Вакансии

Нам важны инженерное мышление и умение создавать работающие продукты с нуля.

Компания: — Формат: hybrid Уровень ЗП: обсуждается индивидуально Занятость: — 🖥 Формат Минск 🕹 Работодатель 🕹 Список обязанностей: — Разрабатывать и поддерживать backend-сервисы на Go. — Развивать микросервисную архитектуру и REST/gRPC API.

Задачи: — Проводить технические аудиты C# / Unity разработчиков. — Проверять знания C# и Unity 3D. — Оценивать понимание архитектуры игровых проектов и принципов построения игровых систем. — Проверять знания Git / GitHub. — Оценивать понимание P2P-соединений и сетевого взаимодействия. — Анализировать выполнение технических заданий и код кандидатов. — Проводить дополнительные вопросы по ответам и решениям кандидата, чтобы определить глубину его знаний. — Выявлять сильные и слабые стороны разработчика. — Определять реальный технический уровень кандидата: Junior / Middle / Middle+ и т.д. — Формировать итоговое техническое заключение и рекомендацию по кандидату. — Взаимодействовать с HR и руководством при принятии решений по техническому найму. Требования: — Уверенное знание C# и Unity 3D. — Хорошее понимание архитектуры игровых проектов. — Понимание принципов ООП, SOLID и построения игровых систем. — Знание Git / GitHub. — Умение самостоятельно разбирать чужой код и находить технические проблемы. — Способность отличать поверхностное знание от реального понимания технологий. — Умение задавать правильные дополнительные вопросы и углубляться в ответы кандидата. — Способность объяснять технические выводы простым и понятным языком. — Опыт проведения технических собеседований (будет плюсом). — Опыт проведения code review (будет плюсом). — Опыт работы в роли Senior Developer / Tech Lead (будет плюсом). — Опыт формирования технических команд (будет плюсом). — Опыт оценки разработчиков при найме (будет плюсом). Условия: — Part-time. — Полностью удалённый формат. — Гибкий график. — Работа по мере необходимости проведения технических аудитов. — Возможность влиять на формирование технического состава текущих и будущих GameDev-проектов студии.

Вы будете создавать и внедрять решения на базе генеративного ИИ: мультиагентные системы, RAG-конвейеры, интеграции с внутренними сервисами и автоматизацию бизнес-процессов. Строить и сопровождать RAG-решения: векторные хранилища, пайплайны, ретривал.

Ведущий Full Stack разработчик C# + Angular + AI IT Вакансии Мы строим платформу для бизнес-аналитики, насыщая её возможностями искусственного интеллекта. Вакансия предполагает end-to-end подход в разработке, от идеи до продакшена.

