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Location: United States (Remote) Workplace: Remote ABOUT ONEPAY OnePay is the consumer fintech trusted by millions of Americans to make money better. Our financial system is broken. High fees, low rates, and too few ways to actually grow your money. We’re fixing it. And we’re moving fast. We’re an all-in-one financial services platform that brings together banking, high-yield savings, credit cards, point-of-sale lending, investing, and crypto in one place. We also partner with employers, HCM providers, gig platforms, and others to deliver embedded financial services to millions of employees and frontline workers. We’re backed by Walmart, the world’s largest retailer, and Ribbit Capital, one of fintech’s most respected investors, giving us rare scale, distribution, and the opportunity to build something truly category-defining. But what really sets OnePay apart is how we move. Our customers don’t have time to wait… and neither do we. This place moves fast, and we’re looking for people who are: - Ready to run - Hungry and driven by urgency - Exceptional at what they do, with low ego - Comfortable operating in motion ABOUT THE EXPERIENCE DESIGN TEAM Experience Design at OnePay shapes how millions of people interact with their money. The product touches saving, spending, borrowing, and growing wealth – often for people the traditional financial system has underserved. That weight raises the bar on what we ship and how we ship it. We’re a small, senior team with roots at Apple, Meta, Ford, Airbnb, and leading fintechs – low ego, high craft, and genuinely collaborative. AI is a baseline part of how we work, not a future we’re talking about. THE ROLE We’re looking for a Design Engineer to help define what modern design-to-code looks like at OnePay. This is a first-class engineering role with design fluency. You’ll generate production-ready components directly, use AI coding tools aggressively, and help push the team past traditional spec-based handoff. You’re not executing the current model – you’re shaping what comes next. WHAT WE’RE LOOKING FOR - You ship in code. Figma is part of how you communicate, but you’re most fluent in the codebase. You generate production-ready work, not just specs. - You’re AI-native at production velocity. Cursor, Claude Code, v0, similar tools – they’re already how you move. You ship more in a day than most teams do in a week. - You’re rethinking handoff. The traditional model is breaking down, and you’re excited to define what replaces it. - You translate fluently. You speak both languages. Designers trust you, engineers trust you, and you make the gap between them disappear. - You sweat the implementation. A two-pixel drift in production matters to you. So does a token that doesn’t quite map. You catch what others miss. - You operate in motion. Process is fluid here, and you help shape it as you ship. TOOLS WE USE We use Node and TypeScript on the server, leveraging the NestJS framework within a microservice-oriented architecture running on Kubernetes and AWS. On the client side, we build and ship product features for iOS, Android, and web platforms using React Native. We also embrace AI-assisted development, so engineers have their choice of Claude Code or Cursor to fit their workflow. While you don't need experience with our exact stack, familiarity with modern software engineering practices will help you ramp up quickly. YOU BRING - Fluency in both Figma and code (React Native or React). - Active use of AI coding tools (Cursor, Claude Code, v0, or similar) at production velocity. - Fluency in design tokens, component architecture, and how design systems map to code. - Experience shipping on cross-functional teams where design and engineering overlap. - Strong communication across both disciplines. - A track record of operating in fluid environments and helping define how teams work. WHAT WE OFFER - Competitive base salary, stock options, and health benefits from Day 1 - 401(k) plan with company match - Remote-friendly (US), flexible time off (FTO), and opportunities for growth - A high-growth, mission-driven, inclusive culture where your work has real impact STANDARD INTERVIEW PROCESS Our process varies by role. Most candidates go through: - AI-assisted initial screen - Interview with Talent Partner - Technical or Hiring Manager Interview - Team Interview - Executive Interview - Offer! EQUAL EMPLOYMENT OPPORTUNITY To build technology and products that are used and loved by people and solve real-world problems, we need to build a team with many different perspectives and experiences. We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us at talent@onepay.com.

Location: Remote, DC MinIO is the data and memory foundation for enterprise AI. Built for the speed, scale, and economics that AI and analytics demand, AIStor and MemKV unify every layer of the data stack, from agentic and inference context memory to tables and objects across core, edge, and cloud. Trusted by 77% of the Fortune 100, MinIO is redefining how AI factories, intelligent applications, and autonomous agents secure, persist, and unlock the full value of their data. The Federal Field Architect at MinIO will bridge our technical platform and the mission requirements of our federal customers. You will bring deep technical expertise to bear across DoW, IC, and civilian agency engagements, spanning data infrastructure for both traditional workloads and AI training and inference at scale, working closely with our Federal Partner Sales team along with Engineering, Support, our channel and systems integrator partners, and our technology ecosystem partners, to ensure customers succeed from Proof of Value through production and beyond, including in air-gapped, classified, and DDIL (Denied, Degraded, Intermittent, Limited) environments. What You Will Do: Technical Architecture & Design: Architect AIStor deployments for federal customers, spanning on-prem, air-gapped, sovereign cloud, and tactical edge environments, including erasure coding, tiering, and replication topology design. Federal Compliance Expertise: Serve as the technical authority on FIPS 140-3, FedRAMP, NIST 800-53, and Zero Trust alignment, translating compliance requirements into deployable architecture for agency customers and partners. Proof of Value & Technical Validation: Lead PoVs, technical demonstrations, and reference architecture design for DoW, IC, and civilian agency opportunities, in direct engagement with customers and through our channel partner and FSI ecosystem. Partner Enablement: Provide technical training and architecture guidance to our federal reseller, systems integrator (FSI), and technology ecosystem partners, ensuring they can independently represent and deploy MinIO solutions with confidence. Ecosystem & Technology Partnerships: Serve as the technical point of contact for joint architecture work with ecosystem partners (e.g., NVIDIA, Databricks, Supermicro), supporting joint solutions, reference architectures, and co-sell motions. Kubernetes & Cloud-Native Deployment: Guide customers and partners on deploying AIStor across Kubernetes distributions common in federal environments, including OpenShift and Rancher. AI/ML Data Infrastructure: Architect data infrastructure for AI training, fine-tuning, and large-scale data lake workloads, ensuring GPU clusters stay fully fed and utilized rather than data-starved. Inference & Agentic AI Enablement: Advise on architecture that reduces recompute overhead and maximizes GPU utilization during inference at scale, including context memory strategies for agentic and long-running AI workloads. Technical Content Development: Develop reference architectures, technical white papers, and solution briefs that support the Federal Partner Sales team and our partner network in active pursuits. Your Skills and Experience: Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience. 4+ years in a solutions architect, sales engineering, or field engineering role, preferably within cloud, storage, or federal systems integration. Active security clearance strongly preferred; ability to obtain a clearance required. Deep technical knowledge of object storage (S3-compatible platforms), Kubernetes, and cloud-native/on-prem hybrid architectures. Familiarity with GPU-accelerated infrastructure and the data/memory demands of AI training and inference workloads at scale. Familiarity with federal compliance frameworks (FIPS 140-3, NIST 800-53, FedRAMP) and DoW/IC deployment environments (air-gapped, classified, DDIL). Strong technical acumen with the ability to communicate complex architecture decisions clearly to both technical and non-technical stakeholders. Experience working through or alongside channel partners, FSIs, and technology ecosystem partners (e.g., NVIDIA, Databricks) is a plus. What We Offer: Health Care Plan (Medical, Dental & Vision) 401K with 3% Contribution Pre-IPO Stock Options At least 12 Public Holidays Flexible Time Off Equal Opportunity Policy (EEO) MinIO is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

