Задачи:
— Координация стратегических и тактических инициатив;
— Коммуникация с проектной группой заказчика и взаимодействие с командой;
— Мониторинг и анализ производительности маркетинговых инструментов;
— Отчетность и аналитика;
— Обновление стратегий и планов проекта;
— Бюджетирование и планирование;
— Анализ рынка и конкурентов;
— Постановка задач проектной команде.
Требования:
— Опыт работы на позиции Digital/Performance Marketing Manager в агентстве от 2х лет;
— Владение английским языком на уровне В2 и выше — обязательно;
— Умение работать со стратегией и проектами;
— Знание, как выстраивать рабочие процессы на проектах;
— Опыт разработки целевых сообщений для рекламных кампаний;
— Умение грамотно работать с визуальной частью креативов;
— Знание: GA4 + GTM, CAPI и Серверное отслеживание, Google ads, Meta ads и других рекламных платформ — будет преимуществом;
— Опыт применения нейросетей, включая MCP рекламных систем, а также генерацию статистических, видео- и визуальных материалов — будет плюсом.
Условия:
— Белая заработная плата, которая зависит от пожеланий, скиллов и опыта;
— Годовой бонус по результатам работы;
— Оплачиваемый отпуск, подарки для сотрудников и их детей;
— Формат работы - офис;
— Рабочее место оборудовано современной техникой с учетом Ваших пожеланий;
— Гибкое начало рабочего дня;
— Корпоративное питание: завтраки и обеды;
— 4 day-off в год за счет компании;
— Отсутствие бюрократии, вопросы решаются оперативно, без многочисленных согласований;
— Частичная компенсация занятий по английскому языку;
— Наличие большого количества задач, которые дают возможность материального и профессионального роста;
— Поездки на ИТ-конференции, митапы, учебные курсы за счет компании;
— Реферальная программа за успешную рекомендацию.
ОфисКипр; Команда международного маркетингового агентства находится в поисках Digital Marketing Manager
Задачи:
— Работа с семантикой для крупных сайтов, структура, техническая оптимизация, внутренняя перелинковка, индексация.
— Создание и продвижение ревьюшников (рейтинги / обзорные сайты) белыми и агрессивными методами.
— Создание монобрендов для забирания брендового трафика конкурентов.
— Аутрич и линкбилдинг: поиск площадок, договоры, фильтрация мусора.
— Работа со ссылочным на потоке: аутрич, PBN, link insertions, понимание эффективности.
— Текстовая оптимизация: ТЗ копирайтерам, работа с интентом, доводка страниц до топа.
— Аналитика и аудиты: выявление причин отсутствия роста сайта и объяснение действий.
— Работа с Claude: понимание MCP и API, самостоятельная генерация и деплой сайтов, вайб-кодинг.
— Автоматизация задач самостоятельно, без ожидания программиста.
— Подготовка коротких, по делу отчётов с цифрами и выводами.
Требования:
— Опыт в аффилиатном SEO от 3-4 лет с реальными кейсами роста.
— Опыт продвижения ревьюшников в конкурентных нишах.
— Английский B2+ обязательно; знание ES/FR/DE/IT/PT будет плюсом.
— Энтузиазм, интерес к работе Google, следить за апдейтами и тестировать гипотезы.
— Высокая трудоспособность, умение работать с большой сетью сайтов и ключей.
— Самостоятельность, ответственность, умение предлагать и реализовывать решения.
— Умение работать в конкурентной нише, не бояться серых методов там, где уместно, и держать критически важные активы в белой зоне.
Условия:
— Полная удалёнка, гибкий график, важен результат, а не часы онлайн.
— Часовой пояс +- 3 от CET.
— Прямая работа с руководителем Олегом Шестаковым.
— Бюджеты на ссылки, инструменты и эксперименты без необходимости выпрашивать.
— Неограниченные ссылочные ресурсы вне аутрича и ресурсы по виральному трафику.
— Подписки на Claude и SEO-инструменты за счёт компании.
