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Location: Lviv Workplace: onsite Ajax Systems, an international tech company and the largest manufacturer of security systems in Europe. We are looking for a new team member to join our System devisions as Java Developer. The System Division is responsible for building and developing the Ajax software ecosystem. The team develops and maintains OS Malevich and the Video Management System, builds scalable cloud infrastructure, and creates client applications for multiple platforms, ensuring that all system components work together as a unified ecosystem. The division works with Java, Kotlin, Swift, C, C++, and Python. It includes embedded, cloud, mobile, and desktop engineers who ensure the stable operation of Ajax as a single digital platform. Required skills: 5+ years of commercial experience in backend development with Java in an enterprise environment. Strong understanding of Java Concurrency and hands-on experience with concurrent programming in production systems. Solid understanding of SOA, microservices and event-driven architecture. Practical experience with cloud computing platforms. Experience building and supporting high-load, scalable and highly available systems; Hands-on experience with messaging brokers. Strong understanding of modern backend infrastructure, NoSQL, key-value databases and in-memory storage solutions. Practical experience with Kubernetes. Experience with Git, Gradle or othet CI/CD tools. Strong knowledge of unit testing and automated testing approaches   Would be a plus:

Location: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers people to perform at a higher level through a deeper understanding of their bodies and daily lives. We handle massive amounts of data continuously streaming up to the cloud from people improving their health and wellness to the world’s greatest sports teams and athletes mandating a fault-tolerant and highly available product. The Connectivity team focuses on bridging the gap between embedded and mobile engineering, ensuring a seamless and consistent experience for members wearing a WHOOP strap. As a Staff Android Engineer on the Connectivity team you'll own the architecture of the software that connects WHOOP hardware to the Android app, and set the technical direction for how that connection performs at scale. From ensuring timely firmware updates to designing innovative ways to establish connections from software to hardware, we bring WHOOP to the highest level of performance and availability across the globe using the latest cutting edge technology. At the Staff level, your impact is measured as much by the engineers and decisions you influence as by the code you write. What you’ll do: - Own the architecture of the Android connectivity layer end to end, from the BLE transport up through history sync and firmware delivery, and drive its evolution across a large modular codebase - Collaborate within a cross-functional environment alongside WHOOP hardware, firmware, and software teams - Establish and refine communication protocols between the WHOOP strap and Android, ensuring alignment with iOS standards - Apply expert-level mastery of the Android Bluetooth stack to manage GATT operations, bonding, and reconnection logic in real-world scenarios - Own connection reliability across the fragmented Android device landscape by diagnosing and mitigating OEM specific Bluetooth, power management, and permission behavior - Create and own systems that aid in analyzing connectivity health of our members, and use that telemetry to set team priorities - Manage a prioritized backlog centered on reducing technical debt, improving code health, and enhancing module testability - Elevate engineering quality through rigorous code reviews, expanded test coverage, and refined architectural design practices - Utilize expert Kotlin proficiency to build product features and define patterns for the broader engineering team - Document new features and architecture using Jira, Confluence and preparing code using Github feature, develop, and master branches - Participate in the incident commander rotation for the whole WHOOP ecosystem and also the release process including getting the app built, managing build variants, signing, sending and testing through Firebase, and submitting to the Play Store - Analyze and monitor user metrics and feedback to determine crash rate or potential bugs and to improve engagement - Represent Android Connectivity in cross-functional forums, including bug triage, product syncs, and firmware coordination - Facilitate the ramp-up of mobile developers, mentor engineers across the Android organization, and assist the backend team with data contracts Who you are: - You are experienced working with consumer-facing apps that control BLE devices. - You have a track record of influencing engineers beyond your own team in the application of architectural and platform design principles - Expert knowledge of best practices for concurrency and multithreading, including Kotlin coroutines and Flow - Product minded engineer with empathy for the member experience - Willingness to learn and grow rapidly across Android and external systems - Extensive experience building, testing, debugging, and delivering native Android apps in a professional environment - Expert knowledge of Android application structure and components as well as lifecycle and Android Design Guidelines - Strong experience with Jetpack Compose and modern declarative Android UI - Experience with Kotlin and frameworks such as Koin, Android Jetpack libraries (including ViewModel, Flows, and Navigation), Room database, and Retrofit / OkHttp - Experience designing modular architecture and dependency boundaries in a large multi-module Gradle codebase, including patterns such as MVI and MVVM - Excellent knowledge of Android Studio, Gradle and CI systems - Experience debugging and diagnosing issues across complex or distributed systems such as firmware, mobile, and backend - Experience using Git to organize feature work - Experience communicating with a RESTful backend - Firm belief that automated testing is important and experience writing both Unit and UI tests - Excellent collaboration and communication skills, driving cross functional problem solving, tradeoff definition, and optimization - Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office. Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/to determine employment eligibilityThe WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success. The U.S. base salary range for this full-time position is $170,000 - $230,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Задачи: — разработка прикладных Android-приложений, включая UI, экраны и навигацию; — создание системных модулей, таких как фоновые сервисы и взаимодействие с системными API; — работа с локальными хранилищами данных и кэшированием; — оптимизация производительности приложений, включая ускорение запуска и снижение потребления памяти и энергии; — написание тестов и настройка процессов сборки; — выполнение исследовательских задач и прототипирование новых функций (PoC). Требования: — уверенное владение Java и Android SDK; — хорошие знания языков С и С++; — понимание принципов работы операционной системы Android; — знание принципов объектно-ориентированного программирования и архитектурных паттернов; — умение читать техническую документацию на английском языке. Будет преимуществом: — хорошее знание Kotlin; — опыт системной разработки для мобильных операционных систем; — желание заниматься не только прикладным, но и системным программным обеспечением; — стремление разобраться в устройстве внутренней архитектуры ОС Android. Условия: — гибридный формат работы с офисом в Москве. Компания НТЦ «Вулкан» является российской аккредитованной IT-компанией, работающей в сфере сервисных IT и информационной безопасности, разработке прикладного ПО, создании VR/AR-приложений, заказной разработке электроники и анализе защищенности embedded-устройств. Клиентами компании являются крупные коммерческие организации и государственные структуры.

— Проектировать и развивать архитектуру платформы и доменную модель: заявки, биллинг, платежи, лицевые счета, пропускные системы. — Принимать ключевые технические решения, оценивать trade-offs, доводить их до реализации и описывать в виде понятных команде договорённостей.

Location: Kyiv Workplace: onsite Ajax Systems, an international tech company and the largest manufacturer of security systems in Europe. We are looking for a new team member to join our System devisions as Java Developer. The System Division is responsible for building and developing the Ajax software ecosystem. The team develops and maintains OS Malevich and the Video Management System, builds scalable cloud infrastructure, and creates client applications for multiple platforms, ensuring that all system components work together as a unified ecosystem. The division works with Java, Kotlin, Swift, C, C++, and Python. It includes embedded, cloud, mobile, and desktop engineers who ensure the stable operation of Ajax as a single digital platform. Required skills: 5+ years of commercial experience in backend development with Java in an enterprise environment. Strong understanding of Java Concurrency and hands-on experience with concurrent programming in production systems. Solid understanding of SOA, microservices and event-driven architecture. Practical experience with cloud computing platforms. Experience building and supporting high-load, scalable and highly available systems; Hands-on experience with messaging brokers. Strong understanding of modern backend infrastructure, NoSQL, key-value databases and in-memory storage solutions. Practical experience with Kubernetes. Experience with Git, Gradle or othet CI/CD tools. Strong knowledge of unit testing and automated testing approaches   Would be a plus: experience with these technologies: Redis, Netty, Akka, NATS, AWS, Kafka, MongoDB, gRPC. Practical experience with Kotlin. Desire to grow into a team leadership role. What you will do:   design and develop core backend services and data pipelines for the product line. Build clean, maintainable, and production-ready code with a strong focus on quality. Contribute to backend architecture, drive technical decisions and document solutions for reliable deployment and operations. Ensure proper test coverage with unit and integration tests. Take ownership of performance, scalability and cost efficiency within your domain. Maintain production reliability through monitoring, alerting, dashboards, and runbooks. Investigate and resolve production issues, including deep-dive analysis of complex cases. Work in a strong engineering culture with testing, continuous delivery and DevOps practices. Collaborate closely with product and engineering teams to deliver new features and improve existing services.   We offer:   The opportunity to suggest and implement your own ideas that directly influence the product and its mass production A place in a fast-growing company with a motivated and professional team Competitive salary Medical insurance English classes The opportunity to participate in Ajax’s internal beta-testing program for security systems  Discounts from partner companies Discounts on Ajax products

Уверенный разработчик на Java или Kotlin. Хорошо знает SQL и умеет работать с реляционными базами данных.

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

• 5+ years of Java backend development experience. • Strong Spring Boot, REST APIs, microservices and SQL skills.