Location: Remote Canada At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The InfoSec team protects Affirm’s systems and data from evolving threats. We manage security risk, monitor vulnerabilities, and enforce protective controls across the company. The team leads incident response, compliance, identity and access management, and employee training. Our goal is to ensure that security is built into every system and decision at Affirm. We maintain a secure, trustworthy environment so the business can operate and grow with confidence. In this role, you'll build and run Affirm's end-to-end security review process for enterprise AI/LLM systems evaluating architecture, prioritizing AI-specific risks, and designing the controls and guardrails that let Affirm adopt AI safely, partnering across Security, Legal, Privacy, Compliance, IT, and Engineering to make it scalable and repeatable. What you’ll do You will lead and continuously improve Affirm's enterprise AI security review process  evaluating the architecture, data flows, permissions, and design of internal AI tools, agentic/MCP-based systems, and AI features — and embed security requirements into the design phase. You will threat model AI/LLM-based systems and their data flows for risks such as prompt injection, insecure output handling, excessive agency, tool-permission abuse, data poisoning, and sensitive-data exposure, and drive remediation. You will review source code, system prompts, agent configurations, and tool/permission manifests (e.g., MCP definitions), and help tool owners build security-focused test cases and red-team/eval scenarios to verify requirements before launch. You will design and build security guardrails and tooling for AI systems permission boundaries, authn/authz for agentic tools and MCP servers, data-handling controls, logging/monitoring, and policy-as-code (Python, IaC) — to enforce and automate AI security. You will evaluate the AI capabilities of third-party SaaS vendors (e.g., Notion, Slack, Google Workspace) as part of vendor and SaaS security reviews and drive risk-based adoption decisions. You will identify emerging classes of AI/agentic security vulnerabilities, develop mitigations before they become incidents, and contribute to AI-specific incident response playbooks as a senior escalation point. You will lead cross-functional AI security initiatives to closure, advise technical and executive stakeholders as an internal point of expertise, and stay current on the AI security landscape (OWASP LLM Top 10, MITRE ATLAS) to translate new research into practical controls. What we look for You are a seasoned security engineer with hands-on experience designing, evaluating, and maintaining security architecture for AI/LLM-based systems, plus deep expertise in enterprise security systems, processes, and controls. You have practical experience threat modeling and reviewing AI/LLM applications (e.g., against the OWASP Top 10 for LLM Applications) and securing agentic systems and tool-calling frameworks — MCP servers/clients, tool-permission models, and agent-to-tool trust boundaries. You have built AI governance artifacts (acceptable use policy, data-handling standards, vendor/model risk assessments) and evaluated AI capabilities within SaaS platforms (e.g., Notion AI, Slack AI, Google Workspace AI, GitHub Copilot) as part of vendor reviews. You have experience with enterprise tools for AI visibility and control (e.g., CASB, IDP/Okta) and familiarity with the corporate systems where AI is adopted (OpenAI, Anthropic, GitHub, Google Workspace, Slack, Notion, Jira). You can build security tooling, guardrails, and detections with Python or similar, and deploy cloud services and policy-as-code using Infrastructure as Code (Terraform or similar); familiarity with Kubernetes and AWS. You understand how LLMs and agentic systems are built (RAG, embeddings, fine-tuning, tool use) and authn/authz models (OAuth2, SAML, service-account/non-human identities) for agentic and machine-to-machine access, with strong application-architecture and threat-modeling fundamentals. You can lead cross-functional initiatives across Security, Engineering, Legal, Privacy, and Compliance and drive them to closure, and communicate effectively with technical and executive audiences. Experience in regulated environments (SOC 2, PCI DSS) and applying IAM to non-human/agent identities is a plus. This posting is for an existing vacancy This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan. Base Pay Grade - P Equity Grade - 7 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company). CAN base pay range per year: $173,000 - $233,000 #Li-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Location: Remote US At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. The InfoSec team protects Affirm’s systems and data from evolving threats. We manage security risk, monitor vulnerabilities, and enforce protective controls across the company. The team leads incident response, compliance, identity and access management, and employee training. Our goal is to ensure that security is built into every system and decision at Affirm. We maintain a secure, trustworthy environment so the business can operate and grow with confidence. In this role, you'll build and run Affirm's end-to-end security review process for enterprise AI/LLM systems evaluating architecture, prioritizing AI-specific risks, and designing the controls and guardrails that let Affirm adopt AI safely, partnering across Security, Legal, Privacy, Compliance, IT, and Engineering to make it scalable and repeatable. What you’ll do You will lead and continuously improve Affirm's enterprise AI security review process  evaluating the architecture, data flows, permissions, and design of internal AI tools, agentic/MCP-based systems, and AI features — and embed security requirements into the design phase. You will threat model AI/LLM-based systems and their data flows for risks such as prompt injection, insecure output handling, excessive agency, tool-permission abuse, data poisoning, and sensitive-data exposure, and drive remediation. You will review source code, system prompts, agent configurations, and tool/permission manifests (e.g., MCP definitions), and help tool owners build security-focused test cases and red-team/eval scenarios to verify requirements before launch. You will design and build security guardrails and tooling for AI systems permission boundaries, authn/authz for agentic tools and MCP servers, data-handling controls, logging/monitoring, and policy-as-code (Python, IaC) — to enforce and automate AI security. You will evaluate the AI capabilities of third-party SaaS vendors (e.g., Notion, Slack, Google Workspace) as part of vendor and SaaS security reviews and drive risk-based adoption decisions. You will identify emerging classes of AI/agentic security vulnerabilities, develop mitigations before they become incidents, and contribute to AI-specific incident response playbooks as a senior escalation point. You will lead cross-functional AI security initiatives to closure, advise technical and executive stakeholders as an internal point of expertise, and stay current on the AI security landscape (OWASP LLM Top 10, MITRE ATLAS) to translate new research into practical controls. What we look for You are a seasoned security engineer with hands-on experience designing, evaluating, and maintaining security architecture for AI/LLM-based systems, plus deep expertise in enterprise security systems, processes, and controls. You have practical experience threat modeling and reviewing AI/LLM applications (e.g., against the OWASP Top 10 for LLM Applications) and securing agentic systems and tool-calling frameworks — MCP servers/clients, tool-permission models, and agent-to-tool trust boundaries. You have built AI governance artifacts (acceptable use policy, data-handling standards, vendor/model risk assessments) and evaluated AI capabilities within SaaS platforms (e.g., Notion AI, Slack AI, Google Workspace AI, GitHub Copilot) as part of vendor reviews. You have experience with enterprise tools for AI visibility and control (e.g., CASB, IDP/Okta) and familiarity with the corporate systems where AI is adopted (OpenAI, Anthropic, GitHub, Google Workspace, Slack, Notion, Jira). You can build security tooling, guardrails, and detections with Python or similar, and deploy cloud services and policy-as-code using Infrastructure as Code (Terraform or similar); familiarity with Kubernetes and AWS. You understand how LLMs and agentic systems are built (RAG, embeddings, fine-tuning, tool use) and authn/authz models (OAuth2, SAML, service-account/non-human identities) for agentic and machine-to-machine access, with strong application-architecture and threat-modeling fundamentals. You can lead cross-functional initiatives across Security, Engineering, Legal, Privacy, and Compliance and drive them to closure, and communicate effectively with technical and executive audiences. Experience in regulated environments (SOC 2, PCI DSS) and applying IAM to non-human/agent identities is a plus. Base Pay Grade - P Equity Grade - 13 Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills. Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.) USA base pay range (CA, WA, NY, NJ, CT) per year: $220,000 - $280,000 USA base pay range (all other U.S. states) per year: $195,000 - $255,000 #LI-Remote Remote-first with flexibility built in Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience. Benefits designed for you Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights: Health coverage at no cost: We cover 100% of premiums for employees and their dependents. Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you. Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to. Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount. We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help. For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Задачи: — Развивать и поддерживать production Kubernetes-кластеры (40+ сервисов, 20+ разработчиков). — Проектировать инфраструктурные решения под рост нагрузки и отказоустойчивость. — Принимать решения по развитию инфраструктуры и платформенных сервисов. — Развивать GitOps-подход через FluxCD: управление релизами, окружениями, политиками. — Писать и поддерживать Terraform-модули для управления облачной инфраструктурой. — Строить и улучшать CI/CD пайплайны в GitLab CI вместе с командами разработки. — Обеспечивать observability: метрики (Prometheus/Grafana), логи (ELK), алерты. — Встраивать практики DevSecOps/FinOps. — Делать ревью инфраструктурного кода коллег. — Отвечать за здоровье и аптайм инфраструктуры. Требования: — Уверенное знание Linux. — Понимание Docker и контейнеризации. — Опыт настройки CI/CD. — Опыт с Kubernetes. — Опыт с GitOps-инструментами (FluxCD, ArgoCD). — Опыт администрирования БД. — Будет плюсом: Разрабатывали на Go или Java. — Будет плюсом: Умеете работать с Terraform для управления инфраструктурой. — Будет плюсом: Опыт внедрения Vault или аналогичных систем управления секретами. — Будет плюсом: Опыт с кластерным Clickhouse. — Будет плюсом: Опыт с поддержкой кластера Kafka. — Будет плюсом: Опыт работы SRE. — Будет плюсом: Выстраивал SLO/SLA для сервисов. — Будет плюсом: Опыт с высоконагруженными проектами. — Будет плюсом: Активное использование ИИ технологий. Условия: — Удаленный или гибридный формат работы на выбор. — Уютный дизайнерский офис в пешей доступности от м. Арбатская или м. Кропоткинская. — Вкуснейший кофе, чай, фрукты, овощи, снэки и сладости. — Компенсация расходов на спорт, английский язык и другие профессиональные курсы. — Подарки на День Рождения, Свадьбу, рождение ребенка. — Реферальная система — бонус за приведенного сотрудника. — Возможность посещения конференций, вебинаров и других мероприятий. — Работа без бюрократии и ненужных ритуалов.