— Зарплата от $2000 на руки плюс бонус за результат, финальная сумма по итогам собеседования и уровня кандидата.
Задачи:
— Работа с семантикой для крупных сайтов, структура, техническая оптимизация, внутренняя перелинковка, индексация.
— Создание и продвижение ревьюшников (рейтинги / обзорные сайты) белыми и агрессивными методами.
— Создание монобрендов для забирания брендового трафика конкурентов.
— Аутрич и линкбилдинг: поиск площадок, договоры, фильтрация мусора.
— Работа со ссылочным на потоке: аутрич, PBN, link insertions, понимание эффективности.
— Текстовая оптимизация: ТЗ копирайтерам, работа с интентом, доводка страниц до топа.
— Аналитика и аудиты: выявление причин отсутствия роста сайта и объяснение действий.
— Работа с Claude: понимание MCP и API, самостоятельная генерация и деплой сайтов, вайб-кодинг.
— Автоматизация под свои задачи без ожидания программиста.
— Подготовка коротких, по делу отчётов с цифрами и выводами.
Требования:
— Опыт в аффилиатном SEO от 3-4 лет с реальными кейсами роста.
— Опыт продвижения ревьюшников в конкурентных нишах.
— Английский B2+ обязательно; знание ES/FR/DE/IT/PT будет плюсом.
— Энтузиазм, интерес к работе Google, самостоятельное тестирование гипотез.
— Высокая трудоспособность, умение работать с большой сетью сайтов и ключевых слов.
— Самостоятельность, ответственность, умение предлагать и реализовывать решения.
— Умение работать в конкурентной нише, использование серых методов там, где уместно, с сохранением белой зоны.
Условия:
— Полная удалёнка, гибкий график, важен результат.
— Часовой пояс +- 3 от CET.
— Прямая работа с руководителем Олегом Шестаковым.
— Бюджеты на ссылки, инструменты и эксперименты без необходимости выпрашивать.
— Неограниченные ссылочные ресурсы вне аутрича и ресурсы по виральному трафику.
— Подписки на Claude и SEO-инструменты за счёт компании.
— Зарплата от $2000 на руки плюс бонус за результат, финальная сумма по итогам собеседования и уровня кандидата.
УдалённоseniorГеография найма не уточнена
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Location: Brisbane, Australia
VALD
is the world leader in technology for the allied health industry, providing innovative human-measurement technology to over 10,000 clients in over 100 countries. If you have a favorite team in the NBA, EPL, or NFL, there's a good chance they use VALD Technologies.
Years on from its humble beginnings in Brisbane, Australia, VALD has grown to a team of over 300 team members in over 30 countries, with five offices across four continents.
Driven by a multidisciplinary team of researchers, clinicians, sports scientists, designers, developers and engineers, VALD’s suite of systems offer unparalleled insight into human movement, performance, injury risk and rehabilitation.
About the role
VALD is building the world’s largest musculoskeletal database, with over two billion data points and counting. Using this data, we can help practitioners to objectively assess patients’ progress and make more accurate, data-informed treatment decisions. We are looking for someone who has hybrid experience in data engineering and data analysis to help shape the future of the VALD Data Lakehouse.
In this role, you will
Build agentic capabilities:
design and ship production agent workflows, including orchestration, tool calling, MCP servers, skills and context management.
Ground AI in data:
build retrieval, search and data-querying capabilities across our data platforms, including Snowflake Cortex and Databricks.
Own quality in production:
design and evolve evaluation, monitor quality, feedback, cost and latency, and make improvements to accuracy and robustness
Build in safety and security:
implement guardrails that keep responses within agreed scope, and ensure each customer's data and context stay securely isolated.
Ship through automation:
deploy AI components through version-controlled pipelines, promoted consistently across environments and regions.
Integrate across teams:
work with data engineering, platform and deployment teams to bring AI capabilities into the VALD product suite.
Shape what gets built:
influence architecture and product decisions, and proactively find ways to improve robustness.
Is this you?
