments - Experience with cost attribution, budgeting or FinOps for usage-based services - Background in security-sensitive or regulated environments such as financial services or crypto - Contributions to open-source gateway, proxy or observability projects Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: Lisbon, Portugal About the Role The Site Reliability Engineering team at iCapital is fundamental to ensuring our platform delivers consistent, reliable service to our client base. Our services run on Kubernetes in AWS, and this role focuses on keeping them healthy in production. We're looking for the hands-on engineer others turn to when production is broken and the cause isn't obvious. You'll troubleshoot across the full stack (the application, its containers, Kubernetes, and the underlying cloud infrastructure) and turn what you learn into lasting improvements: stronger reliability standards, safer rollouts, sharper alerts, and automation that prevents repeat failures. You'll rely on metrics, logs, and traces every day, but the heart of this role is diagnosing and fixing what they reveal. Responsibilities Act as a senior escalation point for complex production issues in Kubernetes-based services, leading hands-on investigation across application, container, Kubernetes, and AWS layers through to root cause. Partner with the teams that own our cluster infrastructure to resolve platform-level issues, and feed what you learn back into reliability standards and improvements. Define and implement reliability and operability standards for Kubernetes-based services, including resource sizing, health checks, scaling patterns, rollout safety, and baseline monitoring, as part of service onboarding. Serve as Incident Commander or senior technical lead for high-severity incidents, lead postmortems, and drive systemic improvements through action items and measurable follow-through. Turn recurring investigations into runbooks, diagnostic tooling, and automated remediation that shorten time to resolution and eliminate toil. Coach engineers in systematic troubleshooting and Kubernetes best practices through reviews, game days, and knowledge sharing. Define, implement, and iterate service level objectives (SLOs) and service level indicators (SLIs) that reflect customer and business expectations. Standardize monitoring and alerting through “monitors as code” (Terraform preferred), including quality gates such as severity, ownership, and runbook links. Operate and tune OpenTelemetry pipelines, including sanitizing data, managing cardinality, and enriching telemetry with consistent fields. Maintain the infrastructure behind our monitoring stack, including Helm charts, ArgoCD ApplicationSets, Kinesis streams, Lambda functions, and Prometheus. Participate in on-call rotations with a focus on improving reliability, reducing alert noise, and increasing signal quality over time. What You'll Need (Must-Haves) 5+ years in SRE or related roles, with evidence of technical seniority across multiple services and teams. 3+ years of hands-on experience running and troubleshooting production workloads on Kubernetes, with a deep understanding of how Kubernetes schedules, connects, scales, and rolls out workloads. Proven ability to independently diagnose complex failures in distributed systems running on Kubernetes, spanning application, configuration, resource, networking, and scaling issues, including cases where the root cause wasn't obvious. Strong Linux and networking fundamentals, with the ability to troubleshoot below the container layer. Strong production experience with AWS, including how cloud networking and access controls affect workloads running in Kubernetes. Strong incident response skills, including leading retrospectives/postmortems and following through on systemic fixes. Strong IaC skills (Terraform preferred), with examples of reusable modules, monitors-as-code patterns, or similar standardization work, and the coding ability to build automation and diagnostic tooling. Track record of defining SLOs/SLIs and using an observability stack (such as Prometheus/Grafana, New Relic, Splunk, or similar) to drive decisions and find root causes quickly. Clear written and verbal communication, with the ability to influence engineering teams through standards, tooling, and practical guidance. Nice to Have Kubernetes certification (CKA or CKS) or equivalent depth. Experience improving rollout safety and autoscaling behavior for Kubernetes workloads. Familiarity with common data stores (Postgres, MongoDB, DynamoDB) and how they fail in distributed systems. OpenTelemetry instrumentation experience at scale. We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office four days, with the flexibility to work remotely one day (Friday). Benefits iCapital offers a comprehensive benefits package that includes a total compensation program consisting of competitive salary, annual performance bonus, and equity for all full-time employees; healthcare with 100% employer-paid health and dental insurance; and generous paid time off (PTO). For additional information on iCapital Network, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc

Location: Москва Workplace: гибкий Группа разработки HPC-инфраструктуры занимается созданием суперкомпьютера, на котором обучается вся компания. Мы строим HPC-сегменты с использованием технологий InfiniBand и RoCE, а поверх них — ML-платформу на базе Kubernetes. Задачи Разработка и развитие компонентов ML-платформы и инфраструктурных сервисов Автоматизация процессов запуска, сопровождения и мониторинга ML/HPC workloads Повышение надёжности, производительности и масштабируемости платформы Развитие CI/CD и внутренних инструментов для эксплуатации платформы Взаимодействие с командами разработки и ML-инженерами по вопросам платформы и инфраструктуры Требования Опыт разработки инфраструктурных и platform-компонентов на Go Углубленные знания Linux, включая понимание работы ОС, сетевого стека и механизмов контейнеризации Хорошее понимание сетей, сетевых протоколов и диагностики проблем связности Знание архитектуры и принципов работы Kubernetes Навыки troubleshooting на всех уровнях инфраструктуры: хост, контейнеры, runtime, сеть Опыт автоматизации инфраструктурных процессов и разработки внутренних инструментов Понимание принципов надёжности, масштабируемости и observability production-систем Будет плюсом Опыт работы с ML / MLOps / HPC workloads Опыт разработки на Python Опыт работы с CI/CD, monitoring и platform tooling

Location: Москва Workplace: Дистанционный Мы разрабатываем крупнейший мессенджер в России, чтобы соединять людей, сервисы и компании. Создаём простые и удобные инструменты коммуникации. Задачи Развивать и сопровождать инфраструктуру highload-системы, повышать надёжность, доступность и производительность Внедрять и поддерживать SLO/SLI и практики error budget, выстраивать алертинг на основе пользовательских метрик и приоритизации Развивать observability (Prometheus/Alertmanager, Grafana, централизованные логи): делать эксплуатационные дашборды, настраивать алерты, снижать alert noise, улучшать MTTD/MTTR Автоматизировать рутинные операции и эксплуатационные процессы, снижать toil, развивать self-service подходы для команд разработки Участвовать в on-call , оперативно реагировать и устранять инциденты, координировать восстановление, проводить postmortem и доводить улучшения до продакшена Взаимодействовать с командами разработки и смежными инфраструктурными командами: участвовать в архитектурных обсуждениях, ревью изменений, согласовании требований к production readiness Вести и развивать эксплуатационную документацию : писать и актуализировать runbooks/playbooks для типовых инцидентов и деградаций, инструкции по релизам/роллбэкам и аварийным процедурам (в том числе DR), документировать дашборды/алерты и схемы зависимостей/эскалаций Требования Опыт 5+ лет в SRE/DevOps/Platform/System Engineering, опыт эксплуатации highload -систем Глубокие знания Linux : администрирование, диагностика производительности (CPU/mem/io), анализ деградаций, systemd, файловые системы, лимиты/квоты, troubleshooting на production Сетевые основы для диагностики : TCP/IP, DNS, HTTP/HTTPS, TLS, L4/L7 балансировка, keepalive; умение находить и устранять сетевые причины деградаций Опыт эксплуатации распределённых систем : понимание partial failures, timeouts/retries, backpressure, graceful degradation Облака: опыт эксплуатации инфраструктуры в публичном облаке — сети и балансировщики, autoscaling, IAM/роль‑модель; построение отказоустойчивости по зонам/регионам, базовые DR-подходы Контейнеры и Kubernetes: понимание контейнеризации и практический опыт работы с Kubernetes на уровне эксплуатации (деплой, конфигурации, диагностика проблем приложений/окружения) Infrastructure as Code : Terraform (или аналог) + Ansible; Git‑workflow, code review, версионирование инфраструктуры CI/CD и управление изменениями : безопасные релизы (canary/blue‑green), rollback стратегии, снижение рисков изменений Код и автоматизация: чтение чужого кода (Go/Java/Python) для диагностики; написание автоматизации (Python/Go/Bash), создание утилит/джоб для эксплуатации Observability: Prometheus/Alertmanager, Grafana, централизованные логи (Graylog/ELK) — дашборды под эксплуатацию, алерты с учётом снижения шума и приоритизации SRE-практики : SLI/SLO, error budget, incident response, postmortem без поиска виноватых Готовность к on-call и участие в разборе и устранении инцидентов Навыки создания и поддержки эксплуатационной документации : runbooks/playbooks, инструкции по деплою/роллбэку, схемы архитектуры, описания SLO/алертов; умение писать кратко и так, чтобы документ работал в инциденте Будет плюсом Опыт с БД/кешами/очередями: PostgreSQL/Redis/Cassandra/Kafka/ClickHouse и так далее Сопровождение Java: JVM/GC, heap/thread dumps, профилирование, диагностика latency Security basics: secrets management, least privilege

Location: Москва Workplace: Офис, Гибридный Яндекс 360 — это виртуальный офис для работы команды. Мы создаём экосистему, которой пользуются миллионы людей и тысячи компаний. Ищем сильного CRE-инженера в нашу команду. Это идеальная роль для тех, кто любит сложные задачи в Linux и хочет видеть бизнес-результат своей работы. Яндекс 360 — это виртуальный офис для работы команды: корпоративная Почта, Диск, Документы, Телемост, Мессенджер, Доски, Трекер и Вики. Мы создаём экосистему, которой пользуются миллионы людей и тысячи компаний. Наше направление on-premise занимается поставкой этих сервисов в закрытые контуры крупных корпоративных заказчиков (Enterprise). Это сложные распределённые инсталляции, высокие требования к безопасности и надёжности. Мы ищем CRE-инженера (Customer Reliability Engineer), который станет мостиком между инфраструктурой заказчика и нашей разработкой, обеспечивая надёжную работу наших продуктов на стороне клиента. Вы столкнётесь с разными задачами на инфраструктуре заказчика. Это идеальная роль для тех, кто любит сложные задачи в Linux и хочет видеть бизнес-результат своей работы. Обязанности Решение сложных технических задач Вам предстоит разбираться в инцидентах, которые не смогла решить первая и вторая линии поддержки. Вы будете анализировать логи, дампы сетевого трафика, поведение ядра Linux и работу баз данных, чтобы находить корневую причину (Root Cause Analysis). Эксплуатация и внедрение Вы будете помогать заказчикам разворачивать и обновлять инсталляции Яндекс 360 на их серверах — вам предстоит работать с гетерогенными средами, где «железо» и сеть не под нашим прямым контролем. Автоматизация работы Вам нужно будет писать