Компания Centicore ищет опытного инженера DevOps для работы над централизованной MLOps-инфраструктурой. Задачи: — Конфигурировать и разворачивать инфраструктурные компоненты — Адаптировать и разрабатывать с нуля автоматизированные пайплайны под актуальные бизнес-задачи (AutoML, LLM, computer vision и пр.) — Создавать и поддерживать пользовательские инструменты для работы в едином ML-контуре применения и обучения — Масштабировать разрабатываемые системы и инструменты для управления жизненным циклом моделей машинного обучения Требования: — Опыт DevOps от 5 лет с инструментами docker, helm, jenkins/gitlab CI, python — Желателен опыт ML/MLOps от 1 года с airflow, jupyterhub, mlflow, seldon, cuda — Опыт администрирования Kubernetes от 2 лет — Опыт работы с Hadoop, Spark, Kafka, ELK Условия: — Удаленный формат работы в IT аккредитованной компании — Оформление по ТК — Оплачиваемый отпуск 28 календарных дней в год и оплачиваемые больничные — Предоставление техники (MAC, Windows) — ДМС со стоматологией — Компенсация хобби/спортзала/английского языка — Компенсация профессионального обучения — Возможность участия во внутренних программах компании и активностях — Онлайн и оффлайн корпоративные мероприятия — Программа лояльности Сентибонусы

Задачи: — Функциональное и системное сопровождение банковского программного обеспечения — Сопровождение и развитие инфраструктуры банковского программного обеспечения — Обеспечение доступности автоматизированных банковских процессов — Осуществление технической поддержки пользователей и клиентов — Накопление и передача технической экспертизы по архитектуре ИТ системы, а также по бизнес-процессам — Развитие программно-инфраструктурного ландшафта банка — Реализация пилотных проектов бизнеса Требования к кандидату: — Управление серверами на базе Linux на уровне администратора — Знание микросервисной архитектуры и технологий контейнеризации: Docker, containerd — Продвинутые навыки работы с Kubernetes, Helm, Kafka — Понимание принципов построения процессов CI/CD — Понимание принципов IaC. Продвинутые навыки работы с Ansible, Terraform, Terragrunt — Понимание принципов построения Observability. Продвинутые навыки работы с ELK/EFK, OpenSearch, Prometheus, VictoriaMetrics — Опыт работы с облачными провайдерами, например, AWS, Yandex Cloud — Знание СУБД на уровне администратора: Redis, MongoDB — Навыки программирования, например, на Python, GO, Java, JavaScript — Kubernetes (не managed), Postgres/Patroni, Redis, Ansible, VictoriaMetrics/Prometheus, ELK/OpenSearch — Образование высшее, профильное техническое — Опыт работы от 3х лет Условия работы: — Оформление по ТК РФ или ИП в аккредитованную ИТ компанию — ДМС со стоматологией — Скидки на изучение иностранных языков от Skyeng — Скидки на фитнес от Xfit — Скидки на кино от КАРО — Техника для работы

Задачи: — Разработка сервисов ИИ платформы для создания функциональных агентов и ИИ ассистентов. — Подготовка бэк части для функциональных агентов, включая среду разработки агентов: тестирование фреймворков, opensource агенты. — Разработка сервиса управления реестром и скиллами агентов. — Создание отдельного единого сервиса для всех баз знаний, интеграция крупных корпоративных источников. Требования: — Понимание архитектуры, возможностей и ограничений современных языковых моделей. — Опыт работы с embeddings, vector search, RAG, structured output и tool calling. — Понимание принципов проектирования AI-агентов: управление состоянием и контекстом, выбор инструментов, контроль уровня автономности и human-in-the-loop. — Опыт построения evals для LLM-систем, оценки качества ответов, контроля галлюцинаций и мониторинга поведения системы. — Понимание рисков prompt injection, некорректного tool calling, утечки данных и чрезмерных прав доступа агента. — Опыт работы с API языковых моделей, Hugging Face и одним из orchestration-фреймворков. — Умение оценивать стоимость, latency и масштабируемость LLM-решений. — Опыт работы в e-commerce, retail или других продуктовых highload-системах. — Опыт работы с Airflow, MLflow, Kafka, Redis, Kubernetes, Prometheus и Grafana. — Опыт эксплуатации GPU-инфраструктуры и оптимизации inference. — Опыт fine-tuning или адаптации LLM, включая LoRA / PEFT. — Опыт проектирования agentic workflows или multi-agent-систем. — Понимание принципов информационной безопасности, privacy и работы с персональными данными. Условия: — full-time