This is a hands-on engineering role for builders, not a research or manual testing position. You don't need every tool on this page. We'd rather hear about one difficult AI system you've built to solve a business problem and maintained in operation, rather than a long list of technologies you've used. We're chasing:
Strong software engineering skills
in modern languages, with the depth to own what you build through deployment and operation.
A record of shipping
LLM-powered or agentic products through to production.
Hands-on experience evaluating AI systems
and using the results to drive decisions.
Practical experience
with retrieval, tool use and agent design.
A clear communicator
who can explain trade-offs to non-technical stakeholders.
Beneficial experience:
Azure
MCPs
AI in health and regulated environments
Why VALD?
You will be working in a fast-paced, dynamic company that has a culture around the belief that anything is possible with hard work, creativity, dedication, and good timing.
We have a range of benefits we offer to our team, such as:
The opportunity to work in a company that is redefining allied healthcare.
Working with a range of high-performing individuals and teams across a range of disciplines.
Working with contemporary tooling on industry first applications.
Casual work attire.
Chefs that prepare you delicious fresh breakfast and lunch.
An on-site barista to make your coffee just as you like it.
A team gym, masseuse, and access to physiotherapy and exercise physiology services.
Diversity & Inclusion Commitment
VALD’s best asset is not our technology but our people and culture. A culture of inclusion and diversity is critical to our business. We know diverse teams perform better. It's not a separate initiative – we aim to embed inclusion and diversity in everything we do. We are committed to fostering an inclusive work environment and embracing diversity, including gender, nationality, disability, age, marital/parental status, ethnicity, gender identity, socioeconomic background and sexual orientation. We welcome applications from people from all backgrounds.
Apply now
We can't wait to meet you and discuss what a career with VALD could look like for you!
Successful applicants will be subject to background checks (including identity and criminal record checks). It will be a condition of employment that the background checks return acceptable results.
Salary: Up to $200,000 / year
Задачи:
— развитие плагинов и кодовой базы для VSCode и Theia
— разработка дополнительных инструментов (CLI, MCP, web back+front, и т.п.)
— интеграция Искусственного Интеллекта, разработка ИИ-агентов
— участие в планировании релизов, декомпозиции задач, контроле результата
— работа с командой: помощь коллегам, онбординг новых специалистов, и так далее
— создание и сопровождение дистрибутива продукта.
Требования:
— умение грамотно пользоваться TypeScript и его экосистемой
— опыт разработки веб-бэкенда или десктопных приложений на JS/TS
— опыт разработки веб-фронта на одном из современных фреймворков для JS/TS
— готовность изучать и использовать другие языки и технологии (Rust, Python, Go)
— умение работать с Git, инструментами CI/CD, терминальными утилитами
— умение работать как с использованием ИИ, так и без него.
Будет существенным плюсом:
— умение работать в режиме исследования (R&D), с высокой неопределенностью
— опыт в разработке IDE или плагинов для IDE (любая платформа – VSCode, IDEA, Zed…)
— опыт в разработке ИИ инструментов (харнессы, агенты, модели, и т.п.)
— опыт в разработке инструментов для разработчиков (компиляторы, отладчики, и т.п.)
— опыт использования разных языков (Rust, Python, Go).
Условия:
— годовой бонус и ежегодный пересмотр зарплаты
— расширенный ДМС с первого дня, страхование жизни, корпоративная пенсионная программа
— статус аккредитованной ИТ-компании со всеми преимуществами
— льготная ипотека для сотрудников, подписка Прайм с возможностью шеринга (совместного использования) на трёх близких, скидки от партнеров и сервисов группы компаний
— корпоративный университет Сбера, внутренняя образовательная платформа, участие в IT-конференциях
— 90 дней удаленной работы из любого региона РФ
— реферальная программа (бонус до 100 000 рублей).
seniorВажной особенностью работы является то, что любой плагин для IDE состоит не только из чистой логики, но имеет визуальный интерфейс
Location: Toronto, Ontario, Canada
Workplace: Hybrid
ABOUT SENTRY
Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building.
Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future.