скрипты и инструменты (Python/Bash), а также создавать плейбуки. Влияние на продукт Вам предстоит отвечать за надёжность систем, передавать разработчикам качественную обратную связь «с полей», а также помогать адаптировать архитектуру сервисов под реалии on-premise-эксплуатации. Выстраивание коммуникаций Вы будете общаться с техническими специалистами и системными администраторами на стороне крупных заказчиков. Требования * Работали с базами данных: знаете основы администрирования PostgreSQL и S3-совместимых хранилищ, умеете писать простые SQL-запросы и читать логи БД * Глубоко знаете Linux: понимаете, как работает ОС «под капотом» (память, процессы, дисковая подсистема, namespaces), умеете пользоваться strace, tcpdump, lsof, perf * Разбираетесь в сетях: знакомы с моделью OSI, протоколами TCP/IP, знаете, как работает DNS, балансировка нагрузки (L3/L7), умеете диагностировать сетевые проблемы * Умеете программировать: пишете на Python для автоматизации рутины, уверенно владеете Bash * Знакомы с контейнеризацией: понимаете принципы работы Docker/Containerd, имеете опыт работы с оркестраторами (K8s) * Обладаете эмпатией: готовы погружаться в проблемы клиента и не просто «закрывать тикеты», а действительно решать задачу Будет плюсом * Работали в роли SRE, DevOps или системного администратора в HighLoad-проектах * Знаете системы управления конфигурациями (Ansible) * Умеете работать с мониторингом (Prometheus, Grafana, ELK-стек) * Понимаете CI/CD-процессы

Location: San Francisco; Remote (United States); Seattle; New York City Perplexity serves hundreds of millions of queries a month. Every answer, every Perplexity Computer task, and every enterprise deployment runs on production infrastructure owned by the Cloud Infrastructure team: a fleet of Kubernetes clusters across a multi-account AWS estate, private networks that reach hyperscalers and the neoclouds serving our models, and the storage underneath our user data and agentic workloads. We're looking for SREs who treat reliability as a software problem. You'll own compute, networking, and storage at scale and keep production stable while everything built on top of it is changing fast. RESPONSIBILITIES - Own production at scale. Run the compute, networking, and storage foundation behind Perplexity's consumer, Computer, API, and enterprise products, and own its availability, latency, and cost. - Run our Kubernetes fleet. Operate and upgrade the EKS clusters that host web services, search, datastores, and secure sandboxes. Tune scheduling, autoscaling, node lifecycle, DNS, and service networking so clusters stay healthy under bursty, fast-growing load. - Engineer the network. Design and operate VPC architectures, Transit Gateway and PrivateLink connectivity, load balancing, DNS, and egress across accounts, regions, and cloud providers. - Keep data durable and fast. Own the storage layer (EBS, S3, DynamoDB, and the managed databases and caches our services depend on), including performance, durability, backups, and restores that have actually been tested. - Manage everything as code. Run infrastructure through Terraform and CI/CD. Build reusable modules and guardrails, and make every change reviewable, repeatable, and safe to roll back. - Prepare for failures. Define SLOs, build alerts that someone can act on, design for zone and regional failure, and run game days and disaster-recovery exercises that prove recovery works. - Lead incident response. Be on the critical path when things break. Drive incidents to resolution, write blameless postmortems, and land the fixes so the same failure never pages anyone twice. - Scale ahead of demand. Own capacity planning, quotas, reservations, and cost efficiency so product launches and traffic spikes never wait on infrastructure. - Automate away the toil. Build tooling, increasingly agent-driven, that turns provisioning, upgrades, and remediation into self-serve, hands-off workflows for every engineering team. QUALIFICATIONS We expect you to have real depth in most of these: - Deep AWS expertise. You know VPC, IAM, EC2, EKS, ELB, Route 53, S3, EBS, etc. well past the console, including their limits, failure modes, and the bill that comes with them. - Production Kubernetes at scale: cluster upgrades, CNI, CoreDNS, autoscalers like Karpenter, and debugging a misbehaving node at 3 a.m. Writing Helm charts alone doesn't count. - Terraform mastery. You've designed module structures, managed state across many accounts, and run large refactors and imports without taking production down. - Strong networking fundamentals (TCP/IP, DNS, TLS, load balancing, routing). - You write real code in Python, Go, or Rust for automation, tooling, and controllers, and you'd rather automate a runbook than follow it. - Fluency with observability tools like Datadog, Prometheus, or Grafana, and the judgment to turn metrics, logs, and traces into SLOs and alerts that matter. - A track record of leading production incidents and turning root-cause analysis into durable fixes. - You own problems end-to-end and do well when the path forward isn't laid out for you. ADDITIONAL EXPERIENCE WE VALUE - Multi-region active-active or failover architectures, and disaster-recovery programs with real recovery targets. - Proxies, service meshes, and kernel-level networking: Envoy, Istio, Cilium, or eBPF. - GitOps and progressive delivery: Argo CD, Flux, or similar. - Enterprise and compliance environments: single-tenant or BYOC deployments, KMS/BYOK, SOC 2 or similar controls. - Running stateful systems in production: Postgres, Redis, or search engines like Vespa or Elasticsearch. - Multi-cloud or neocloud operations (GCP, CoreWeave, or similar). - FinOps: cost attribution, Savings Plans and reservations, and making infrastructure cheaper without making it fragile.