Location: Bremen, Germany Supervisor: Prof. Dr. Alexander Tormasov About the Position Constructor Knowledge Labs (CKL), in collaboration with Constructor Technology, invites applications for a PhD position in machine learning for software engineering and formal methods, on the Constructor Fabric project. Constructor Fabric turns a company's informal knowledge into production software through a pipeline of composable capability units called gears : requirements → architecture → product fit → framework (G1) → application → runtime. We are building a World Model over that pipeline — a model that does not just generate code, but predicts the consequences of an architectural decision: total cost of ownership, unintended side effects, latency and failure behaviour, and whether a proposed composition is even admissible. The central object is not a digital twin of the application but its formal architectural skeleton : gear contracts (GearSpec), a typed attributed hypergraph of the application (AppGraph), a composition algebra that defines which assemblies are legal, and several semantic projections (types, protocols, resources, security) over which properties are proved, refuted by counterexample, or reported as an explainable gap . All of it is written in a domain-specific language whose syntax trees and graphs we keep in a projectional editor (JetBrains MPS) — so the DSL is not a convenience layer, it is the thing that defines the model's state space and the boundary of what the model is allowed to propose. What you will work on Depending on your background, one or two of: Formal skeleton and composition — GearSpec as a contract $(Requires, Provides, State, Effects, Assumptions, Guarantees, Parameters)$; AppGraph as a typed attributed hypergraph; an algebra of assembly (sequential, parallel, feedback, refinement); semantic projections and system-level invariants over trajectories. Architecture synthesis as an inverse problem — given a specification, load and constraints, find the composition of gears that realises it. Constraint solving and MCTS as the baseline; a learned transition/value model for ranking and pruning; LLM proposals treated strictly as candidate hypotheses that a DSL parser, type checker and property checks must then admit or reject. DSL design and language engineering — the gear DSL and its glue layer decide which AppGraphs are expressible at all, and therefore where the search space ends. This thread covers the abstract syntax and static semantics of that DSL; the requirement that an architectural decision be unbypassable by construction (you must not be able to wire authentication around the Auth Resolver); what happens to the language when gear contracts change or a 201st gear is added; projectional representation of graphs with cycles; and the open hypothesis that a specialised G1-DSL is generated together with every G1. Local transition models and pipeline surrogates — fast approximate predictors for single pipeline steps (spec change → code quality, architecture → product fit, app → runtime outcome), with calibrated uncertainty, validated against real telemetry. Data — reconstructing (specification → architecture) pairs from open repositories at scale, plus synthetic project generation from a fixed gear set and DSL grammar to cover rare transitions, gaps and counterexamples. Profile MSc (or equivalent) in computer science, mathematics, or a mathematical natural science. Coursework in compilers, programming-language theory, language design or model-driven engineering is a strong positive signal, half of this project is deciding what a formal architecture description is allowed to say. Evidence that you finish things: a maintained open-source repository, a peer-reviewed publication, or a strong competition result. Fluent technical English. Most importantly: the habit of stating an assumption explicitly and designing an experiment that could falsify it. Required mathematical background Core skills: Probability and statistics. Estimation, Bayesian inference, uncertainty quantification and calibration (proper scoring rules, reliability diagrams, ECE), experiment design and significance testing. A prediction we cannot calibrate is not usable here. Linear algebra and multivariate calculus at the level needed to derive, not just call, a training objective: matrix calculus, gradients, stochastic optimisation, conditioning. Discrete mathematics and graph theory. Typed and attributed graphs and hypergraphs, subgraph matching and isomorphism, graph rewriting, reachability, basic complexity classes. Mathematical logic and formal methods. First-order logic, type systems, SAT/SMT, temporal logic (LTL/CTL) and model checking, pre/post-conditions, invariants, refinement. Sequential decision making. MDP/POMDP, dynamic programming, model-based RL, latent state-space (world) models, Monte-Carlo Tree Search. Strong command of at least one, working knowledge of a second: Formal languages, semantics and language engineering — grammars (context-free, attribute and graph grammars), derivation and reachability, parsing; abstract versus concrete syntax; operational and denotational semantics; metamodelling, model-driven engineering, model-to-model transformation, and projectional (structural) editing of the kind JetBrains MPS implements. We are asking for the education, not the tool: you should know why a projectional editor exists, what a metamodel buys you over a text grammar, and how a language evolves without breaking its existing models. Hands-on MPS experience is explicitly not required — we will teach it. Category theory for compositional systems — monoidal and traced monoidal categories, functors as semantic projections, string diagrams, operads. This is the language of our assembly algebra. Causal inference — structural causal models, do-calculus, counterfactuals, identifiability. Required for the "what happens if we replace this technology / move on-premises" class of questions, which similarity search alone cannot answer. Queueing theory and applied stochastic processes — M/M/1 and networks of queues, heavy tails, retries, timeouts, partial failure and reliability models. This is the resource and stochastic projection. Combinatorial optimisation, constraint programming and program synthesis theory — CEGIS, version-space algebras, symmetry breaking, search heuristics. Representation learning theory — VAEs and latent dynamics, GNN expressiveness (Weisfeiler-Leman hierarchy), permutation equivariance, embedding migration under a changing vocabulary. Required hands-on programming skills This is an engineering-heavy PhD. We expect code that another person can clone, run and reproduce — not notebooks that worked once. Must have: Python (professional level). Type hints, packaging, `pytest`, profiling, `asyncio`, memory-aware data structures. You write unbuffered, logged, restartable long-running jobs by default. Training loops written from scratch, custom datasets and collation, mixed precision, multi-GPU; experiment tracking (W&B or MLflow), configuration management (Hydra), strict seed and artefact reproducibility. Graph machine learning. PyTorch Geometric or DGL — message passing, heterogeneous and typed graphs, graph transformers, handling graphs whose node vocabulary changes between versions. Solvers and verification tooling driven from Python. Z3 or cvc5 hands-on; demonstrated exposure to at least one model checker (TLA+/TLC, SPIN, NuSMV, Alloy) or proof assistant (Lean, Coq, Isabelle). Code as data. AST manipulation, `tree-sitter`, static analysis, dependency and interface graph extraction, large-scale repository mining. Parallel data pipelines. `multiprocessing`, Ray or Dask; checkpointing, heartbeats, cost estimation before launching a run that touches millions of files. LLM engineering. API orchestration, structured and grammar-constrained decoding, evaluation harnesses, token/cost accounting — with the discipline to treat model output as a hypothesis subject to formal checks. Linux, git, code review, shell. Desirable: Language tooling you have actually used: ANTLR, Xtext, Lark, or a parser, type checker or interpreter you wrote yourself. Our internal representation of gear syntax trees and graphs lives in JetBrains MPS — again, we do not ask for MPS experience, only that you are comfortable reading and extending a metamodel; Java/Kotlin literacy helps once you get there. JAX, or compiler / SAT-SMT internals. Infrastructure literacy — Docker, Kubernetes, Terraform, OpenTelemetry/Prometheus — since the resource projection is calibrated against real deployment telemetry. One systems language (Rust, Go or C++) for performance-critical search. Prior experience with production software architecture, or with a brownfield system you had to change without breaking. Funding The appointment provides full financial coverage through a dedicated fellowship, comprising: Monthly stipend of €1,650 Monthly research-cost allowance of €100 (Forschungskostenpauschale) Health-insurance subsidy of €100 per month Location: Bremen, Germany Duration: 3 years, full time Start date: November 2026 Application package must include CV, including publications, code, or research projects. Cover letter (1–2 pages) explaining your motivation, research interests, and fit with the project. A link to code you have written. A one-page research statement picking one open research question from the project and sketching how you would approach it. Master’s and Bachelor’s degree certificate and transcripts. Contact information for 2–3 academic referees. Applications are reviewed on a rolling basis. Shortlisted candidates will be invited to interviews.