ABOUT THE ROLE
At Sentry, Support is an engineering discipline. Our customers are the greatest technical minds in the world—developers at elite enterprises building the future of software—and they deserve answers that go deeper than a knowledge base link.
We are architecting the Technical Support engine. We’re looking for a veteran engineer to help us redefine the standard of technical support by combining deep human expertise with autonomous agentic systems. You are a debugger of both code and systems. You will treat support volume as a data signal to build automated resolution paths, ensuring our human engineers only touch the most complex, high-impact architectural puzzles.
Sentry Support Engineers aren't just clearing queues; they are Orchestrators. You will engage with our users across GitHub, Discord, and our internal systems, while acting as the Technical Lead for our Agentic Ops. You ensure that when a developer asks a complex question, our systems have the right context and a seamless "Human-in-the-Loop" path to you when deep, nuanced expertise is required.
IN THIS ROLE YOU WILL
Master the Sentry Ecosystem & Support Elite Developers
- Deep-Dive Debugging: Perform root-cause analysis on complex issues and distributed tracing gaps across polyglot environments.
- Support the Great Minds: Act as a strategic consultant for senior engineers at our largest enterprise customers, solving high-stakes architectural challenges that push the boundaries of observability.
- Troubleshoot SDK Implementations: Go deep into the source code of Sentry’s SDKs to help developers instrument complex frameworks and custom environments.
- Engineering Feedback Loop: Serve as the bridge between the world's best developers and our product teams, using data from your systems to prioritize high-impact platform fixes.
Engineer Agentic Operations (The Scaling Engine)
- Deterministic Support Paths: Engineer the logic that powers our support agents, moving beyond probabilistic guesses to high-fidelity, autonomous resolutions.
- Knowledge Engineering: Build the right context into our systems so they can resolve issues consistently and indefinitely.
- Agentic Tooling Development: Use MCP (Model Context Protocol) and Sentry’s internal APIs to build "skills" for our agents, allowing them to perform complex lookups or state-checks autonomously.
- The Seer Philosophy: We’ve already proven AI can handle autonomous production fixes with Seer. You will apply that same philosophy to the support lifecycle—moving us from a "Help Desk" to an "Autonomous Resolution Engine."
YOU’LL LOVE THIS JOB IF
- You love eliminating Non-scalable effort: you enjoy automating repetitive work and take pride in building systems that save time and effort.
- You’re a Full-Stack Troubleshooter: You enjoy jumping from a React frontend issue to a Python backend trace to a CI/CD pipeline failure in a single afternoon
- You Value Evidence-Based Support: You prefer looking at data trends over anecdotal evidence to decide where to build automation next.
- You’re a Developer Advocate: You want to guide the industry on how elite engineers and AI co-exist in a high-density technical ecosystem.
QUALIFICATIONS
- 5–8+ years of experience in technical support engineering, systems engineering, or software development, with a track record of solving high-complexity SaaS problems.
- Strong Coding Foundations: Mastery of Python, JavaScript, Java, or Ruby. You are comfortable reading SDK source code and identifying bugs in production-level repositories.
- Systems Depth: Deep understanding of distributed systems, microservices, APIs, and the "path of a pixel" from frontend to database.
- AI & Automation Literacy: Practical familiarity with LLM orchestration (RAG, context windows, system prompts) and a critical eye for where AI succeeds versus where it requires human intervention.
- Exceptional Communication: The ability to explain complex architectural concepts to a human and write precise "system instructions" for an AI.
BONUS QUALIFICATIONS
- Open Source Contributor: An active presence on GitHub or experience maintaining open-source libraries.
- Former Software Developer: You’ve spent time in the trenches as a full-time dev and know exactly what keeps our customers up at night.
The base salary range (or hourly wage range, if applicable) that Sentry reasonably expects to pay for this position is $125,000 to $150,000. A successful candidate’s actual base salary (or hourly wage) amount will be determined by a variety of relevant factors including, without limitation, the candidate’s work location, education, work and other relevant experience, skills, and job-related knowledge. A successful candidate will be eligible to participate in Sentry’s employee benefit plans/programs applicable to the candidate’s position (including incentive compensation, equity grants, paid time off, and group health insurance coverage). See Sentry Benefits https://sentry.io/careers/ for more details about the Company’s benefit plans/programs.