Location: Canada What The Role Is We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless. Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting. We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next. Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help. If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on. What You'll Own You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape: Product recommendations across every surface. Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them. Personalizing the Feed. Deciding which products, editorial content and social content each family sees, and in what order. Personalizing search. Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations. Making Addie (our AI registry assistant) better at recs. Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site. In practice, you will: Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric. Make the modeling and architecture calls that span surfaces and are expensive to reverse. Design the evaluation, offline and online, that tells us a model is good before and after it ships. Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches. Partner with product, design and data to help shape what's worth building. Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org. Who You Are You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey. You bring: Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias. Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend. An ability to take an ambiguous problem and start moving before anyone hands you the full picture. A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings. An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue. AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next. Compensation We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is 299,300 to 372,600 CAD plus a target annual bonus of 20 percent of base. That's total target cash of roughly 359,160 to 447,120 CAD. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. If your timeline is tight, tell us and we'll move faster. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things To Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: United States What The Role Is We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless. Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting. We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next. Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help. If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on. What You'll Own You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape: Product recommendations across every surface. Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them. Personalizing the Feed. Deciding which products, editorial content and social content each family sees, and in what order. Personalizing search. Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations. Making Addie (our AI registry assistant) better at recs. Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site. In practice, you will: Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric. Make the modeling and architecture calls that span surfaces and are expensive to reverse. Design the evaluation, offline and online, that tells us a model is good before and after it ships. Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches. Partner with product, design and data to help shape what's worth building. Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org. Who You Are You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey. You bring: Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias. Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend. An ability to take an ambiguous problem and start moving before anyone hands you the full picture. A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings. An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue. AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next. Compensation We post real numbers. For a US-based Staff Engineer, the starting base salary range is $233,500 to $290,700, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $280,200 to $348,840. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. If your timeline is tight, tell us and we'll move faster. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things To Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: Remote; Japan (Remote); Slovakia (Remote); Spain (Remote); Czechia (Remote); Switzerland (Remote); Estonia (Remote); Singapore (Remote); Mexico (Remote); USA (Remote); Israel (Remote); Kyrgyzstan (Remote); Bulgaria (Remote); Austria (Remote); India (Remote); Iceland (Remote); Hungary (Remote); Ireland (Remote); Canada (Remote); South Africa (Remote); Brazil (Remote); Finland (Remote); UK (Remote); Romania (Remote); Cyprus (Remote); Malta (Remote); Latvia (Remote); Argentina (Remote); Poland (Remote); Uruguay (Remote) Workplace: Remote WHO WE ARE Hi, we're DuckDuckGo, the online protection company and remote-first team of 400+ on a mission to raise the standard of trust online. Founded in 2008 and profitable since 2014, our annual revenue is in the hundreds of millions USD and millions use our browser on Mac https://spreadprivacy.com/introducing-duckduckgo-for-mac/, Windows https://spreadprivacy.com/windows-browser-open-beta/, iOS https://spreadprivacy.com/duckduckgo-privacy-browser-ios14/, and Android https://spreadprivacy.com/introducing-app-tracking-protection/, our search engine https://duckduckgo.com/, and the DuckDuckGo subscription https://duckduckgo.com/pro. We also offer private, useful, and optional AI, including Duck.ai https://duck.ai/, which lets you chat privately with ChatGPT, Claude, and other AIs, all in one place.   Our culture https://duckduckgo.com/how-we-work of trust, inclusivity, and empowered project management underpins everything we do, where each team member takes full ownership of their projects, from scoping and execution to postmortem. If you're seeking end-to-end ownership of your work, you've come to the right place! YOUR TEAM AND ROLE Working on the Privacy Functional Team, you'll lead complex projects across key company-wide objectives. You'll protect the privacy of our users using Go, Node.js, Python, and (sometimes) Perl to write pragmatic, performant, testable code, and work on related projects. Potential projects include: - Designing systems for improving our search indexes and AI features without compromising user privacy - Building new features on top of our Tracker Radar https://spreadprivacy.com/duckduckgo-tracker-radar/ crawler to detect emerging privacy threats - Implementing new privacy features and maintaining existing ones, such as our Web Tracking https://duckduckgo.com/duckduckgo-help-pages/privacy/web-tracking-protections and Email https://duckduckgo.com/duckduckgo-help-pages/email-protection/privacy Protections   As a Senior Privacy Engineer, you'll own major components of our privacy technology, taking responsibility for their maintenance and improvement over time. A key part of the role will also be participation in our privacy review and audit processes, ensuring that all product developments align with our privacy principles. In time, you'll formally mentor other engineers, supporting their career growth and the growth of the Privacy Team at DuckDuckGo. ABOUT YOU - Ability to lead and collaborate on high-impact and complex projects from proposal through post-mortem. - Skills to wrangle vague problems, propose innovative solutions, and execute them effectively, involving others when necessary. - Experience working on privacy solutions in an engineering capacity (e.g. tracker blocker, differential privacy, or similar technology). - Deep technical understanding of online privacy threats and the existing solution space to protect against them. - Proficiency in any of the following: Go, Node.js, Python, Perl. - Excellent communication skills. You can validate your decisions and communicate them clearly to a variety of audiences, including non-technical stakeholders. COMPENSATION $178,500 USD annually and stock options. Compensation is transparent across the organization, and all team members within the same professional level and global region receive the same compensation.   Eligibility for company-sponsored health benefits is limited to team members based in the United States. This program does not extend to team members located in other countries, such as Canada or the UK.   Our Team Member Support Guide https://duckduckgo.com/assets/hiring/team_support_guide.pdf explains how we prioritize your wellbeing including paid parental leave, office setup, and co-working allowances. HIRING PROCESS Hiring works best when it's a two-way street. Learn how we help you get to know DuckDuckGo, envision your future role here, and find out more about how we hire https://duckduckgo.com/how-we-hire. DIVERSITY, EQUITY AND INCLUSION DuckDuckGo provides equal work opportunities to all team members and applicants, and it prohibits discrimination and harassment of any type on the basis of race, color, ethnicity, caste, religion, age, sex (including pregnancy), national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by our policies or federal, state, or local laws. We want to ensure that our hiring process is accessible. If you need reasonable accommodation for any part of the application process because of a medical condition or disability, please send an email to careers@duckduckgo.com to let us know the nature of your request. PLEASE NOTE THAT: - You’ll be required to attend meetings on camera via video conferencing - Expect to travel at least two times a year: once for our all-hands meetup and again for a team retreat (each around 4-5 days). While extenuating circumstances may impact attendance, everyone is strongly encouraged to attend. - While we offer a flexible work arrangement with no core hours, expect an average full-time commitment of 40 hours per week. - A successful candidate must pass a background check as a condition of joining the team. - By applying for this role, you confirm that all information submitted is accurate and complete. You further acknowledge that providing false or fraudulent information during the application process is cause for denial of an offer, revocation of any existing offer, or other adverse action, up to and including termination after the start of your commencement of work. Disclosure Statement: Use of AI in Hiring Process As part of our commitment to enhancing our recruitment process, we utilize artificial intelligence (AI) technology to assist in reviewing and summarizing job applications and test projects, including those tools integrated into our recruitment vendor platforms. We use AI to flag potentially fraudulent applications, analyze and summarize applicants’ experience, interviews, and project performance, and help streamline our selection process. Key Principles: - Data Privacy: All information provided in your application will be handled in accordance with our Recruiting Privacy Policy https://duckduckgo.com/static-assets/files/pages/careers/DuckDuckGo-Recruiting-Privacy-Policy-effective-September-30-2025.pdf. We ensure that your personal information is protected and used solely for recruitment purposes. - Human Oversight and Accountability: The AI technology is designed to support our hiring team by providing insights and summaries of applications and evaluations of test projects against scoring rubrics. All final evaluations and hiring decisions, however, will be made by our hiring team, who will consider the AI's input alongside other factors. - Transparency: We believe in transparency regarding our hiring practices. If you have any questions about how AI is used in our recruitment process, please feel free to reach out to us. By submitting your application, you acknowledge and consent to the use of AI technology in our review process. If you would like to request an alternative selection process, please contact us as at careers@duckduckgo.com. Thank you for your interest in joining DuckDuckGo! #LI-DNI

Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role Data Products integrates GitLab and third-party SDLC data, and builds the dashboards, APIs, and data products that turn it into trusted, interoperable intelligence for customers and internal teams. This is a 0 to 1 team and we are hiring for a foundational engineering role. That means you bring technical leadership through ambiguity, helping figure out what to build, making the foundational design decisions, and keeping delivery moving while the picture is still forming. You own the full lifecycle of what ships and stand behind it. What you'll bring Proven ability to influence as a Staff owning product or platform systems end to end across multiple engineering and product teams. High agency, i.e finds the owner, clarifies the path, makes the call, and keeps pushing until the work lands. Force multiplier and raise the people and the codebase around them Deep full-stack expertise, including strong proficiency in Go, Ruby and Node . Depth in at least one of analytics and metrics platforms, graph data systems, CDC and warehouse integration. Hands-on experience building production AI-powered tool orchestration. Experience operating multi-tenant systems across SaaS and self-managed deployment. Direct communicator who builds alignment across teams. Bias to write things down and make reasoning legible. What you'll own Architect how GitLab and third-party data is ingested, modeled, and synced into the knowledge graph as a near-real-time graph of the development ecosystem. Lead integration with external systems for business context (Jira, observability tools, Zendesk, ServiceNow), indexed into the graph. Architect the Data Marketplace so customers consume GitLab data through Snowflake, Databricks, and BigQuery with no engineering dependencies. Publish GitLab observability as OpenTelemetry and broker the data-sharing APIs. Define operational readiness for everything the team ships across GitLab.com, Dedicated, and Self-Managed. Translate an ambiguous 0 to 1 problem space into concrete, iterable roadmaps in partnership with Product, Design, and the graph backend team. Resolve cross-team dependencies across graph backend, AI Platform, and Infrastructure without escalating everything upward. Mentor senior and intermediate engineers through design reviews, pairing, and code review. Create organizational leverage through speed. You identify systemic bottlenecks, simplify processes, and design systems that dramatically improve execution velocity. About the team Data Products work across three surfaces: Dashboard and Reporting Framework Builds AI-native dashboard components so customers and internal teams can see engineering health and GitLab's impact across DORA, VSA, AI Impact, SDLC trends, security, and quality, and launch their own custom dashboards on the same framework. Internal Ingestion Ingests third-party data into the GitLab and power tools like Knowledge Graph, building connectors so that signals from systems like Jira, Zendesk, ServiceNow, and observability tools become one queryable, near-real-time graph of the developer ecosystem. External Ingestion External makes GitLab and Knowledge Graph data consumable outside the product, through marketplace listings, data-sharing APIs and SDKs, and co-branded partner products. We are a new team in a highly ambiguous, high-impact space, and we need engineers who can create clarity while building, make practical tradeoffs, unblock cross-team dependencies, and keep pushing until meaningful customer value lands. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $152,800 — $259,200 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

☁️ Strong AWS experience: 3+ years designing cloud-native architectures on it. 🔧 6+ years architecting and running CI/CD (Jenkins, GitLab, GitHub Actions, Argo CD).

Location: Amsterdam Workplace: OnSite ABOUT US Tebi is creating the first Connected Restaurant Management System that makes hospitality flow. In one seamless platform, Tebi embeds sales, reservations, kitchen prep, payments, and all the data that powers it, creating smooth service and intuitive insights. Founded by Arnout Schuijff, co-founder of Adyen, and backed by €50 million in funding from Index Ventures & CapitalG, Tebi is built in service of hospitality first. Thousands of restaurants, cafés, bars, and coffee shops across the Netherlands, UK, Italy, Spain, Germany, Denmark and Finland already love running on Tebi. ABOUT THE ROLE You'll own design for the heart of Tebi: the point of sale, kitchen display and payment flows that restaurants use every minute of service. On a busy Friday night, one restaurant might run Tebi on an iPad at the bar, handhelds on the floor, payment terminals at the tables, screens in the kitchen and a printer at the pass. All of it has to work together, often for staff who only started that week. A lot of merchants like Tebi because it's as easy to use as a consumer app, so training new staff takes less time. You'll help keep it that way as the product grows. You'll work with a product manager and five engineers, and across teams on the work we share. Some of the problems waiting for you: - Making onboarding so simple that a restaurant can get set up and run its first service with confidence. - Making the kitchen display valuable even for kitchens that still print tickets. As a design team, we want to ship work we're proud of, own our seat at the table, and push the company to aim higher. WHAT YOU'LL DO - Own design for the core aspects of hospitality service. The sales flow on the POS, the floor plan during service, the kitchen display, receipts and cash management. - Make paying the easy part. Checkout, splitting the bill, tips and service charges, settling up, and the terminals staff use to take payment. - Own the design system in the native app. We want the whole Tebi platform to share one design DNA. You'll own how it shows up in our native app: the design system, its components, and the details of how they're built. - Work AI-first and design AI into the product. Prototype in code, ship UI yourself, and help reinvent Tebi to be more helpful and proactive, like setup that configures itself for each restaurant. - Champion our merchants. Get close to the people who run their business on Tebi, and help the whole company understand them too. - Shape what we build. You'll work with the PM and engineers on which problems we take on and how we solve them. - Help the whole team level up. We're a small team, so your experience goes a long way. You'll mentor, give feedback and help other designers do their best work. WHAT YOU'LL BRING - You've led design end to end on a product people depend on, and other designers looked to you on craft. - You make complex things feel simple. Your work holds up for someone using it for the first time, in a rush, with a queue in front of them. - You're at home in the complicated system underneath: states, edge cases, money, and what happens when things go wrong. - You use AI tools in your work, or you're keen to learn fast. It's a requirement of the role, but we don't expect you to be an expert on day one. It's a bonus if you've worked on: - Native apps for tablets, phones or handhelds - Payments or fintech - Products that span several devices or real hardware - Building or running a design system - Hospitality. If you've worked a shift in a restaurant, bar or café, you'll know what the people using Tebi are up against. This probably isn't the role for you if you're happiest designing dense desktop tools for expert users. The person using your work could be on their very first shift. People who succeed at Tebi are independent, curious and passionate about hospitality. If this speaks to you we can be the right fit. Learn more about how we work from our Recipe here: https://www.tebi.com/gb/careers. This role is based in our Amsterdam office, with at least three days a week in the office. We can sponsor visas, if you are already based in the Netherlands. BENEFITS - Start-up Equity - Competitive Salary - Lunch Provided in Office - Team building events - Unlimited time off WHAT IS RESTAURANT SOFTWARE? Restaurants and other merchants use various software systems such as Point of Sale (POS), Reservations, Kitchen Display Systems (KDS), Payments, Inventory, Staffing, and the list goes on. These systems all need to speak to each other which they frequently don’t. It’s a mess, and we are fixing it. From buying a croissant at a cafe to having dinner with friends, it’s a €4 Trillion+ global market and a critical part of everyday life in today's economy. HOW WE USE AI AT TEBI We use AI the way our merchants use Tebi, to cut out the friction and get to what matters faster. We believe in a world where AI increases quality, efficiency and speed. At Tebi, AI isn't a policy or a checkbox, it's just part of how we work. It helps us write, analyse, build, and improve but doesn’t make the last call. If there's a smarter way to do something, we want to find it.