Location: GE; PL Workplace: remote Overview: SOFTSWISS is looking for an Incident Response Analyst to join our on-call incident response team. In this role, you will respond to and investigate security incidents across the company, coordinate incident response with relevant teams, and help ensure timely and effective resolution of incidents . Key responsibilities: Participation in security incident response Performing basic primary incident response measures/triage Execution (and monitoring of execution) of tasks assigned based on planning results Development and updating of playbooks for alert verification Monitoring alerts in compliance with SLA Submitting proposals for optimizing tools and processes used The position operates on a 2-on-2-off shift pattern, encompassing a 12-hour day shift, a 12-hour night shift the next day, and 2 free days after that Required Experience: Basic indicator of compromise (IoC) analysis skills using publicly available tools (VirusTotal, AnyRun, etc.) Experience working with Splunk/Clickhouse/SQL at the level of writing simple search queries and interpreting results Experience working with SOAR/IRP General understanding of current cyber threats and main attack methods Basic programming skills in Python, PowerShell, or Bash for automating routine tasks Knowledge of operating systems (Linux/Windows) at a junior system administrator level Understanding of the MITRE ATT&CK framework and Cyber Kill Chain Ability to analyze and process large volumes of data, including logs and triage Strong communication and teamwork skills: able to clearly articulate thoughts, ask relevant questions, and effectively collaborate with colleagues across different teams, especially during incident response Analytical and flexible mindset: able to approach issues from different perspectives, build logical chains, make informed decisions, and independently suggest solutions Proactivity and ownership: takes responsibility for decisions and results, double-checks own work, learns from mistakes and feedback, and actively develops professional skills Nice to have: Knowledge of information security best practices (NIST, ISO) and ability to cite them when necessary Basic knowledge of Docker and Kubernetes, understanding their monitoring features Experience writing correlation rules in SIEM Experience with NTA (Network Traffic Analysis) tools Experience working with online reputation services (VT, AnyRun, IPAbuseDB, etc.) Experience developing instructions for alert verification and/or writing information security incident response scenarios Experience with Kafka, ELK, Graylog, etc Strong Linux system administration experience Expertise in network, host, and cloud-based analysis and investigation A strong understanding of attack pipelines (MITRE ATT&CK Framework, Cyber Kill-Chain) Familiarity with CI/CD, software development lifecycle, and Infrastructure-as-Code (Terraform/Ansible/etc) Proficiency in automation (Bash/PowerShell, Python) Experience with log collection, delivery, and normalization Strong knowledge of open-source solutions for endpoint & infrastructure security, such as Audit.d, Sysmon, AppArmor, SELinux, etc Fundamental static and dynamic malware analysis skills Offensive experience (penetration testing, red teaming) Main Advantages Private health insurance Sports benefits Comprehensive Mental Health Program Free English lessons (online) Local language courses Paid time off Maternity leave support Referral program rewards Upskilling, internal workshops, and participation in professional conferences and corporate events

Location: St. Petersburg, Russia; Moscow, Russia; Belgrade, Serbia Workplace: remote At NOVACARD , we’re redefining how people use credit. We are the first interest-free and no-annual-fee credit card in Mexico , designed to simplify personal finances and give users complete control - all from a mobile app. With NOVACARD, users can access up to $200,000 MXN in credit , only pay when they use it, and manage everything digitally in under 5 minutes. Our mission is to empower people to make smarter financial decisions by offering flexibility, transparency, and the freedom they need to reach their goals. Simple finances, big goals. About the Role: We’re looking for a DevOps Engineer to design, deploy, and operate AWS infrastructure for a large-scale migration of a digital financial product. You’ll build and maintain a production-ready platform covering AWS networking, Kubernetes/EKS, CI/CD, observability, backup/restore, and secure access management. You’ll collaborate closely with development, system analysis, QA, and engineering teams to ensure fast delivery, stable services, and a controlled migration. Key Responsibilities: AWS Infrastructure Design & Operations Design, deploy, and maintain AWS infrastructure: VPC, Subnets, Route Tables, Security Groups, IAM, EC2, EBS, S3, ELB/ALB/NLB, Route53. Configure AWS networking: public/private subnets, NAT Gateway, Internet Gateway, VPC Peering / Transit Gateway, VPN, routing. Ensure HA, backup/restore, disaster recovery, and production infrastructure principles. Create and maintain AWS infrastructure as code using Terraform. Kubernetes & Containerization Build and operate Kubernetes on AWS (EKS). Work with core Kubernetes objects: Deployment, StatefulSet, DaemonSet, Service, Ingress, ConfigMap, Secret, Job/CronJob, PVC/PV, Namespace, ServiceAccount. Use Helm for application management. Configure Ingress Controller, Load Balancer, and TLS/certificates. Understand Kubernetes storage and ensure stateful applications run reliably. Work with Docker: image builds, registry, container troubleshooting. CI/CD & Automation Build CI/CD processes, preferably with GitLab CI. Automate deployment of applications and dependent services. Integrate infrastructure changes into pipelines and maintain reproducible environments. Observability, Reliability & Operations Set up monitoring with Prometheus + Grafana: metrics and alerts. Organize centralized log collection and analysis: Loki/ELK/OpenSearch. Diagnose network and system issues in Linux. Ensure production stability, respond to incidents, and eliminate root causes. Security & Access Management Manage secrets: AWS Secrets Manager / Vault/OpenBao / External Secrets. Configure RBAC/IAM and follow the principle of least privilege. Ensure secure service-to-service communication and infrastructure access. Data & Services Support PostgreSQL, Redis, RabbitMQ/Kafka at the infrastructure and application integration level. Ensure backup/restore and fault tolerance for stateful services. Help teams deploy and maintain dependent services in Kubernetes. Key Requirements: AWS & Networking Strong AWS experience: VPC, Subnets, Route Tables, Security Groups, IAM, EC2, EBS, S3, ELB/ALB/NLB, Route53. Good understanding of AWS networking: public/private subnets, NAT Gateway, Internet Gateway, VPC Peering / Transit Gateway, VPN, routing. Kubernetes & Containers Hands-on experience building and operating Kubernetes on AWS (EKS). Understanding of core Kubernetes objects: Deployment, StatefulSet, DaemonSet, Service, Ingress, ConfigMap, Secret, Job/CronJob, PVC/PV, Namespace, ServiceAccount. Experience with Helm. Experience configuring Ingress Controller, Load Balancer, and TLS/certificates. Experience with Docker: image builds, registry, container troubleshooting. Understanding of Kubernetes storage and stateful application operation. IaC & CI/CD Terraform — creating and maintaining AWS infrastructure as code. Experience building CI/CD, preferably GitLab CI. Data, Queues & Storage Experience with PostgreSQL, Redis, RabbitMQ/Kafka at the infrastructure and application integration level. Understanding of HA, backup/restore, disaster recovery, and production infrastructure principles. Monitoring, Logging & Secrets Monitoring: Prometheus + Grafana, configuring metrics and alerts. Centralized log collection and analysis: Loki/ELK/OpenSearch. Secrets management: AWS Secrets Manager / Vault/OpenBao / External Secrets. Linux & Security Linux administration and confident diagnosis of network and system issues. Experience configuring RBAC/IAM and following the principle of least privilege. Especially Important Practical Experience: The engineer must be able to design an AWS network from scratch → set up EKS → deploy an application and dependent services → configure ingress/DNS/TLS → CI/CD → monitoring/logging → backup → hand over a production-ready infrastructure for operation. Nice to Have: Experience migrating lending systems or fintech products. Experience building CI/CD with GitLab CI. Hands-on experience with Vault/OpenBao, External Secrets. Experience with Kafka and stateful services in Kubernetes. What We Offer: Participation in a large-scale migration of a digital financial product. Work with a modern stack: AWS, Kubernetes/EKS, Terraform, CI/CD, Prometheus/Grafana. Close collaboration with development, system analysts, QA, and engineers. Opportunity to build a production-ready platform from scratch and hand it over to operations. Terms and work format — discussed individually