EQUAL OPPORTUNITY AT SENTRY
Sentry is committed to providing equal employment opportunities to its employees and candidates for employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other legally-protected characteristic. This commitment includes the provision of reasonable accommodations to employees and candidates for employment with physical or mental disabilities who require such accommodations in order to (a) perform the essential functions of their jobs, or (b) seek employment with Sentry. We strive to build a diverse team, with an inclusive culture where every teammate can thrive. Sentry is an open-source company because we believe that everyone, everywhere, should have the ability and tools to make great software. Software should be accessible. That starts with making our industry accessible.
If you need assistance or an accommodation due to a disability, you may contact us at accommodations@sentry.io.
Want to learn more about how Sentry handles applicant data? Get the details in our Applicant Privacy Policy https://sentry.io/careers/applicantprivacy/.
Location: Remote
Who we are
Our mission is to bring clarity and control to the world's most complex codebases. AI is accelerating code creation, but the infrastructure to understand, oversee, and evolve that code hasn't kept pace. Sourcegraph gives engineering organizations full visibility across their systems, precise context for their agents, and the ability to execute coordinated code changes at scale. As agentic development becomes the dominant engineering paradigm, we provide the context layer teams need to take control of their codebase.
With Code Search, Deep Search, MCP, and Agentic Batch Changes, we deliver on that mission today - giving engineering teams and their AI tools the cross-repo context to navigate massive codebases with confidence, and the ability to make changes across hundreds of repositories at once.
Companies like Stripe, Reddit, and Leidos rely on Sourcegraph to ship faster and with higher quality. We're backed by a16z, Sequoia, and Redpoint, and proud to operate as a globally distributed team that values high agency, direct communication, and customer love.
If you want to build the infrastructure that lets every engineering team - and every agent they deploy - operate on their codebase with confidence, join us.
Working hours
🌎 While we are an all-remote company and hire
almost anywhere
in the world, we do require successful candidates to be located in the United States.
Preferred location:
USA
Why this job is exciting
As an Enterprise Account Executive [IC5], you will have more responsibility, upside, and growth potential than anywhere else with a comparable role. At Sourcegraph, we strive to create the best environment for exceptionally talented people to thrive. If you join us, you’ll make a meaningful impact on how engineering organizations operate at scale.
Here’s what you can expect in your first year:
📅 Within one month, you will…
Begin 1:1’s with your manager, understand your 30-60-90 plan, shadow current team members, review your quota, and dive into your territory.
Build a territory plan targeting net-new logo accounts with a strong emphasis on outbound engagement and expanding existing customer relationships.
Start to hold new business meetings and build pipeline
Meet key partners across Customer Engineering, Technical Success, Product, Legal, and Engineering teams—relationships that will be critical throughout your deal cycles.
📅 Within three months, you will…
Be well versed in Sourcegraph’s Value Framework.
Understand the unique capabilities of Sourcegraph products and develop compelling strategies to align their value with your prospect’s engineering and business objectives.
Hone your storytelling skills, clearly articulating use cases, sharing real-world customer success stories, and conveying outcomes that matter to both technical and executive audiences.
Identify champions, influencers, and decision makers, building trusted advisor relationships that accelerate adoption across engineering organizations.
Execute a disciplined, repeatable sales process to continuously build and advance pipeline while maintaining accurate forecasting.
Negotiate complex enterprise proposals and contracts and surface market insights to the Product team to influence our roadmap.
Consistently hit your activity and pipeline goals.
📅 Within six months, you will…
Own the full sales cycle, consistently meeting and exceeding pipeline and revenue objectives.
Collaborate cross-functionally with Customer Engineering, Product, Legal, and Engineering to successfully close technically complex and strategically significant enterprise deals.
Deliver actionable customer feedback across teams, ensuring engineers and product teams remain tightly aligned with customer needs.