Location: Berlin adjoe builds the technologies behind mobile app growth and monetization, challenging the status quo of adtech by redefining how apps acquire users and generate revenue. Our two products, Playtime Arcade and adjoe Ads, sit at opposite ends of the mobile advertising spectrum: rewarded engagement and programmatic in-app advertising. Together they run on 13% of the world’s smartphones, connecting advertisers, publishers, and hundreds of millions of users, with one goal: making mobile advertising work better for everyone in the ecosystem. Next-Gen Machine Intelligence for Auctions & Real-Time Bidding The Data Science Research team builds the foundational algorithms that govern real-time bidding, budget pacing, and allocation mechanics across our products. Operating as a horizontal deep-tech layer, the team leverages advanced AI—specifically reinforcement learning, objective-based optimization, and control theory—to deliver critical systems that perfectly harmonize advertiser ROI, platform health, and user relevance. These frameworks scale adjoe’s products beyond standard industry limitations, utilizing behavioral and transactional data from over 770 million users. The team operates at the intersection of high-load, low-latency engineering, auction mechanism design, and state-of-the-art machine learning. Acting as the company’s internal science bar raiser, they translate complex business constraints into mathematical objectives. The stack is optimized for high throughput: PyTorch for training deep learning and RL models, distributed architectures for large-scale Bayesian inference, Trino and Athena for querying massive user-behavior data lakes, and dedicated GPU infrastructure. The full lifecycle of these AI capabilities is owned by the team—from academic paper translation and offline prototyping to deploying core algorithmic frameworks built to sustain ultra-low latency, real-time production environments evaluating tens of thousands of requests per second. Your Mission & Who We Are Looking For: - PhD or equivalent research depth, with a production track record. You have a PhD in CS, Statistics, Math, or Physics (or an MSc with extensive industry research) and a track record of peer-reviewed publications in fields like Computational Advertising, Auction Theory, Mechanism Design, or Game Theory. You’ve spent 4+ years optimizing complex systems through automated algorithms in AdTech, marketplaces, or high-frequency trading. - You translate research into production, not just prototypes. You distill SOTA research into robust, production-ready code optimized for sub-millisecond latency. At adjoe, that means architecting sophisticated auction mechanics, real-time bidding engines, and allocation algorithms serving millions of requests across a stack built on 770 million users. - Deep expertise in Reinforcement Learning and Optimization. You have hands-on, deep theoretical and technical expertise in objective-based optimization, control theory, or RL applied specifically to bidding, pricing strategy, and budget pacing under extreme production constraints. - Mastering high-dimensional data at scale. Large-scale Bayesian inference and handling sparse, high-dimensional advertising data are core to your work. You are strongly proficient in Python and related stacks, and know exactly how to architect scalable data pipelines to feed real-time optimization models. - Raises the technical bar around them. You lead architectural debates, collaborate tightly with Product Managers and Engineers to map business goals to mathematical objective functions, mentor junior scientists, and drive the team’s research direction without needing a roadmap handed to you. 🌎 WE WELCOME APPLICATIONS FROM TALENT WORLDWIDE AND PROVIDE RELOCATION SUPPORT TO HAMBURG, GERMANY FOR THOSE READY TO JOIN OUR TEAM. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. We welcome applications from people who will contribute to the diversity of our company.

• Развитие поставок данных. Проектировать и развивать RT/NRT‑поставки данных для разных сценариев работы продуктовых команд — например, для жизненного цикла заказа, работы сотрудников, складских операций и отслеживания доступности товаров.

Location: Lisbon Workplace: Hybrid ROLE HIGHLIGHTS: - Role: Forward Deployed Backend/DevOps Engineer - Location: Portugal (Lisbon) - Reports to: VP, Forward Deployed Engineering - Working type: Hybrid (On-site at customer locations approx. 50% of time) - Must be eligible and able to attain relevant national and NATO security clearances. - Must be based in-country and native level speaker of the country you're deploying to.   WHY THIS ROLE MATTERS In this role, you are the backend and infrastructure backbone defence and intelligence customers rely on. You deploy ICEYE's intelligence platform into secure (often air-gapped) environments and design the high-performance backend systems that move satellite data at scale — fast APIs, resilient services, tuned databases, automated infrastructure. Our stack: Python and Go services on Kubernetes, PostgreSQL and MongoDB, Terraform and Ansible, CI/CD pipelines that also run offline, cloud (AWS) and on-premises air-gapped clusters, with AI-assisted development as the default. This is a ship-daily role: systems you build run mission-critical workloads analysts use to protect nations. WHAT YOU'LL OWN Platform deployment & operations - Deploy ICEYE's intelligence platform into customer secure environments (on-premise, air-gapped networks, classified data centres). - Install, upgrade and operate Kubernetes clusters and containerised applications (Docker) in customer environments — cloud and on-premises. - Build infrastructure-as-code (Terraform, Ansible) and CI/CD pipelines that work without external internet access, including offline registries and artifact mirroring. - Troubleshoot deployment and production issues in disconnected environments, from the application layer down to storage and networking. High-performance backend systems - Design and build APIs, services and data pipelines that handle large volumes of SAR imagery and intelligence data with low latency. - Connect ICEYE systems to customer C4ISR infrastructure and intelligence tools through robust, well-designed integrations. - Own database design and performance at production scale (PostgreSQL, MongoDB): schemas, indexing, tuning, replication and backup. - Apply caching, queueing and horizontal scaling patterns deliberately — and capacity-plan for fixed on-premises hardware where you cannot simply scale out. Reliability, security & observability - Build monitoring, logging and alerting that work in restricted environments, so problems are found before the customer finds them. - Harden deployments to meet customer security constraints; own backup, recovery and upgrade paths for systems that cannot go down. - Run the infrastructure behind AI workloads shipped by the team — model serving, vector databases, GPU nodes — reliably and repeatably. Customer engagement & rapid delivery - Work embedded with intelligence analysts, operators and customer IT teams to understand operational and infrastructure requirements. - Rapidly prototype and iterate (working systems first, polish later) to address immediate operational needs. - Conduct hands-on training for customer administrators on platform operations. - Feed deployment experience back to ICEYE's product and engineering teams as concrete technical requirements. WHAT WE'RE LOOKING FOR Must-haves - 5+ years hands-on backend engineering building and operating production systems at scale. - Strong programming skills in Python. You write typed, tested services and you are comfortable with async APIs. TypeScript is a plus. - Proven experience designing high-performance backend systems: APIs, distributed services, messaging, caching and databases under real load. Experience with spatial, search, or vector workloads in Postgres is a plus. - Production experience in both cloud (e.g., AWS) and on-premises environments — this role lives in both. - Deep Docker and Kubernetes: deploy, debug, and upgrade clusters — not only consume them. GitOps and infrastructure-as-code experience. Pipelines that can run offline or on an isolated network are a plus. - Observability as a habit: metrics, logs, and alerts are part of done. - Infrastructure-as-code (Terraform, Ansible) and CI/CD experience, ideally including pipelines that run offline or in isolated networks. - PostgreSQL and/or MongoDB at production scale: schema design, tuning, replication, backup and recovery. - Observability as a habit: metrics, logging and alerting are part of done, not an afterthought. - Builder mindset: ship fast, iterate with feedback, and prioritise working solutions over perfect architecture. - Strong communication and customer engagement, able to work embedded with intelligence analysts / military operators. - Strong spoken and written English, able to explain technical concepts to non-technical stakeholders. - Willingness to travel 40–60% to customer sites within the region. Nice to have - Experience in defence, intelligence, or government operational environments. - Deploying to on-prem data centres and/or air-gapped networks, including offline artifact and registry management. - Event streaming and high-throughput data systems (e.g., Kafka or similar) at production scale. - Deeper Kubernetes: operators, service mesh, multi-cluster, storage and networking internals. - Security hardening and accreditation experience (system hardening baselines, audit and compliance in classified environments). - Familiarity with geospatial data, satellite imagery, or remote sensing. - Experience running infrastructure for AI/LLM workloads: GPU scheduling, model serving, vector databases. - Active use of AI-assisted development tools as part of your daily workflow. - Experience in defence tech (e.g., Palantir, Anduril, Scale AI, similar startups). WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing—at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. OUR COMMITMENT TO DIVERSITY, EQUITY AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at https://www.iceye.comiceye.com http://iceye.com