Location: Lisbon, Portugal Joom is a global cross-border marketplace where millions can find anything they want at fair prices. Joom helps consumers to make shopping easy and entertaining and provides access to interesting and unique goods from around the world. Joom is one of the key businesses of Joom Group, an international group of tech-centric group of e-commerce companies founded in 2016 in Latvia. Joom also includes other businesses: JoomPro, the first and only end-to-end cross-border B2B marketplace; JoomPulse, an AI analytics tool for Mercado Livre sellers; and Onfy, a pharmaceutical marketplace in Germany. Joom Group has offices in Latvia, China, Germany, and Brazil, with its headquarters in Lisbon, Portugal. We work as one international team, sharing knowledge and collaborating across countries, businesses and products. We are currently looking for Senior/Middle+ Backend Developers to join our teams: JoomPro is the first and only end-to-end cross-border B2B marketplace. It serves small, medium, and large businesses, handling orders of any size from start to finish. Today, JoomPro operates in Brazil and Mexico, with plans to expand into other markets. Tech stack: Go, MongoDB, Redis, Kafka, Amazon AWS, Docker, Kubernetes, Elasticsearch The Development Infrastructure team is responsible for the uninterrupted operation of internal services, the fault tolerance of components, the evolution of the codebase architecture, as well as creating and maintaining tools for developers. Tech stack: Go, Bazel, Jenkins, Kubernetes, Helm, KCL, Terraform, MongoDB, Postgres The Antifraud Infrastructure team is responsible for ensuring platform security, including infrastructure protection, bot management, user device authorization, personal data storage, and preventing data leaks. Tech stack: Go, Kotlin, MongoDB, Cassandra, Redis, Kafka, Spark (Scala, SQL), Amazon AWS, Docker, Kubernetes, ML The Client Backend team is responsible for all API requests coming from our mobile apps and Joom's web client. Tech stack: Go, MongoDB, Redis, Casandra, Kafka, sometimes Spark (Scala, SQL), Docker, Kubernetes, Grafana, Prometheus Responsibilities Come up with architecture Program in Go (Go is not a must for us; it is more important for a successful candidate to have solid algorithm skills, fundamental technical knowledge, and great coding skills in general) Provide fault tolerance for coded services in an AWS environment Be prepared for a constant increase of processed and stored data loads and volumes Participate in new feature and product development discussions Requirements Confident knowledge of any of the programming languages: Go/Java/Kotlin/C++/Python/Scala Complex project development experience Excellent algorithmic training Experience in development for Linux / Unix Preferred Experience with highload Experience with MongoDB Experience with Kubernetes We offer Compensation package: base salary and performance-based bonuses Office-first: flexible hours with a possibility to work remotely 52 days per year Care & Wellbeing: health insurance (including dental care) for employees and their children, daily meal allowance, and 100% paid sick leave Relocation Support: full assistance for a smooth relocation for the employees and their family AI-first approach: licenses and access to a wide range of AI tools Team & Growth: collaboration with colleagues across Portugal, Brazil, Latvia and China, with opportunities for promotions, professional trainings, and English & Portuguese courses Community & Engagement: annual team building activities, knowledge-sharing workshops, and a strong sense of team work Before applying for the above position please review our Candidate Privacy Notice here . By responding to the vacancy, you acknowledge that you have read our Privacy notice.

Вакансия предполагает работу на позиции Senior Data Science специалиста с полной занятостью и удалённым форматом в России. Основные задачи включают разработку сервисов для ИИ платформы, предназначенной для создания функциональных агентов и ИИ ассистентов, а также подготовку серверной части для таких агентов, включая тестирование фреймворков и работу с opensource агентами. В обязанности также входит создание сервиса управления реестром и навыками агентов, а также разработка единого сервиса для баз знаний с интеграцией крупных корпоративных источников. Кандидат должен хорошо разбираться в архитектуре и ограничениях современных языковых моделей, иметь опыт работы с embeddings, vector search, RAG, structured output и tool calling. Важны знания принципов проектирования AI-агентов, включая управление состоянием и контекстом, выбор инструментов, контроль автономности и human-in-the-loop. Требуется опыт построения evals для LLM-систем, оценки качества ответов, контроля галлюцинаций и мониторинга поведения, а также понимание рисков, связанных с prompt injection, некорректным tool calling, утечкой данных и избыточными правами доступа. Необходим опыт работы с API языковых моделей, Hugging Face и одним из orchestration-фреймворков, умение оценивать стоимость, задержки и масштабируемость LLM-решений. Желателен опыт в e-commerce, retail или других высоконагруженных продуктовых системах, а также владение инструментами Airflow, MLflow, Kafka, Redis, Kubernetes, Prometheus и Grafana. Кандидат должен иметь опыт эксплуатации GPU-инфраструктуры и оптимизации inference, а также fine-tuning или адаптации LLM, включая LoRA/PEFT. Опыт проектирования agentic workflows или multi-agent систем и понимание принципов информационной безопасности, конфиденциальности и работы с персональными данными также обязательны.