Location: San Francisco; Remote (United States); Seattle; New York City Perplexity serves hundreds of millions of queries a month. Every answer, every Perplexity Computer task, and every enterprise deployment runs on production infrastructure owned by the Cloud Infrastructure team: a fleet of Kubernetes clusters across a multi-account AWS estate, private networks that reach hyperscalers and the neoclouds serving our models, and the storage underneath our user data and agentic workloads. We're looking for SREs who treat reliability as a software problem. You'll own compute, networking, and storage at scale and keep production stable while everything built on top of it is changing fast. RESPONSIBILITIES - Own production at scale. Run the compute, networking, and storage foundation behind Perplexity's consumer, Computer, API, and enterprise products, and own its availability, latency, and cost. - Run our Kubernetes fleet. Operate and upgrade the EKS clusters that host web services, search, datastores, and secure sandboxes. Tune scheduling, autoscaling, node lifecycle, DNS, and service networking so clusters stay healthy under bursty, fast-growing load. - Engineer the network. Design and operate VPC architectures, Transit Gateway and PrivateLink connectivity, load balancing, DNS, and egress across accounts, regions, and cloud providers. - Keep data durable and fast. Own the storage layer (EBS, S3, DynamoDB, and the managed databases and caches our services depend on), including performance, durability, backups, and restores that have actually been tested. - Manage everything as code. Run infrastructure through Terraform and CI/CD. Build reusable modules and guardrails, and make every change reviewable, repeatable, and safe to roll back. - Prepare for failures. Define SLOs, build alerts that someone can act on, design for zone and regional failure, and run game days and disaster-recovery exercises that prove recovery works. - Lead incident response. Be on the critical path when things break. Drive incidents to resolution, write blameless postmortems, and land the fixes so the same failure never pages anyone twice. - Scale ahead of demand. Own capacity planning, quotas, reservations, and cost efficiency so product launches and traffic spikes never wait on infrastructure. - Automate away the toil. Build tooling, increasingly agent-driven, that turns provisioning, upgrades, and remediation into self-serve, hands-off workflows for every engineering team. QUALIFICATIONS We expect you to have real depth in most of these: - Deep AWS expertise. You know VPC, IAM, EC2, EKS, ELB, Route 53, S3, EBS, etc. well past the console, including their limits, failure modes, and the bill that comes with them. - Production Kubernetes at scale: cluster upgrades, CNI, CoreDNS, autoscalers like Karpenter, and debugging a misbehaving node at 3 a.m. Writing Helm charts alone doesn't count. - Terraform mastery. You've designed module structures, managed state across many accounts, and run large refactors and imports without taking production down. - Strong networking fundamentals (TCP/IP, DNS, TLS, load balancing, routing). - You write real code in Python, Go, or Rust for automation, tooling, and controllers, and you'd rather automate a runbook than follow it. - Fluency with observability tools like Datadog, Prometheus, or Grafana, and the judgment to turn metrics, logs, and traces into SLOs and alerts that matter. - A track record of leading production incidents and turning root-cause analysis into durable fixes. - You own problems end-to-end and do well when the path forward isn't laid out for you. ADDITIONAL EXPERIENCE WE VALUE - Multi-region active-active or failover architectures, and disaster-recovery programs with real recovery targets. - Proxies, service meshes, and kernel-level networking: Envoy, Istio, Cilium, or eBPF. - GitOps and progressive delivery: Argo CD, Flux, or similar. - Enterprise and compliance environments: single-tenant or BYOC deployments, KMS/BYOK, SOC 2 or similar controls. - Running stateful systems in production: Postgres, Redis, or search engines like Vespa or Elasticsearch. - Multi-cloud or neocloud operations (GCP, CoreWeave, or similar). - FinOps: cost attribution, Savings Plans and reservations, and making infrastructure cheaper without making it fragile.

Инженерные и платформенные задачи (60–70% времени): проектировать и разрабатывать инструменты для управления парком баз данных — развивать управление инстансами в сторону Kubernetes-операторов вместо статического Terraform-кода, переработать систему наполнения дев-стендов, заниматься подготовкой и обезличиванием данных.