Location: Canada Workplace: remote About Xsolla Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. About the Role We're looking for a Staff Engineer to own the smart wallet and account abstraction layer of Xsolla's Web3 platform. This is an individual contributor role with outsized technical scope: you'll be the technical anchor for how millions of players get an on-chain account they never have to think about — setting direction, making hard architectural calls, and raising the bar across the org. Concretely, you'll own the account model behind Xsolla ZK, our zkSync-based L2, and the wallet that sits inside Xsolla App. Every player who signs in with Xsolla ID receives a deterministic, non-custodial smart account — derived from their identity claim, identical on every device, with private keys that never leave the client. That account is not a separate "wallet" screen: it is the player's inventory, and it backs minting, gifting, trading on our Bazaar marketplace, Merkle-based reward airdrops, gas sponsorship, and an in-app dApp browser that exposes the same signer to third-party applications through an EIP-1193 provider. You'll own the primitives underneath all of it: the ERC-4337 user operation lifecycle, EIP-7702 delegation, session keys and origin-bound Smart Sessions, paymaster and gas abstraction strategy, and the custody and recovery roadmap — including the move from raw key export to MPC custody. You will own the strategy behind account abstraction, signing, and session management at scale, and evolve our smart account and permissioning model to meet both product and compliance needs. You operate with significant autonomy, but your decisions ripple across teams — so you'll spend real time building buy-in with engineering, product, security, and legal stakeholders, not just designing in isolation. You are technically deep, calm under pressure, and comfortable being the escalation point when production wallet issues get hard — because in this domain, "hard" means a stuck user operation, a drained paymaster, or a signing prompt a player didn't understand. You write the RFCs and design docs that people actually read, and you create leverage for the broader engineering org through documentation, tooling, and mentorship — without needing a management title to do it. Responsibilities Own Smart Wallet & AA Architecture — Own the technical strategy and architecture of our smart wallet platform, covering the account model, signing, session management, and gas abstraction at scale. Design the Account & Signing Model — Design and evolve our ERC-4337 user operation lifecycle (prepare → sign → submit → confirm), EIP-7702 delegation, deterministic address derivation from identity, and the session-key and permission primitives that let players act without a prompt on every transaction. Own Gas Abstraction — Set the paymaster and gas-sponsorship strategy: what we sponsor, how we meter and cap it, how we defend it from abuse, and how it degrades when sponsorship is unavailable. Harden the dApp-Facing Surface — Own the security model where our signer meets third-party applications: EIP-1193 / EIP-6963 provider behavior, origin-bound and policy-versioned sessions, trust tiers, and the transaction and signature confirmation flow. Define what a player is actually approving, and make sure the UI can prove it. Drive Custody & Recovery — Lead the custody roadmap from today's interim mechanisms toward MPC-based custody, and design recovery paths (passkeys, guardians, social recovery) that a non-crypto-native player can complete without losing assets. Drive Cross-Team Technical Decisions — Drive decisions on account architecture, SDK contracts, data modeling, and platform reliability, and build buy-in across the wallet, marketplace, SDK, mobile, and security teams. De-Risk Proactively — Identify systemic risks — key management, signature phishing, reorgs and indexer staleness, bundler and RPC dependencies, contract upgrade paths — and lead initiatives to resolve them before they become incidents. Set Engineering Standards — Define engineering standards, review critical code, contracts, and designs, and create leverage for the team through documentation, tooling, and mentorship. Align with Stakeholders — Collaborate with product, security, legal, and infra teams to align on roadmap and translate business and regulatory needs into well-scoped technical plans. Own Production Escalations — Serve as the go-to escalation point for complex production issues in the wallet and account abstraction domain. What You Bring Account Abstraction & Smart Wallets ERC-4337 Depth — Deep, hands-on understanding of ERC-4337: EntryPoint (v0.6 through v0.8), the UserOperation lifecycle, bundler and paymaster roles, validation rules (ERC-7562), gas estimation and its failure modes, counterfactual deployment, and signature validation for undeployed accounts (ERC-6492). EIP-7702 & the Post-Pectra Landscape — Working knowledge of EOA delegation, its interaction with ERC-4337 EntryPoint v0.8, and the trade-offs and risks it introduces (residual key authority, delegation phishing, storage collisions). Smart Account Implementations — Experience building on or extending production smart account implementations (Safe, Kernel, Biconomy, Coinbase Smart Wallet, or equivalent), and familiarity with modular account standards (ERC-7579 / ERC-6900). Session Keys & Delegated Permissions — Experience designing scoped, time-limited, policy-bound authority: session keys with TTL and contract allowlists, origin binding, permission revocation, and delegated-permission standards (ERC-7710 / ERC-7715). Signature Schemes & Wallet Interfaces — Practical command of EIP-712 typed data, ERC-1271 contract signatures, WebAuthn / passkey (P-256) signers, and the wallet-facing standards: EIP-1193, EIP-6963, EIP-5792 batched calls, ERC-7677 paymaster interfaces. Production Wallet Experience — Experience designing or operating a production smart wallet or account abstraction system serving real users and real value. Production Crypto Track Record Scale in a Major Crypto Organization — Substantial engineering experience at a large crypto product or protocol organization — for example Coinbase, Kraken, Base, Safe, the Ethereum Foundation, Consensys / MetaMask — or a comparable wallet, exchange, or account-abstraction infrastructure team where wallet correctness and custody were core to the product. Operational Judgment Under Value at Risk — You have shipped and operated systems where a bug meant lost funds, and you can talk concretely about the guardrails, reviews, and rollback paths you put in place. Smart Contracts & EVM Solidity & EVM Fluency — Ability to read, review, and write account, paymaster, and module contracts; gas-aware design; upgradeability and migration patterns; working effectively with external auditors. L2 Specifics — Understanding of L2 execution differences and how they affect wallet design: native account abstraction on zkSync-family chains, transaction and fee models, finality and reorg behavior, and RPC and indexer semantics. Backend Engineering Go Engineering — Strong Go (Golang) engineering skills: idiomatic code, concurrency patterns, performance profiling. TypeScript & SDK Design — Ability to design and own client-side SDK surfaces in TypeScript that other engineering teams — internal and external — build on top of. Distributed Systems — Experience with distributed systems and their trade-offs (consistency, availability, failure modes), and with reconciling off-chain state against an authoritative on-chain result. Data & Infrastructure PostgreSQL — Schema design, query optimization, migrations at scale. Kubernetes — Deploying, operating, and debugging services in a k8s environment. Message Streaming — Kafka or NATS — event-driven patterns, consumer groups, at-least-once delivery. Git & CI/CD — Git and modern CI/CD practices. Security Key Management — Hands-on experience with key material in production: platform secure storage (Keychain / Keystore), HSMs, MPC or threshold signing, and the operational discipline around each. Wallet Threat Modeling — Solid grasp of the wallet attack surface: signature and delegation phishing, malicious dApp origins, replay and cross-chain replay, token approval abuse, and paymaster griefing and DoS. Leadership Cross-Team Initiative Leadership — Proven ability to lead multi-quarter technical initiatives across teams. Architectural Influence — Track record of influencing architecture and standards beyond your immediate team. Written & Verbal Communication — You write RFCs and design docs that people actually read. Nice to Have Experience working in the video game industry, building or operating platforms for game developers, publishers, or players Hands-on experience with the zkSync / Elastic Chain ecosystem (ZKsync OS, Matter Labs stack, native AA and paymaster flows, custom L2 operations) Experience with embedded and ecosystem wallet providers or AA infrastructure vendors (thirdweb, Privy, Dynamic, Turnkey, Pimlico, Alchemy, Biconomy, ZeroDev, Safe{Core}) — and clear views on where to build versus buy Experience with MPC / threshold custody, social recovery, or guardian-based recovery in a consumer product Experience with NFT and token infrastructure at scale: ERC-721 / ERC-1155 / ERC-20 mechanics, marketplace contracts, Merkle-based airdrop and claim distribution, chain indexing services Contributions to open-source wallet, security, or identity projects — including authorship or review of ERC / EIP standards Familiarity with compliance requirements relevant to crypto consumer products: KYC / AML, geofencing, MiCA, SOC 2, ISO 27001, GDPR data minimization, audit logging Experience with identity and auth integration for wallet derivation (OAuth 2.0 / OIDC, JWT verification, token scoping) Background in platform or infrastructure engineering — building systems other engineers build on top of Experience owning a mobile wallet surface (React Native / Expo, WebView provider injection, native signing UI) Hands-on, up-to-date experience with modern AI tools (e.g. Claude, Copilot, Cursor) for code generation, review, and accelerating day-to-day engineering work How We Work Xsolla operates across multiple time zones, and the smart wallet underpins identity, ownership, and value transfer for every Web3 product we ship. Strong written communication is essential — your architectural decisions and designs need to stand on their own and be actionable without you in the room. We value directness, technical depth, and follow-through. In this domain that means saying plainly when a design has custody, security, or reversibility implications, defending your position with evidence, and staying engaged until it's resolved. Where a decision touches player funds or key material, we expect the conservative call to be argued for explicitly rather than assumed. Benefits We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play.