Предстоит добавлять функции, участвовать в проработке API и интерфейсов, следить за плавностью работы экранов.

Location: Казань Команда Управления развития платформенных сервисов кибербезопасности в поиске Java разработчика Обязанности * работа в роли разработчика в Agile-команде * оценка трудоёмкости доработок, планирование работ в спринтах * контроль работ, code review * техническая экспертиза * написание технической документации. Требования * Java 17/21: уверенное знание языка, многопоточности, Collections, Streams API * Spring/Spring Boot: конфигурация, жизненный цикл бинов, управление контекстом, REST API * PostgreSQL: умение писать оптимальные запросы, работать с индексами, понимать уровни изоляции транзакций * Apache Kafka: понимание семантики доставки, работы с consumer groups, управления смещениями * NoSQL DB: распределённые кэши, опыт работы с Ignite или другими * инфраструктура: контейнеризация (Docker), оркестрация и деплой в кластерах (Kubernetes / OpenShift) * архитектура ПО: принципы SOLID, шаблоны проектирования (Design Patterns).   Будет преимуществом: * Kotlin: базовое знание языка, понимание корутин и data classes (готовы рассмотреть Java-разработчиков с желанием освоить) * Reactive Programming: Project Reactor, неблокирующий I/O * Micronaut / GraalVM: легковесная микросервисная разработка, Native Image * глубокое понимание JVM internals (GC, memory model, performance tuning) * gRPC: опыт разработки и интеграции сервисов. Условия * комфортный современный офис в Казани * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * бесплатная подписка СберПрайм, скидки на продукты компаний-партнеров.

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 Card Experiences team builds the product surfaces that make the Affirm Card feel simple and trustworthy. We own the cardholder journey from the moment a card is ordered to every time it's used. Our work spans the full stack: customer-facing web and mobile experiences and the backend services behind them. You'll work closely with product, design, risk, and operations partners to turn customer pain points into shipped improvements, and use data to measure their impact. You'll own features end to end, from shaping the problem to launching and monitoring in production, and you'll help raise the bar on reliability and on-call health. AI is central to how we work. We use it to build faster, to improve the quality of what we ship, and to create smarter, more helpful customer experiences. We lead from the front on adopting it, while holding a high bar on security and craft. A card is a high-trust product, so speed never comes at the expense of quality. If you want to help change how people plan their purchases, with a customer-first mindset and an eye for both speed and craft, we'd love to meet you. What You'll Do You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes. You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, policies, testing and alerting in place to support “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What We Look For This is a full stack role. You have 8+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. You have an extensive track record of developing highly available distributed systems using technologies like AWS, MySQL, Spark and Kubernetes. You have a total of 8+ years of experience as a software engineer. You are proficient in developing web apps using declarative UI frameworks like React Native or React or Vue. You are proficient in designing, developing and launching systems at scale. You have experience delivering major features, system components or deprecating existing functionality in a system through the definition of a technical and execution plan. You write high quality code that is easily understood and used by others. You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work. You think AI first and an adopter of latest technologies. You identify trends and safely apply them to the work. Your growth and impact trajectory demonstrates that you have mastered gathering and iterating on feedback from your engineering and cross-functional peers. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. This position requires either equivalent practical experience or a Bachelor’s degree in a related field. 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: CAD $181,000 - $241,000 Location - Remote Canada 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. #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 Card Experiences team builds the product surfaces that make the Affirm Card feel simple and trustworthy. We own the cardholder journey from the moment a card is ordered to every time it's used. Our work spans the full stack: customer-facing web and mobile experiences and the backend services behind them. You'll work closely with product, design, risk, and operations partners to turn customer pain points into shipped improvements, and use data to measure their impact. You'll own features end to end, from shaping the problem to launching and monitoring in production, and you'll help raise the bar on reliability and on-call health. AI is central to how we work. We use it to build faster, to improve the quality of what we ship, and to create smarter, more helpful customer experiences. We lead from the front on adopting it, while holding a high bar on security and craft. A card is a high-trust product, so speed never comes at the expense of quality. If you want to help change how people plan their purchases, with a customer-first mindset and an eye for both speed and craft, we'd love to meet you. What You'll Do You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes. You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, policies, testing and alerting in place to support “keep the lights on” & on-call efforts. You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. You will help develop talent on your team by providing feedback and guidance, and leading by example. What We Look For This is a full stack role. You have 8+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin. You have an extensive track record of developing highly available distributed systems using technologies like AWS, MySQL, Spark and Kubernetes. You have a total of 8+ years of experience