Location: Chicago, Austin DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. The Container Infrastructure team provides scalable on-premises and cloud-based container orchestration services for DRW’s trading desks, data scientists, and enterprise application teams. Our goal is to enable teams to keep focused on their business goals by providing simple, scalable solutions with off the shelf tools and the right amount of focused engineering. We’re looking to expand our Container Infrastructure team. In this role you work closely with other teams and trading desks to ensure the performance and reliability of our Kubernetes platform. The platform is large: hundreds of clusters, thousands of nodes, and dozens of components. Common day-two tasks include development of new components, monitoring costs, and ensuring compute consumption for each desk is optimized. As a member of this team you will help administer the platform, engage with internal customers and infrastructure stakeholders to ensure the platform remains reliable, performant, and cost-effective. Our philosophy: We believe in relentless automation of repetitive tasks. We have the curiosity and drive to dig deep and find creative solutions. We believe our goal is to find the right solution rather than always being right. We provide exceptional customer service to our teams and trading desks. We care more that the right thing is done than about rigid job descriptions or boundaries. What you’ll do: Work with different business units to ensure a successful onboarding and deployment of applications into DRW’s Kubernetes platform. Relentlessly automate repetitive manual tasks. Provide exceptional customer service to our platform’s users. Solve complex problems, build new features/components, get to work every day with exceptionally talented and curious coworkers. Your background: Experience working with or administering Kubernetes Clusters. Knowledge of networking, storage, and containerization fundamentals. Familiarity with AWS and/or Google Cloud Platform. A service focused attitude: you ask questions and focus on getting the right resources and solutions to people instead of rigid boundaries. Strong written and verbal communication skills. You can work across teams and have evidence-based discussions on technical and operational topics. You are eager to learn, collaborate, and find solutions under interesting constraints. Bonus points if you have: Experience with common Kubernetes operators (Flux, Fluentbit, Fluentd, Prometheus, etc.). Experience administering on-premise infrastructure. Experience developing, deploying, and supporting full stack web applications. Experience with multiple programming languages in both greenfield development and legacy maintenance. The annual base salary range for this position is $220,000 to $280,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . [#LI-SK1]

Location: London Workplace: OnSite Company Description We’re http://checkout.comCheckout.com http://Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. The Role Every payment we process runs on infrastructure we built. At Checkout.com http://Checkout.com, the Cloud Platform team owns the cloud foundations that global payments depend on: a large multi-account AWS estate, a growing Azure platform, and the networking and connectivity that reaches card schemes and banks worldwide. We are genuinely multi-cloud, and we are looking for a Senior Cloud Engineer who is too - a strong generalist who treats infrastructure as a software problem and can deliver from week one. This is a hands-on senior role in an established, fast-moving team. Everything we run is defined in code, deployed through pipelines, and reviewed like software. You will bring deep cloud expertise across AWS and Azure and pair it with a genuine software engineering mindset: you write Terraform modules others build on, you automate away toil rather than documenting it, and you treat the platform as a product with users, SLOs, and a roadmap. As a Senior Cloud Engineer, you are responsible for the technical delivery of your team's services. You will work closely with your Engineering Manager to shape direction, manage dependencies across pillars, and ensure our platform meets the standards a regulated payments business demands. What we are looking for: Deep AWS expertise: Advanced, hands-on experience designing and operating production infrastructure in AWS at enterprise scale: multi-account architectures (Control Tower, Organizations, SCPs), IAM, KMS, and the core compute, storage, and security services that a large regulated estate runs on. You should have a proven track record of delivering resilient, multi-region architectures. Azure experience: Real production experience with Azure alongside AWS: landing zones, VNet architectures, Entra ID, and the Azure resource and governance model. You understand where the two clouds differ and can design well for both rather than forcing one cloud's patterns onto the other. Software engineering mindset: You treat infrastructure as software. Expert-level Terraform: reusable modules, secure state management, and disciplined code review. You are comfortable in a Git-based workflow with CI/CD (we use Spacelift), and you reach for Python or similar to automate what others would handle with a runbook. No ClickOps. Strong cloud networking: Confident designing and debugging in a complex network estate: VPC and VNet design, hub-and-spoke and Transit Gateway or Cloud WAN architectures, DNS, private connectivity (PrivateLink, Private Link), and enough routing knowledge to own connectivity issues end to end rather than escalate them. Kubernetes: Solid experience running containerised workloads in production, ideally on EKS/AKS: cluster lifecycle, workload deployment patterns, and the operational realities of keeping Kubernetes healthy at scale. Security and compliance awareness: Experience operating in regulated environments. You understand why change control, least privilege, and auditability matter, and you design controls in rather than bolting them on. Familiarity with PCI DSS is a strong plus. Engineering excellence: A focus on observability and measurement: you instrument what you build and answer operational questions with data rather than opinion. Leadership and mentorship: A natural ability to guide and mentor peers, translate ambiguous problem definitions into actionable technical plans, and raise the bar through your code and your reviews. Pragmatic problem solver: You understand when to move fast (creating tech debt) and when to move right (paying it off). You are a cornerstone in incident resolution and root-cause analysis. Experience: 5+ years in cloud engineering roles with significant AWS depth. We need someone who can hit the ground running: comfortable joining a complex, established estate and delivering meaningful work in their first weeks, not their first quarter. A degree in Computer Science or a related field is useful but not required; we care about what you can build. HOW YOU’LL MAKE AN IMPACT: Lead Design & Delivery: Take ownership of large-scale platform projects end to end, from architecture through Terraform to production, ensuring they are scalable, secure, and cost-optimised. Build the paved road: Design the platform primitives that every product team at Checkout.com http://Checkout.com builds on, so that the secure path is also the easy path. Architectural Influence: Work with Engineering Managers and architects to refine requirements and shape the technical direction of the platform, documenting significant decisions as ADRs. Operational SME: Act as the Subject Matter Expert for numerous team-owned services, providing advanced operational support and ensuring high availability for our global payment systems. Evangelise Best Practices: Produce exemplary code and documentation that inspires others. You will be responsible for spreading best practices and standards across your group. Manage Dependencies: Navigate the organisation to manage technical dependencies inside and outside your pillar, optimising for both delivery speed and business outcomes. Foster Culture: Embody Checkout Operating Principles, using them to shape the group’s culture and acting as an example of efficiency and professional excellence. AI Integration: Proactively explore and implement AI-driven automation to enhance infrastructure efficiency and team productivity. Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here. It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com http://Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it’s like to be part of our team? Visit our Careers Page https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/

Поддерживать и развивать инфраструктуру дата‑платформы: HDFS, Spark, ClickHouse, Airflow и др. Запускать и эксплуатировать Ceph‑кластер с высокими требованиями к SLA.