📅 Within one year, you will…
Be recognized as a top-performing Account Executive, consistently exceeding goals and setting the standard for excellence.
Mentor and support new Account Executives, assisting with onboarding, training, and motivation to elevate the entire team.
About you
You are a results-oriented, strategic hunter who thrives in enterprise environments and has a proven track record selling to developers and engineering leaders. You excel at uncovering needs through rigorous discovery, navigating complex multi-stakeholder deals, and building consensus across technical and executive audiences.
You are highly motivated, self-directed, and energized by creating new opportunities and expanding your footprint within accounts. You take ownership of your pipeline and performance, and you hold yourself accountable for achieving ambitious goals.
Your Skills and Experience:
7+ years of B2B SaaS or software sales experience
3+ years of selling as an Enterprise Account Executive
Proven track record of exceeding quotas while leading with empathy and credibility
Experience selling complex solutions with ASP ≥ $100k
Comfortable engaging with both individual contributors and VP/C-level executives
Exceptional interpersonal, presentation, verbal, and written communication skills across all levels and personas
Passion for our mission and belief in the transformative power of developer productivity
Nice to Haves:
Experience selling developer or engineering-focused products
Familiarity with software development concepts, CI/CD, version control, or DevOps tooling
Experience managing complex multi-year contracts
Knowledge of security, licensing, and compliance requirements
Vertical expertise in Financial Services, Insurance, Semiconductors, Auto-Manufacturing, or Retail.
Level
📊 This job is an IC5. You can read more about
our job leveling philosophy
in our Handbook.
Compensation
💸 We pay you an above-average salary because we want to hire the best people who are fully focused on helping Sourcegraph succeed, not worried about paying bills. As an
open and transparent
company that values
competitive compensation
, our compensation ranges are visible to every single Sourcegraph teammate. To determine your salary, we use a number of market and data-driven salary sources, along with your location zone, and target the high-end of the range to ensure we’re always paying above market regardless of where you live in the world.
💰The compensation for this role is outlined below:
IC5: $165,000 USD base + $165,000 USD variable ($330,000 USD on-target-earnings).
📈 In addition to our cash compensation, we offer equity (because when we succeed as a company, we want you to succeed, too) and generous
perks & benefits
.
Interview process
Below is the interview process you can expect for this role (you can read more about
the types of interviews
in our Handbook). It may look like a lot of steps, but rest assured that we move quickly and the steps are designed to help you get the information needed to determine if we’re the right fit for you… Interviewing is a two-way street, after all!
We expect the interview process to take 5 hours in total.
👋
Introduction Stage
- we have initial conversations to get to know you better…
[30 min]
Recruiter Screen
[30 min]
Hiring Manager screen
with Regional Sales Director
[60 min]
Resume Deep Dive
🧑💻
Team Interview Stage
- we then delve into your experience in more depth and introduce you to members of the team, including cross-functional partners…
[45 min]
Peer
with an Account Executive & Solutions Engineer
[45 min]
Sales Presentation
with RSD, Global Head of Sales, CRO
[30 min]
Values
🎉
Final Interview Stage
- we move you to our final round, where you gain a better understanding of our business and values holistically
[30 min]
Leadership
with Global Head of Sales
We check references and conduct your background check
Please note - you are welcome to request additional conversations with anyone you would like to meet, but didn’t get to meet during the interview process.
Learn more about us
You can learn more about what it is like to work at Sourcegraph by reading
our handbook
.
We are an ambitious team who are collectively working hard to build the most influential company in the world. You can read more about our
culture
,
competitive compensation
and
benefits
here.
Sourcegraph is an equal opportunity workplace; we welcome people from all backgrounds.
Sourcegraph participates in
E-Verify
for U.S. Employees.
Location: Remote - US
Sr. Developer Relations Manager
Backblaze — Remote, US
Compensation: $172,000–$215,000 base + equity
About Backblaze
Backblaze is the object storage layer for AI and data-intensive workloads, fueling customer success with cloud storage purpose-built for scalable performance and economics. We make customers unstoppable by solving their toughest storage challenges.