as a software engineer. You are proficient in developing web apps using declarative UI frameworks like React Native or React or Vue. You are proficient in designing, developing and launching systems at scale. You have experience delivering major features, system components or deprecating existing functionality in a system through the definition of a technical and execution plan. You write high quality code that is easily understood and used by others. You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work. You think AI first and an adopter of latest technologies. You identify trends and safely apply them to the work. Your growth and impact trajectory demonstrates that you have mastered gathering and iterating on feedback from your engineering and cross-functional peers. You have strong verbal and written communication skills that support effective collaboration with our global engineering team. This position requires either equivalent practical experience or a Bachelor’s degree in a related field. 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 Pacific base pay range (CA, WA, NY, NJ, CT): $230,000 - $290,000 USA Sapphire base pay range (all other U.S. states): $204,00 - $264,000 #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: AU: Sydney (45 Clarence St); AU: Melbourne: (260 Burwood Rd) Workplace: Hybrid The role You will design, build and own the production systems behind Xero’s AI features: the services, pipelines and infrastructure that power LLM-driven and agentic experiences for millions of small businesses every day. This is a software engineering role. You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship. You don’t need a machine learning background. We’re looking for strong production engineers, ideally with experience building LLM or agentic systems, and ML depth can be learned on the team. Beyond architecture, you’ll lift engineering capability across AI Products by setting standards, mentoring engineers and partnering across Xero to make data usable and systems dependable.   The team You’ll join AI Products, a diverse, globally distributed team of scientists, engineers, product managers and analysts within our broader Data & AI business. Engineers here partner closely with Applied Scientists early on to build the interfaces and harnesses that take models into production. They then own the engineering and infrastructure of every ML and AI system shipped into production, from reliability and cost to scale. Together, this collaborative team reduces toil and delivers reliable, intelligent experiences for small businesses. The team is currently working on - Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production. - JAX (Just Ask Xero): Powering Xero's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences. - Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks. - XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across Xero’s products and supporting reliable, reusable agentic experiences at scale. - End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work.   Where and how you can work Xero offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively. Here are some of the things we are looking for - A track record of designing, shipping and operating production-grade backend systems at scale - Experience building and operating production systems for LLM or agentic workloads (orchestration, tool use, evaluation, guardrails, latency and cost management) - Strong system design fundamentals and excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript) - Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs - Experience running services in production, including on-call and incident response - Solid SQL and experience with large-scale data processing - Excellent communication, with the ability to explain complex technical concepts to business and technical audiences - A coaching mindset and the ability to set engineering standards and mentor other engineers Nice to have - Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines) - Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools - Distributed processing experience (Spark, Dask)   Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: AU: Sydney (45 Clarence St); AU: Melbourne: (260 Burwood Rd) Workplace: Hybrid The role You will design, build and own the production systems behind Xero’s AI features: the services, pipelines and infrastructure that power LLM-driven and agentic experiences for millions of small businesses every day. This is a software engineering role. You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship. You don’t need a machine learning background. We’re looking for strong production engineers, ideally with experience building LLM or agentic systems, and ML depth can be learned on the team. Beyond architecture, you’ll lift engineering capability across AI Products by setting standards, mentoring engineers and partnering across Xero to make data usable and systems dependable.   The team You’ll join AI Products, a diverse, globally distributed team of scientists, engineers, product managers and analysts within our broader Data & AI business. Engineers here partner closely with Applied Scientists early on to build the interfaces and harnesses that take models into production. They then own the engineering and infrastructure of every ML and AI system shipped into production, from reliability and cost to scale. Together, this collaborative team reduces toil and delivers reliable, intelligent experiences for small businesses. The team is currently working on - Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production. - JAX (Just Ask Xero): Powering Xero's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences. - Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks. - XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across Xero’s products and supporting reliable, reusable agentic experiences at scale. - End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work.   