Location: Bengaluru, Karnataka, India, APAC From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role Fivetran is looking for a high-performance, experienced engineer to be a part of a team of Senior Site Reliability Engineer. You will be working closely with engineering teams, product managers, as well as support and sales engineers to build the future of the Fivetran Data Platform Reliability. As a member of the Site Reliability Engineering team, you will take ownership of the overall performance and reliability of Fivetran’s infrastructure, the robustness of the deployment pipeline, as well as timely and effective incident response and resolution. You will take responsibility for the growth and stability of Fivetran’s infrastructure, and be a key player driving effective incident response and overall issue avoidance. Responsible for ongoing reliability and robustness of Fivetran’s production infrastructure by monitoring availability, capacity, and throughput. Evolve systems by adding reliability into our product roadmap Coordinate the re-prioritize or fix critical bugs for support or sales requirements as needed Make recommendations to production infrastructure by interfacing with engineering to ensure 100% availability Ensure scalable artifacts deployment to all environments by automation scripts Constantly monitor infrastructure vulnerabilities and remedy them by working with the security team Technologies You’ll Use Working knowledge of managed Kubernetes (EKS, AKS and GKE) Knowledge of Cloud Platforms and related tooling: AWS, Azure, GCP, Terraform, Ansible, Buildkite, Pulumi and ArgoCD Experience in Python/Shell scripting. Bonus if you have Java, GO, etc Experience with Linux operating systems internals and administration Experience with cloud networking like VPNs, Privatelinks, and Private Service connect (GCP) Experience with databases such as PostgreSQL Skills We’re Looking For 6+  Years of experience working with SaaS products at scale. Working knowledge of managed Kubernetes (EKS, AKS and GKE). Knowledge of Cloud Platforms and related tooling: AWS, Azure, Google Cloud (GCP), Terraform, Ansible, Buildkite, Pulumi and ArgoCD. Experience in Python/Shell scripting and Go Language. Bonus if you have Java. Experience with Linux operating systems internals and administration Experience with cloud networking like Site-to-Site VPNs, Privatelinks and Private Service connect (GCP) #LI-AV1 #LI-HYBRID Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

Location: New York ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. The Role We are seeking highly experienced Site Reliability Engineers (SRE) to shape the reliability, scalability and performance of our platform and customer facing applications. You will work closely with our software engineers and research teams to ensure our systems meet and exceed our internal and external customers' expectations.     What You Will Do As a Site Reliability Engineer, you balance the day-to-day operations on production systems with long-term software engineering improvements to reduce operational toil and foster the reliability, availability, and performance of these systems.   Operations • Design, build, and maintain scalable, highly available and fault-tolerant infrastructures to support our web services and ML workloads • Make sure our platform, inference and model training environments are always highly available and enable seamless replication of work environments across several HPC clusters • Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.) • Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime • Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our client-facing APIs and large training runs • Participate occasionally in on-call rotations to respond to incidents and perform root cause analysis to prevent future occurrences   Development • Drive continuous improvement in infrastructure automation, deployment, and orchestration using tools like Kubernetes, Flux, Terraform • Collaborate with AI/ML researchers to develop and implement solutions that enable safe and reproducible model-training experiments • Build a cloud-agnostic platform offering an abstraction layer between science and infrastructure • Design and develop new workflows and tooling to improve to the reliability, availability and performance of our systems (automation scripts, refactoring, new API-based features, web apps, dashboards, etc.) • Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements • Document processes and procedures to ensure consistency and knowledge sharing across the team • Contribute to open-source projects, research publications, blog articles and conferences   What We're Looking For • Master’s degree in Computer Science, Engineering or a related field • 7+ years of experience in a DevOps/SRE role • Strong experience with cloud computing and highly available distributed systems • Exposure to site reliability issues in critical environments (issue root cause analysis, in-production troubleshooting, on-call rotations...) • Experience working against reliability KPIs (observability, alerting, SLAs) • Hands-on experience with CI/CD, containerization and orchestration tools (Docker, Kubernetes...) • Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack, Datadog...) • Familiarity with infrastructure-as-code tools like Terraform or CloudFormation • Proficiency in scripting languages (Python, Go, Bash...) and knowledge of software development best practices • Strong understanding of networking, security, and system administration concepts • Excellent problem-solving and communication skills • Self-motivated and able to work well in a fast-paced startup environment   Your application will be all the more interesting if you also have: • experience in an AI/ML environment • experience of high-performance computing (HPC) systems and workload managers (Slurm) • worked with modern AI-oriented solutions (Fluidstack, Coreweave, Vast...) WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: San Francisco; New York Patreon is a media and community platform where over 300,000 creators give their biggest fans access to exclusive work and experiences. We offer creators a variety of ways to engage with their fans and build a lasting business including: paid memberships, free memberships, community chats, live video, and selling to fans directly with one-time purchases. Ultimately our goal is simple: fund the creative class. And we're leaders in that space, with: - $10 billion+ generated by creators since Patreon's inception - 100 million+ free memberships for fans who may not be ready to pay just yet, and - 25 million+ paid memberships on Patreon today. We're continuing to invest heavily in building the best creator platform with the best team in the creator economy and are looking for a Director of Platform Engineering to support our mission. This role is based in New York or San Francisco and open to those who are able to be in-office 2 days per week on a hybrid work model. About the Team We’re looking for a Director of Platform Engineering to lead the teams responsible for the core infrastructure and platform services that power Patreon’s product and ecosystem. This role is ideal for a senior engineering leader who has: - Scaled a consumer, UGC, or marketplace platform to millions of users - Led infrastructure and/or platform teams supporting product engineering at scale - Operated in environments with high availability, bursty traffic, and complex distributed systems You’ll partner closely with Product, Security, Data, and Product Engineering leaders to ensure Patreon’s platform is reliable, scalable, and developer-friendly. About the Role - Lead and grow multiple Platform & Infrastructure Engineering teams, including backend services, APIs, developer platforms, reliability foundations and AI enablement - Own the technical strategy and roadmap for scaling Patreon’s platform as usage, content, and integrations grow - Drive platform initiatives across: - Core backend services & APIs - Service reliability, availability, and performance - Platform scalability and capacity planning - Internal developer tooling and productivity - Partner with product engineering teams to enable faster feature delivery while maintaining platform stability - Establish strong operational excellence (on-call, incident response, SLAs, SLOs) - Hire, develop, and mentor senior engineering managers and technical leaders - Communicate clearly with executives and cross-functional partners about risks, tradeoffs, and platform investments About You Required: - 10+ years of engineering experience with 5+ years in engineering management - Experience leading platform, infrastructure, or foundational backend teams - Proven track record scaling a consumer product, UGC platform, or marketplace to millions of users - Strong background in distributed systems, APIs, and service-oriented architectures - Experience operating production systems with high availability and performance requirements Preferred: - Background in developer platforms, internal tooling, or platform abstractions - Familiarity with cloud infrastructure (AWS/GCP), data pipelines, and event-driven systems - Experience leading through major architectural transitions or scale inflection points About Patreon Patreon powers creators to do what they love and get paid by the people who love what they do. Our team is passionate about making this mission and our core values come to life every day in our work. Through this work, our Patronauts: - Put Creators First | They’re the reason we’re here. When creators win, we win. - Build with Craft | We sign our name to every deliverable, just like the creators we serve. - Make it Happen | We don’t quit. We learn and deliver. - Win Together | We grow as individuals. We win as a team. We hire talented and passionate people from different backgrounds because workplace diversity and inclusion is critical to our ability to serve creators worldwide. If you’re excited about a role but your past experience doesn’t match with every bullet point outlined above, we strongly encourage you to apply anyway. If you’re a creator at heart, are energized by our mission, and share our company values, we’d love to hear from you. Patreon is proud to be an equal opportunity employer. We provide employment opportunities without regard to age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class. If you need a reasonable accommodation during the interview process, please let us know via email at accommodations@patreon. Patreon offers a competitive benefits package including and not limited to salary, equity plans, healthcare, flexible time off, company holidays and recharge days, commuter benefits, lifestyle stipends, learning and development stipends, patronage, parental leave, and 401k plan with matching. Patreon operates under a hybrid work model, where employees based in office locations are expected to come into the office two days per week, excluding sick time and paid leave. The goal of this policy is to be intentional about the in-person time we spend together to strengthen the feeling of community at Patreon. Candidates hired into remote-eligible roles are not expected to meet the same requirements. At Patreon, we believe in fair and transparent pay. In compliance with New York and California pay transparency laws, we are sharing the expected salary range for this role. The posted salary range is dependent on the location and the level. This range may encompass multiple levels within the role’s job family. The final offer will be based on candidate’s experience, skills, competencies, and geographic location, aligning with the appropriate job level within Patreon’s leveling framework. For remote employees located outside CA and NY, salary may vary based on location and local market conditions. Patreon reserves the right to modify or update compensation and benefits at any time.