Location: Paris; Zurich; Madrid; Amsterdam; London; Brussels; Berlin Workplace: Hybrid 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. ROLE SUMMARY We are looking for an Anti-Corruption & Trade Compliance Legal Counsel to play a central role in the building, development and operation of Mistral AI's corporate compliance framework, with a particular focus on anti-corruption, economic sanctions and export controls. Reporting to the Lead Anti-Corruption & Trade Compliance, the position offers genuine build-from-scratch ownership of core policies, processes and tools. It combines programme development, day-to-day compliance operations and cross-functional advisory work. The role involves close collaboration with Legal, Finance, Procurement, Sales, Security, and Product and Engineering to translate legal requirements into clear, proportionate and auditable processes. Key responsibilities Anti-corruption/Sapin II - Coordinate Sapin II Action Plan deployment of relevant policies, controls, training and third-party procedure. - Lead the day-to-day operation and continuous improvement of risk-based due diligence from integrity screening through enhanced diligence and periodic review; - Support the implementation and periodic review of the code of conduct, related policies, whistleblowing framework and training programme, - Administer the gifts, hospitality and conflicts-of-interest processes, including reviewing requests and declarations, maintaining the relevant records and registers, and providing practical guidance to business teams. - Work with Finance and Internal Control to define and monitor risk-based anti-corruption accounting controls. - Contribute to the monitoring and periodic assessment of the anti-corruption programme, including programme records, metrics and reporting; monitor relevant regulatory and enforcement developments; and support anti-corruption incidents, internal reviews and investigations. Economic sanctions and export controls - Manage screening for new and existing counterparties as part of third-party due diligence and transaction-review processes. - Support the Lead Anti-Corruption and Trade Compliance in export control classification of AI models, software, technology, compute infrastructure and hardware. - Work with Procurement, Operations, Product and Engineering to embed screening and access-control requirements into onboarding, contracting and deployment processes, and maintain clear, auditable records and internal guidance. - Develop and maintain standard sanctions and export-control contractual positions and clauses, and support their review and negotiation in customer, supplier, partner and reseller agreements. - Monitor relevant regulatory and enforcement developments; coordinate external counsel and advisers; contribute to programme reporting for Legal leadership. QUALIFICATIONS AND SKILLS - Legal Master degree (Master’s in Business Law, Corporate Law, Compliance, or equivalent). Compliance certifications are also an asset. - A minimum of 5 years of relevant experience in a company, law firm, consulting firm or regulatory authority. - Substantive exposure to at least two of the following areas: anti-corruption and Sapin II, economic sanctions, and export controls. - Experience in the technology or AI sector is a plus (understanding of data, semiconductors, or dual-use goods), as well as knowledge and understanding of artificial intelligence. - Analytical and problem solving skills: Candidates should be able to analyze complex topics and have strong problem-solving skills, and be able to dig into internal systems. - Pedagogy: Excellent written and verbal communication; strong ability to communicate legal advice to clients and colleagues, and presenting complex legal concepts in a clear and understandable manner. - International mindset: International experience is a plus. - Adaptability: Given the rapidly evolving nature of AI technologies and compute topics, and the legal landscape surrounding them, candidates should be adaptable and willing to continuously learn and update their skills and knowledge. - Ability to work independently and in a team-oriented, collaborative environment. - Ethical Awareness: Ability to promote an ethical and responsible culture. 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: Biassono, Italy; Milan, Italy Workplace: Hybrid Artificial Intelligence. Actual Impact. At Docebo, we’re using AI to change how people learn at work—and we mean actually change it. We’re an AI-powered learning platform that helps organizations create, deliver, and manage training all in one place. But our real mission goes deeper: we help teams move faster, work smarter, and focus on the work that truly matters. Our platform is built with intelligent, time-saving tools that personalize learning, eliminate busywork, and turn training from a checkbox into a superpower. The result? Better experiences for learners and real results for businesses. We’re shaping the future of learning with a team that isn’t afraid to challenge the status quo. If you're excited by the idea of using AI to make work-life better for real people–you’ll feel right at home here. And it’s not just what we build, it’s how we show up. At Docebo, our values aren’t just posters on the wall—they guide how we work every day. We call it the Docebo Heart: trust by default, assume positive intent, and create space for different perspectives to thrive. So… what are you waiting for? Join 900+ Docebians around the world and help us reinvent the way people learn, because learning never stops. 🚀 THE ADVENTURE AHEAD Ready to launch your cloud engineering journey by helping power the future of enterprise learning? As a Cloud Engineer I at Docebo, you won’t just keep systems running—you'll collaborate with seasoned mentors to automate, secure, and scale our multi-tenant AWS cloud environments. You will play a vital role in keeping our platforms robust, compliant, and rock-solid for millions of users worldwide. If you're eager to turn complex infrastructure challenges into seamless, high-impact performance, your next big adventure starts here! 🛠️ THE DAY-TO-DAY - Build the Foundation: Implement defined AWS compute, storage, networking, and IAM changes alongside senior engineers using best-in-class multi-tenant patterns. - Automate Everything: Craft and refine Infrastructure-as-Code (Terraform, CloudFormation) modules and scripts to streamline routine provisioning, maintenance, and backups. - Master Observability: Configure dynamic dashboards and alerts in tools like Datadog and CloudWatch to keep a proactive finger on overall system health. - Troubleshoot & Resolve: Dive into non-production environments to investigate issues, analyze logs and metrics, apply targeted fixes, and escalate complex puzzles when needed. - Drive Cross-Functional Synergy: Collaborate closely with Product Engineering and Site Reliability Engineering (SRE) teams to translate requirements into smooth cloud changes. - Guard the Castle: Support critical FedRAMP system patching routines, monitor security compliance dashboards, and take swift action to resolve vulnerabilities. - Document for Success: Create clear runbooks, configuration updates, and script documentation so the entire team can easily reuse and build upon your work. ⚡ YOUR SUPERPOWERS - Solid Educational Foundation: A Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or equivalent hands-on project experience. - Early Cloud Craft: 1–2 years of experience or project work in cloud or infrastructure engineering, with exposure to AWS (or another major cloud provider). - Tooling & Scripting Chops: Comfort navigating Linux, writing scripts in Bash or Python, and managing code using Git alongside CI/CD tools like GitLab CI or Jenkins. - Incurable Curiosity: A high interest in modern containerization (Docker, Kubernetes) and Infrastructure-as-Code tools such as Terraform or CloudFormation. - Growth Mindset: A strong problem-solving approach paired with an enthusiastic drive to continually elevate your cloud engineering skills. OUR HYBRID WORK PHILOSOPHY 🤝 Great work can happen anywhere but coming together helps us go further. Our team spends three days a week in the office (Tuesday-Thursday) to collaborate, solve problems, and learn from each other at either our Milan or Biassono location. With flexibility the rest of the week, it’s a balance designed to help everyone do their best work and keep growing.   OUR TOTAL REWARDS PHILOSOPHY 🎉 Our Total Rewards Philosophy centers around three core areas to reward and care for our People: - Rewarding Impact: We lead with competitive pay to reward the impact, skills and traits that fuel our success. - Fostering Holistic Wellbeing: We care deeply about and invest in the whole person with programs that support our people’s physical, mental, and financial well-being. - Empowering Our Talent Culture: We build a culture of trust and empowerment by designing our rewards and benefits with transparency, equity, and flexibility, enabling our people to do their best work and stay for the long haul.   OUR PROMISE TO YOU 😍 - Financial Wellness: Own a piece of Docebo through our Employee Share Purchase Plan (ESPP) at a 15% discount, plus a competitive compensation package. - Your Well-Being, Covered: You’ll get access to health benefits, so you can get the care you need when you need it. - Rest, Relax, Repeat: Rest and recharge with paid vacation days, two company-wide Docebo Days, floating holidays for cultural celebrations, and your birthday off! - Family First: We provide coverage offering you time with your little one(s) so you can soak up all those precious moments. Fun fact: we had 30 Docebian babies join the family in 2025! - Fuel for Your Day: Receive a meal voucher for every working day, so you can focus on doing your best work while enjoying a meal that keeps you energized. - Connections That Count: Connect with global communities through our Employee Resource Groups (including PRIDE, DWA, BIDOC, and Green Ambassadors) and company-wide events that keep the fun rolling all year long.