Where and how you can work Xero offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively. Here are some of the things we are looking for - A track record of designing, shipping and operating production-grade backend systems at scale - Experience building and operating production systems for LLM or agentic workloads (orchestration, tool use, evaluation, guardrails, latency and cost management) - Strong system design fundamentals and excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript) - Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs - Experience running services in production, including on-call and incident response - Solid SQL and experience with large-scale data processing - Excellent communication, with the ability to explain complex technical concepts to business and technical audiences - A coaching mindset and the ability to set engineering standards and mentor other engineers Nice to have - Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines) - Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools - Distributed processing experience (Spark, Dask)   Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: Canada What the Role Is We’re hiring a Staff Software Engineer who’ll be the technical lead for a new Search team at Babylist. This new team will be focused on moving Babylist’s search capability in-house, making our search results more relevant and personalized, and partnering with other teams to transform search in the product from functional to delightful. 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 search and personalization problems in consumer e-commerce. This is zero-to-one work, with big ambitions. You’d build a search capability from the ground up, with a clear mandate from leadership to do it. In your first year, we expect to have rebuilt search to be highly relevant and personalized, and delivered big bets like universal search: one experience across items we sell and items from other retailers, and across products, guides and registries. We also want to work with Addie, our AI registry assistant, to have LLMs play a role in the search experience. If you want to tune an established search system, this isn’t the right role. If you’ve worked inside a strong search team and want to build a new system from scratch at a company earlier in that journey, read on. What You'll Own A Staff Engineer at Babylist sets direction. You’ll be the technical lead for search: you decide where it goes over the next year or two, sequence the bets that get there, and make the technical and product calls along the way. You’re still in the code and will drive initiatives forward across multiple teams. You’ll have software engineering and machine learning engineering support on the team. A few examples of initiatives you’d drive on the Search team: Build search in-house. Choose the architecture for indexing, retrieval and serving, and plan a seamless migration. The system you design replaces what we use today and is the foundation for everything below. Define what a good result is. Decide how we measure result quality, then improve it through query understanding, ranking and the behavioral signals we collect. Unify search across everything we show. One experience across items we sell and items from other retailers, and across products, guides and registries, including how to rank items we don’t sell next to ones we do. Decide how search and recommendations fit together. Bring what we know about a user and their registry into results, and decide how much retrieval and ranking search shares with our recommendation models. Make search conversational. Work with the Addie team, our AI registry assistant, on queries like “best stroller for urban family,” where the shopper describes a need instead of naming a product. Like every Staff Engineer here, you will: Take a fuzzy business problem from the first sketch through to production, and stay on the hook for whether it actually helped customers. Build the platform or tooling other teams adopt by choice, and own it as it scales. Set the standard for how search builds with AI. Decide what good looks like, build the patterns and evals that get agents there and catch the output that's confidently wrong before it ships. Partner with product, design and data as a peer, shaping what's worth building from the start. Coach Senior engineers through the hard calls, the ambiguous ones as much as the technical ones Who You Are You meet the Staff bar at Babylist. You’ve shipped production systems for enough years to have earned strong opinions, and you hold them loosely. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. You’ve already changed how a team builds with AI, and the new way stuck. On top of that, you’ve worked on search problems before, ideally in an e-commerce setting. This role needs depth in the systems behind search and a clear focus on the people using it. You bring: Hands-on search experience: building and running search in production, including indexing, retrieval, ranking and query understanding. You know how to keep a search service fast, relevant and reliable as traffic and catalog size grow. Experience evaluating search quality: offline and online, including relevance judgments and A/B tests. A focus on the user: you use query data, behavior and judgment about result quality to decide what to build, and you can connect a search change to what shoppers do, and to conversion or revenue. Comfort building from zero: you can define the problem, design the system and own it end to end. You measure yourself by impact: a customer outcome, or a system a dozen teams come to depend on. 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 an RRSP 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. 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: Санкт-Петербург Workplace: гибкий Крупнейший российский видеосервис: ежедневно им пользуются десятки миллионов людей. Перед нами стоит амбициозная задача — развивать видеосервис № 1 в России и внедрять новые технологии. Задачи Разработка и оптимизация Android-приложений с использованием Java/Kotlin Работа с видеотехнологиями: обработка видео, кодирование/декодирование, трансляции, стриминг Оптимизация производительности мультимедийных компонентов и управление ресурсами Взаимодействие с командами backend и QA для обеспечения качества продукта Проектировании архитектуры мультимедийных решений Анализ и устранение багов, профилирование кода Дизайн и верификация метрик и статистики Требования Уверенные знания Android SDK, Java и (или) Kotlin Умение строить, верифицировать, доказывать и опровергать гипотезы безопасно для продукта Декомпозиция, планирование и исполнение сложных задач Сильные навыки проектирования библиотек для мобильных платформ: поддержка обратной совместимости, наблюдаемости, версионирования, отказоустойчивости и так далее Развитие крупных сегментов функциональности в самостоятельном режиме: выбор ориентированного на бизнес направления развития компонента Будет плюсом Глубокие знания видеотехнологий: кодеки (H.264, H.265), форматы видео, протоколы потоковой передачи (RTMP, WebRTC и тому подобное) Опыт работы с мультимедийными библиотеками (FFmpeg, OpenGL, Vulkan или аналогичными) Навыки оптимизации производительности и работы с мультимедийными потоками Знание систем сборки (Gradle, CMake) и отладки нативного кода Опыт работы с live streaming и broadcast решениями