Location: New York, New York, United States About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Role: Enterprise AI - Platform Engineer Location: New York City, Madison Square Park area Reports to: Head of Engineering Experience Level: 6+ years Work Model: Hybrid, with regular in-office presence Why Join Enterprise AI? Enterprise AI is building the platform that enables reliable deployment of AI systems across enterprise environments. As a Platform Engineer, you will build and operate the core of Turing’s Enterprise AI platform, including platform services, the model gateway, multi-tenant infrastructure, CI/CD, infrastructure as code, and observability. The central challenge is creating repeatable deployments across environments Turing may not control, including client cloud accounts, dedicated instances, and sovereign installations. As a Platform Engineer, You Will Build Core Platform Services Design, build, and operate the services that support the Enterprise AI platform, including platform infrastructure and the model gateway. Enable Enterprise Deployment Create reliable deployment systems for client cloud accounts, dedicated instances, and sovereign environments. Own Infrastructure and Delivery Systems Build and maintain CI/CD, infrastructure as code, and deployment tooling across environments using Kubernetes, Helm, Terraform or Pulumi, and GitOps practices. Build for Reliability Design systems that support secure multi-tenant operation, reliable service ownership, and clear operational accountability. Establish Observability Build observability across the platform using service-level objectives, structured logging, metrics, tracing, and alerting. Build FinOps Visibility Develop telemetry that tracks model and compute costs by tenant. The Anti-Sell Hands-on software engineering: This is not a cloud-operations or ticket-queue DevOps role. You must be able to write production software and contribute deeply to platform services. Operational ownership: You will participate in on-call operations and incident response and help build the processes required to operate a production platform. Deployment complexity: The platform must operate across client cloud accounts, dedicated instances, and sovereign environments. Team accountability: The platform must be observable, operable, and maintainable by the team rather than dependent on one individual. Our Enterprise AI Platform Engineers Typically Have Production platform engineering experience: Six or more years of platform or infrastructure engineering experience supporting production SaaS. Customer-controlled deployment experience: Experience shipping a product that customers run in their own environment, including in a VPC, a self-hosted environment, or an air-gapped environment. Strong software engineering depth: Deep expertise in at least one backend language, such as Go, Ruby, Python, or TypeScript, with the ability to read and work across the others. Cloud and infrastructure expertise: Deep experience in at least one cloud and comfort working in a second, including private networking, KMS, IAM, Kubernetes, Helm, Terraform or Pulumi, and GitOps. Reliability and observability ownership: Experience carrying a pager, running incidents, and working with tools such as OpenTelemetry, Prometheus, or Datadog. Data and platform systems experience: Familiarity with Postgres, object storage, queues, and vector stores. Candidates whose experience is limited to cloud operations or ticket-queue DevOps without software engineering, or who have never operated multi-tenant systems, will not be a fit for this role. Top-Tier Candidates Will Have Experience with model serving and model gateways, including vLLM, LiteLLM, or Triton. Experience implementing SOC 2 controls in CI. Experience deploying and operating AI systems in regulated or highly controlled environments. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: Cairo, Egypt Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.

Location: Islamabad, Pakistan Workplace: hybrid inDrive runs many ML models across 48 countries, and the platform under them is growing fast. Teams ship to Databricks, SageMaker and self-managed GPU inference, and LLM workloads are moving into production. We are hiring a Backend Engineer to build and run the services and tooling that ML teams depend on. You will write production-grade Go and Python, own your services from design to on-call, and learn the MLOps stack (Terraform, Kubernetes, Databricks, SageMaker) on the job. You will work with data scientists, ML engineers, and software and data engineers. Key Responsibilities Design, build and run backend services and internal tooling for the ML platform, in Go and Python, and own them in production: delivery, monitoring, on-call. Drive technical research and design for new platform features. Weigh trade-offs and write them down. Build and extend the deployment tooling and SDKs ML teams use to ship models, including serving, autoscaling and data capture. Integrate ML services with the wider backend: sync (HTTP, gRPC) and async (Kafka, RabbitMQ) communication, built for reliability under high load. Support the full ML delivery cycle with data scientists and ML engineers: CI/CD for models and pipelines, monitoring, and model performance metrics. Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks. Write infrastructure as code with Terraform and Terragrunt, and ship it through reviewed pull requests. Take part in code and design reviews and help raise the engineering bar. Mentor engineers and hold AI-generated changes to the same review standard as human ones. Skills, Knowledge and Expertise 3+ years of commercial backend engineering, including high-load systems. Strong Go: you know and have used its advanced features in production. Solid Python for data processing (batch, streaming and async) and for service code. Strong SQL: schema design, indexes, query optimisation, and scaling approaches such as replication and partitioning. Experience with Redis or similar key-value stores. Experience with sync and async service communication (HTTP, gRPC, Kafka or RabbitMQ), with a focus on reliability. Docker, CI/CD pipelines, and working Kubernetes knowledge. Experience with AWS/GCP core services (compute, storage, networking, IAM). Understanding of the ML lifecycle: data preparation, model performance metrics, non-functional requirements, and concept drift in production. Familiarity with scikit-learn, PyTorch/TensorFlow. Experience designing and running observability: metrics, logging, dashboards, tracing (Prometheus, Grafana, ELK or similar). Git workflows and code review, comfortable Linux command line, and networking basics (TCP/IP, DNS, VPC, load balancers). Ability to explain a trade-off clearly to a data scientist, a product owner and an on-call engineer. Nice to have: Hands-on experience with MLOps tooling: Databricks (Unity Catalog, Asset Bundles), SageMaker, Kubeflow, MLflow or Airflow. GPU or LLM inference experience (vLLM, Triton, Langfuse). Experience using AI coding agents with full review of generated changes. Experience in emerging markets, or building where there is no playbook yet. Experience with Infrastructure-as-Code (IaC) tools Why join us Real scale and real constraints: models serving a global fleet, GPU budgets that matter, LLM workloads reaching production. A strong backend engineer can grow into the MLOps domain here. We will teach you the platform side; you bring the engineering craft. Help us challenge injustice by creating fair choices for millions of people across 48 countries. Develop your professional skills with access to mentoring, career consulting, and learning programs. Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program. Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects. Work alongside people who take initiative, speak openly, and challenge themselves to grow. Improve your language skills through co-financed courses and internal speaking clubs. Final benefits may vary depending on the location.