Workplace: none About Utorg Founded in 2019, Utorg builds the infrastructure for stablecoin payments: on- and off-ramps, self-custodial wallets, and crypto cards. Over 2 million users across 130+ countries already buy, hold, and spend crypto through our app. On the B2B side, the same rails power 2,100+ platforms, with $2.4B+ moved to date. Fully MiCA-authorized across the EEA. PCI DSS Level 2 certified, backed by Dragonfly, TA Ventures, and Hypra. Location: Remote Tech stack Frontend: React 18/19, TypeScript, Vite, TanStack Query / Router / Table, Zustand, MUI, Tailwind + shadcn/ui, Next.js, i18next, Sentry Testing: Playwright, Vitest, Testing Library, MSW Backend: Java 17 + Spring Boot 3, Kotlin + Spring Boot 4 (new services), Node.js/TypeScript services, PostgreSQL, Redis, NATS, Temporal Infrastructure: Docker, Kubernetes (GKE), FluxCD, GitHub Actions, Cloudflare Web3: viem, ethers AI: Claude Code, MCP, custom skills and plugins, AI code review in CI The role We are looking for a senior engineer who builds product features end-to-end — mostly on the frontend, with the confidence to change the backend when the feature needs it — and who already works agent-first. Our team plans, writes, tests, and reviews code with AI agents. You will own the frontend of our payment products and help turn good AI habits into shared team workflows. The split is roughly 70% frontend / 30% backend. What you will work on Crypto on/off-ramp widget — an embeddable buy/sell flow with KYC, card payments with 3-D Secure, alternative payment methods, and a customer account area—one codebase, built for multiple white-label brands. Merchant checkout — hosted payment pages, from a simple one-step checkout to a full multi-step flow with KYC and compliance screens. Back-office admin apps — internal tools that operations, compliance, and support use every day. A legacy admin is being replaced by a new one built on a modern stack. Backend changes — API endpoints and business logic in our Java/Spring Boot services, so a feature doesn't stop at the API boundary. Responsibilities Own features from ticket to production: UI, API contract, backend change, tests, release, and monitoring. Make frontend architecture decisions and drive ongoing migrations (legacy admin → new admin, older UI libraries → modern stack, stricter type checks). Build and improve AI-driven development workflows: project context files, shared skills and commands, automated PR review in CI, agent-driven end-to-end and visual checks. Review code — both teammates' and agents' — and keep the quality bar high. Work with product, design (Figma), QA, and backend engineers in a weekly release cycle. Must have 5+ years of commercial frontend development, 3+ years with React + TypeScript in production. Solid modern React: server-state management (TanStack Query or similar), client state (Zustand/Redux), forms, routing, performance. Comfortable with large legacy codebases, not just greenfield projects. Production backend experience in at least one language. Java or Kotlin with Spring is a plus; Node.js/TypeScript, Go, or others are fine. You can design a REST API, work with PostgreSQL (schema, indexes, migrations), and ship changes in our Java services. Agentic development is your daily way of working — with Claude Code, Codex, or a similar agent, not just autocomplete. Specifically: you keep project context files ( CLAUDE.md / AGENTS.md ) and write your own skills, commands, or subagents; you connect agents to real tools through MCP (issue tracker, GitHub, Figma, databases, browser); you work in a plan → implement → verify loop, where the agent proves its work with tests, type checks, and browser automation; you run agents in parallel and headless (for example, an AI review bot in CI); you review agent output critically and know the failure modes: invented APIs, silent scope creep, "fixing" a test instead of the code, leaked secrets, prompt injection; you keep up with how agentic tools change (new features, models, practices) and bring what works into your workflow . Testing: Playwright for end-to-end, Vitest/Jest for unit and integration tests. Security-minded: real money, personal data, auth tokens, iframes, and cross-origin messaging. Fluent Russian (the team's working language). English good enough to read and write technical texts: tasks, pull requests, and docs are in English. Nice to have Payments/fintech: card flows and 3-D Secure, alternative payment methods, KYC SDKs (e.g., SumSub), fraud prevention, open banking. Web3 on the frontend: viem / ethers, wallet connection, EIP-712 signing. Multi-brand (white-label) products, theming and design tokens. OpenAPI-generated clients (Orval), TanStack Router / Table. Kotlin, Spring Boot, NATS, Temporal. Docker, Kubernetes, GitHub Actions, GitOps (FluxCD), Cloudflare Workers. How we work with AI Every main repository has AI context files and repo-specific skills. An internal plugin marketplace ships team-wide skills (code review, release flow, back-office operations). AI code review runs on pull requests in CI. It advises, and humans decide. Custom MCP servers provide agents with secure access to internal systems. The company pays for AI tooling. What we offer Fully remote work in an international team. A team where AI-first engineering is the norm, not an experiment. Real influence on architecture and on how the team works. A product at real scale: millions of users and thousands of partner platforms. Competitive salary based on individual performance review. Transparent feedback culture that values ownership and visible impact. Recruitment process Apply with your CV. Application review. HR interview with a short technical screen. Technical interview: a live task solved with your own AI agent while sharing your screen, plus a design discussion. Final interview with the CTO. Offer.