Location: Remote (Canada) Workplace: Remote BUILD SOMETHING PEOPLE LOVE Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $169 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada. We're proud of what we've built — and we're just getting started. Read our Culture Manual https://www.wealthsimple.com/en-ca/culture and learn more about how we work https://www.wealthsimple.com/en-ca/careers. ABOUT THE TEAM People Intelligence sits within People and Communications. We build the data and products behind talent decisions at every level — from leaders, managers, and employees. Our partners in Total Rewards, HRBP, Talent Management, and People Operations depend on what we ship..The team is a growing team, and you will help set the engineering standard for how we build. IN THIS ROLE, YOU'LL HAVE THE OPPORTUNITY TO: - Lead technical projects from first design through launch and iteration, across products such as performance cycles, compensation planning, talent reviews, total rewards statements, and self-service tools. - Design scalable architectures that integrate with our internal systems (i.e. Workday, Ashby, etc.) and our people data platform, that holds up when the whole company is in a review or compensation cycle. - Build with security in mind from the first commit, including role and reporting-line access, protection for compensation and performance data, and an audit trail on every change. - Work directly with Total Rewards, HR business partners, Talent Management, and People Operations to understand how each program runs, transforming it into products that managers and employees want to use. - AI is native to you, and speeds up how you design, build, and test, to help the team adopt the workflows that hold up. - Raise the technical bar through design reviews, code review, documentation, and mentorship. SKILLS YOU BRING: - 5+ years of professional software development, with a track record of building internal tools and production systems that employees and teams depend on every day. - Full-stack experience building web applications, with depth in at least one of Ruby, Python, TypeScript, or Kotlin, and a modern frontend framework such as React. - Experience designing systems that handle sensitive data, including authentication, fine-grained authorization, and auditability. - Clear communication with non-technical partners, and the product judgment to simplify a complex process rather than rebuild. - Experience taking a product from 0 to 1, including making architectural calls with incomplete information and revisiting them as you learn. NICE-TO-HAVE'S: - Experience building HR or people products, such as performance management, compensation planning, talent management, or employee self-service. We value this domain depth highly. - Experience integrating with an HRIS such as Workday, including its APIs and effective-dated data and other HR related systems (i.e. Ashby, Lever, Shareworks, Okta, etc.) - Familiarity with how people programs run, including review and calibration cycles, compensation bands and merit planning, and job architecture. - Experience in a regulated or privacy-sensitive environment. WHO YOU ARE: - You are self-directed, and you find the next problem worth solving without waiting for a ticket. - You are curious about how things work, and you ask why a process exists before you change it. - You treat employee data with care and think about privacy and access as design constraints from the start. - You would rather ship a simple version, learn from real users, and improve it than hold back a perfect one. - You own outcomes, not just code, and you stay with a product after it launches. - You make the people around you better through pairing, reviews, and clear writing. WHY WEALTHSIMPLE? 🌸 Top-tier health benefits and life insurance 📈 Long-term group savings with employer match, through Wealthsimple for Business 🌴 20 vacation days, 4 wellness days, and unlimited sick and mental health days per year* ✈️ 90 days away: work outside Canada for up to 90 days per year* 👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS 🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work. *Unlimited paid sick days, Wellness Days and the 90 day away program do not apply to certain roles. ICYMI Technology & Innovation at Wealthsimple: We move quickly and build thoughtfully. That means we're always looking for better ways to work — whether that's new tools, AI, or rethinking how we approach a problem. We don't expect you to have all the answers, but we do expect curiosity and a willingness to evolve alongside the products we're building. Inclusion Statement: We're building products for a diverse world, and we need a diverse team to do it well. We strongly encourage applications from everyone, regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status. Accessibility Statement: We're committed to an accessible hiring experience. If you need any accommodations throughout the interview process, please let us know — we'll work with you to make sure you have what you need. We also welcome any feedback on how we can better accommodate candidates with accessibility needs. AI in Hiring: We may use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our team but don't replace human judgment – all final hiring decisions are made by people. If you have questions about how your data is used, reach out to us.