Компания Clearway Integration – команда архитекторов и консультантов, созданная выходцами из Microsoft Consulting Services. Мы создаем программные продукты для управления и мониторинга больших ИТ-инфраструктур. Компания аккредитована в реестре Минцифры, имеет продукты в Реестре отечественного ПО и предоставляет системно-значимые сервисы. Мы разрабатываем линейку программных продуктов для автоматического управления и мониторинга серверов и АРМ в сетях из десятков тысяч хостов, управления Инфраструктурой Открытых Ключей TLS и ГОСТ, миграции лесов Active Directory и Exchange масштаба страны. Наши продукты успешно применяются в одном из крупнейших банков и ряде промышленных холдингов. Мы решаем реальные проблемы реальных людей, а не переклеиваем этикетки «импортозамещения». Задачи: • Сбор, анализ и документирование требований к разрабатываемому программному обеспечению, взаимодействие с командами. • Разработка и актуализация технической документации: функциональные и нефункциональные требования, спецификации, сценарии использования. • Моделирование бизнес-процессов и их преобразование в требования к ПО, создание и поддержка UML-диаграмм, схем и других визуальных моделей. • Участие в анализе конкурирующих решений, формирование и актуализация battlecard. • Активное участие в проектировании архитектуры системы. • Активное участие в проведении системного тестирования и валидации разрабатываемых решений на соответствие требованиям. • Участие в формировании технической документации, формирование и поддержка базы знаний компании. Требования: • Высшее техническое образование. • Уверенное знание отраслевой терминологии в сфере мониторинга ИТ-инфраструктуры и состояния корпоративных информационных систем, управления конфигурациями, PKI-инфраструктуры. • Опыт работы на позиции IT системного аналитика или аналогичной должности от 5 лет. • Понимание жизненного цикла разработки ПО, опыт работы с Agile/Scrum методологиями. • Практический опыт применения методологий системного анализа, таких как UML, BPMN, IDEF и других. • Понимание процессов тестирования ПО. • Навыки работы с инструментами для моделирования и документирования. • Понимание принципов работы REST API, SOAP и других протоколов межсервисного взаимодействия. • Знание SQL и понимание принципов работы с различными типами баз данных. • Отличные аналитические способности, внимание к деталям и умение видеть "общую картину". • Хорошие коммуникативные навыки, умение работать в команде, проактивность и ответственность. Будет плюсом: • Опыт работы в компаниях-разработчиках ПО или в IT-консалтинге. • Понимание принципов DevOps, CI/CD, контейнеризации (Docker, Kubernetes). • Опыт работы с системами мониторинга (Zabbix, Prometheus и др.) и управления инфраструктурой. • Сертификации в области системного анализа (CBAP). • Базовое понимание какого-либо из языков программирования. Что нам важно увидеть в кандидате: • вдумчивость и понимание смысла своих решений: главный вопрос - "зачем"; • желание делать свою работу лучше и развиваться: читайте и делитесь; • английский – необходимы умения и навыки свободного самостоятельного чтения технической литературы и обсуждения выводов с коллегами. Что мы предлагаем: • возможность участвовать в проектах, которые сложно получить в обычной команде разработчиков в банке или онлайн-сервисе; • возможность предлагать и быть услышанным; • конкурентный уровень полностью официальных доходов и постоянное трудоустройство по ТК РФ; • возможность официального участия во всех государственных программах поддержки ИТ-отрасли включая льготную ипотеку; • Соцпакет включает в себя: медицинскую страховку (ДМС), доплата больничных до 100% от оклада (28 дней в году), 3 оплачиваемых day-off на случай форс-мажора; мобильную связь, полное обеспечение оборудованием (включая орг. технику); возможность бесплатного обучения (внешнее обучение и профильные конференции), регулярные корпоративные мероприятия для сотрудников и их семей, а также материальная помощь при важных событиях в жизни (заключение брака, рождение детей и другое); • существенные годовые бонусы до 6 ЗП; • офисный, удаленный или комбинированный вариант работы на выбор;

Заказчик — крупный российский ритейлер. Проект связан с масштабной миграцией инфраструктуры и приложений в Yandex Cloud: перенос Kubernetes-приложений со старых версий Kubernetes, миграция виртуальных машин и баз данных, а также перевод CI/CD-процессов с Bamboo на GitLab CI. Работа ведётся в команде заказчика под руководством проектного менеджера. Обязательные требования — Не менее 3 лет коммерческого опыта в направлениях DevOps, SRE или Platform Engineering. — Практический опыт работы с сервисами Yandex Cloud: Compute Cloud, VPC, Managed Service for Kubernetes, Object Storage, а также с managed-сервисами баз данных. — Уверенное владение Kubernetes и Helm. — Опыт адаптации приложений — перенос решений со старых версий Kubernetes на актуальные. — Навыки работы с Terraform либо OpenTofu, в том числе с готовыми IaC-модулями. — Знание особенностей устаревания (deprecation) API Kubernetes, включая типовые сложности при миграции с Kubernetes 1.11. — Опыт разработки и поддержки CI/CD-пайплайнов в GitLab. — Опыт переноса CI/CD-процессов из Bamboo или схожих систем. — Практические навыки Linux-администрирования, настройки виртуальных машин и сетевых параметров. — Опыт миграции баз данных — в частности, PostgreSQL, MySQL либо других СУБД, задействованных в проекте. — Способность следовать установленным шаблонам и инженерным стандартам, а также фиксировать изменения в документации. — Готовность к работе в команде заказчика под руководством проектного менеджера. Дополнительные требования — Практический опыт работы с Yandex Managed Service для PostgreSQL, MySQL, Redis и Kafka. — Навыки применения GitOps-инструментов Argo CD, FluxCD. — Опыт использования Container Registry. — Владение Helmfile и Kustomize. — Опыт переноса legacy-приложений и миграции устаревших Kubernetes-кластеров. — Участие в крупных миграционных проектах с параллельными потоками работ. Задачи на проекте Подготовка к миграции — Изучение существующих шаблонов развёртывания: Terraform-модулей, Kubernetes-манифестов, Helm-чартов, GitLab CI-шаблонов и эксплуатационных инструкций. — Техническая инвентаризация переносимого приложения или компонента: контейнеры, зависимости, конфигурация, секреты, хранилища, БД, сетевые взаимодействия. — Оценка технической готовности компонентов к переносу и выявление отклонений от типовых шаблонов. — Согласование выявленных технических блокеров и нестандартных решений с представителями заказчика. Миграция Kubernetes-приложений — Подготовка приложений, работающих в Kubernetes 1.11, к развёртыванию в целевом Kubernetes-кластере Yandex Cloud. — Адаптация манифестов, Helm-чартов и иных deployment-конфигураций под актуальную версию Kubernetes и принятые на проекте шаблоны. — Устранение использования устаревших Kubernetes API и несовместимых параметров конфигурации. — Настройка параметров приложений: ConfigMap, Secret, Ingress, Service, PersistentVolumeClaim, resource limits/requests, probes и других необходимых сущностей. — Выполнение развёртывания и технической проверки работоспособности в согласованных окружениях. — Подготовка технических процедур отката в рамках принятого процесса релизов. — Переключение сервисов в новое окружение. Перенос ВМ и сервисных компонентов — Перенос прикладных компонентов с on-premise ВМ в Yandex Cloud с использованием существующих шаблонов и подходов проекта. — Развёртывание и настройка целевых ВМ, если компонент не переводится в managed-сервис. — Перенос баз данных и сервисных компонентов в определённые заказчиком managed-сервисы Yandex Cloud либо на целевые ВМ. — Миграция данных по утверждённой процедуре. — Техническая валидация: доступность сервиса, сетевые соединения, корректность конфигурации, целостность данных и запуск приложений. Трансформация с Bamboo на GitLab CI — Анализ действующих Bamboo-планов конкретных переносимых приложений. — Перенос логики сборки, тестирования, упаковки и деплоя в GitLab CI. — Использование существующих на проекте GitLab CI-шаблонов и общих компонентов пайплайнов. — Настройка передачи артефактов, кэширования, переменных окружения и правил запуска jobs в соответствии с принятыми стандартами проекта. — Настройка деплоя в согласованные окружения и механизма отката, предусмотренного действующим процессом. — Проверка пайплайнов на тестовом и целевом окружениях. Документирование и передача результатов — Ведение технической документации по каждому перенесённому компоненту. — Фиксация отклонений от шаблонных решений, принятых workaround'ов и известных ограничений. — Подготовка инструкций по запуску миграции, валидации, деплою и откату. — Участие в технических статус-встречах, предоставление актуального статуса и информации о блокерах проектному менеджеру заказчика.

Задачи: — Функциональное и системное сопровождение банковского программного обеспечения — Сопровождение и развитие инфраструктуры банковского программного обеспечения — Обеспечение доступности автоматизированных банковских процессов — Осуществление технической поддержки пользователей и клиентов — Накопление и передача технической экспертизы по архитектуре ИТ системы, а также по бизнес-процессам — Развитие программно-инфраструктурного ландшафта банка — Реализация пилотных проектов бизнеса Требования: — Управление серверами на базе Linux на уровне администратора — Знание микросервисной архитектуры и технологий контейнеризации: Docker, containerd — Продвинутые навыки работы с Kubernetes, Helm, Kafka — Понимание принципов построения процессов CI/CD — Понимание принципов IaC, продвинутые навыки работы с Ansible, Terraform, Terragrunt — Понимание принципов построения Observability, продвинутые навыки работы с ELK/EFK, OpenSearch, Prometheus, VictoriaMetrics — Опыт работы с облачными провайдерами, например, AWS, Yandex Cloud — Знание СУБД на уровне администратора: Redis, MongoDB — Навыки программирования на Python, Go, Java, JavaScript — Важно: kubernetes (не managed), postgres/patroni, redis, ansible, victoria metrics/prometheus, elk/opesensearch — Желательно: istio, mongo, minio, clickhouse, qdran, ebula, litellm — Работа с llm моделями инференсом и т.д. — Образование высшее, профильное техническое — Опыт работы от 3 лет Условия: — Оформление по ТК РФ или ИП в аккредитованную ИТ компанию — ДМС со стоматологией — Скидки на изучение иностранных языков от Skyeng — Скидки на фитнес от Xfit — Скидки на кино от КАРО — Техника для работы Контакты для отклика: @ivmargarita https://t.me/ivmargarita

Задачи: — Архитектура и развертывание корпоративной инфраструктуры Azure с использованием Terraform/Bicep, поддержка модульных библиотек IaC и управление состоянием. — Обслуживание, патчинг и оптимизация кластеров Azure Kubernetes Service (AKS), управление автоскейлингом, маршрутизацией ingress и политиками service mesh. — Проектирование, поддержка и обеспечение безопасности автоматизированных CI/CD пайплайнов в Azure DevOps или GitHub Actions для ускорения циклов деплоя. — Применение Azure Policy, аудит ролей IAM через Entra ID, управление ротацией секретов в Key Vault, устранение уязвимостей с помощью Defender for Cloud. — Мониторинг метрик системы, реагирование на инциденты инфраструктуры, проведение RCA и оптимизация использования ресурсов для снижения затрат. Требования: — Опыт работы не менее 5 лет с Microsoft Azure, включая compute, сети (VNets, ExpressRoute, Application Gateways) и уровни хранения. — Продвинутые навыки Terraform или Bicep для автоматизации, обнаружения дрейфа и управления состоянием в мульти-подписочных средах. — Опыт построения, защиты и масштабирования AKS, управление ingress контроллерами и деплой приложений с Helm. — Глубокое понимание построения CI/CD с Azure DevOps или GitHub Actions, включая автоматическое сканирование безопасности, соблюдение политик и безотказные релизы. — Знания в области безопасности облака с Microsoft Entra ID, Azure Key Vault, Azure Policy и RBAC в модели Zero Trust. — Опыт настройки мониторинга и алертинга с Azure Monitor, Log Analytics, Application Insights или сторонними платформами (Datadog, Dynatrace). — Локация в часовом поясе CET (+/- 3 часа). Желательно: — Сертификаты Azure AZ-104, AZ-305, AZ-400. — Навыки программирования на Python, Go, PowerShell или Bash для скриптинга инфраструктуры. — Опыт оптимизации затрат в облаке (FinOps) и управления политиками Azure Cost Management. — Знакомство с гибридными облачными конфигурациями или Azure Arc. Условия: — Своевременная оплата с гибкими вариантами вывода средств. — Предсказуемый график работы: 8 часов в день. — До 24 дней гибких выходных в год для полноценных позиций. — Долгосрочные удалённые позиции в ведущих компаниях. — Персонально подобранные вакансии без типичных рекрутинговых барьеров. — Единый процесс контрактации для множества возможностей без дополнительных оценок. — Стабильная ежемесячная оплата через Proxify.

Задачи: — Архитектура, создание и поддержка инструментов самообслуживания платформы и порталов разработчиков, позволяющих командам самостоятельно обеспечивать инфраструктуру, управлять окружениями и развёртывать сервисы. — Поддержка автоматизированных GitOps пайплайнов доставки с использованием ArgoCD/Flux, внедрение безопасных практик деплоя (canary, blue-green, автоматические откаты). — Поддержка здоровья кластеров, жизненных циклов обновлений, политик автоскейлинга и безопасности в мульти-региональных Kubernetes-развёртываниях. — Написание production-кода на Go/Python для создания кастомных Kubernetes операторов, CLI-утилит и API-автоматизации для оптимизации рабочих процессов разработчиков. — Внедрение платформенных SLI/SLO, централизованного логирования и трассировки, а также автоматизация политик безопасности и контроля затрат. Требования: — Опыт 5+ лет в platform engineering, site reliability engineering (SRE) или core DevOps с подтверждённым опытом проектирования и внедрения Internal Developer Platforms (IDP). — Экспертное владение Kubernetes, архитектурами кастомных контроллеров/операторов, сервис-мешами (Istio/Linkerd), непрерывной доставкой через GitOps инструменты (ArgoCD или Flux). — Глубокие знания Terraform, OpenTofu или Pulumi для создания модульных инфраструктурных шаблонов в облаках (AWS, GCP, Azure). — Сильные навыки программирования на Go или Python для создания расширений платформы, CLI-инструментов, Kubernetes операторов и интеграций API. — Практический опыт создания или интеграции порталов разработчиков (Backstage, Port) и автоматизированных workflow движков. — Опыт настройки телеметрии с Prometheus, Grafana и OpenTelemetry для метрик, логов и трассировок. Желательно: — Опыт с cloud-native control plane абстракциями, например Crossplane. — Знания FinOps, мониторинга затрат контейнеров (Kubecost) и автоматической оптимизации ресурсов. — Активное участие в open-source проектах CNCF. — Опыт в zero-trust безопасности, управлении секретами (HashiCorp Vault) и автоматизации комплаенса. Условия: — Своевременные ежемесячные выплаты с гибкими опциями вывода. — Предсказуемый график работы: 8-часовой рабочий день. — До 24 оплачиваемых гибких дней отпуска в год для full-time позиций. — Долгосрочные удалённые позиции в передовых компаниях. — Персонально подобранные вакансии без типичных рекрутинговых барьеров. — Единый процесс контрактации для множества возможностей без дополнительных оценок. — Стабильная оплата каждый месяц при работе через Proxify.