Today we manage nearly 6 billion gigabytes of data for 500K+ customers across 175+ countries with fast growth among Neoclouds, GenAI companies, and companies reliant on data–heavy workloads. Developers are at the center of our next chapter, and we're serious about earning their trust.
About the Role
Developer relations is evolving quickly. Coding agents, informed by reference architectures and machine-readable documentation, are increasingly making integration decisions on behalf of developers. And trust, transparency, and human interaction are more important than ever as open source ideals and corporate agendas are weirdly attacked, limited, or promoted by unexpected sources and trends.
Backblaze B2 Cloud storage was launched as a result of developer demand and has been committed to the developer ecosystem since day one. Today, we are seeking a leader who can help us become more present and trusted than ever before in this space, both as the storage default for agent-led projects and as a leading source of support, inspiration, and enablement for developers who need storage for whatever they’re building.
As Sr. Developer Relations Manager, you'll work across a strong set of existing assets — a mature docs team, an engineering team focused on AI ecosystem integrations, our Flamethrower Startup Program, a content org, and an outward-facing SE team — and coordinate their outputs into a coherent, credible developer presence that earns mindshare where it matters most.
This is a program-defining role for someone who thinks in systems, works backwards from adoption goals, knows how to make a company technically credible with developers who haven't heard of it yet, and is comfortable both channeling and being the face of developer relationships at Backblaze.
What You'll Own
Developer Presence in the Agentic Stack
The primary goal of this role is to ensure Backblaze B2 is the best storage layer for developers and for their agents. That means understanding how AI coders discover and evaluate infrastructure tools today: through MCP servers, coding agent contexts, reference architectures, SDKs, and machine-readable documentation. You'll work with the internal AI team to define what "agent-ready" means for Backblaze and drive execution against it across engineering, docs, and content.
Cross-Functional Coordination
This role starts as an individual contributor, but you'll have real influence over a strong set of resources: an engineering team building integrations into AI tooling (MLFlow, ComfyUI, Hugging Face, popular agent frameworks), a docs team that can be directed toward structured, agent-consumable formats, a content org that can amplify what you build, and an SE team that can extend your enablement work, among a number of others at the company. Your job is to coordinate these teams around a unified developer strategy, keep that strategy moving, and share its outputs with the broader world.
Community and Ecosystem
Developers trust other developers. You'll underscore Backblaze's credibility in the communities where AI builders live: GitHub, Discord, open source projects, developer events, and the growing ecosystem of AI infrastructure tooling. You'll elevate internal technical voices, use their expertise to build your own thought leadership in the space, and partner with ecosystem players, and show up in a way that is earned, not marketed. Critically, you should have a presence in this community before coming to the role.
Developer Feedback Loop
You'll maintain a tight feedback loop from the developer community back to product and engineering — surfacing adoption friction, unmet integration needs, and emerging patterns worth prioritizing. The Flamethrower Startup Program gives you direct access to early-stage builders who can serve as signal-rich canaries for what's working and what isn't.
Metrics and Program Accountability
You'll define what success looks like — developer signups, activation rates, B2 adoption in AI frameworks, community engagement, content reach — and own progress against it. We're building this program to drive real revenue, and you'll be expected to connect the dots between awareness and conversion. Success in this role opens the door to bringing on, or from elsewhere in the company, developer resources to grow the program.
What We're Looking For
Meaningful DevRel, developer marketing, or developer experience leadership at a cloud infrastructure, open source, or AI tooling company. You've built or significantly grown a developer program, not just contributed to one.
Understand how agentic workflows are reshaping how developers discover and integrate infrastructure tools — and you have opinions about what that means for DevRel strategy.
Technically credible. You can read a codebase, evaluate an SDK, write a working integration, and have a real conversation with an engineer about tradeoffs. You don't need to be a full-time SWE, but you need to have been one, or close to it.
Worked, or started, without a large team. You know how to amplify yourself through cross-functional relationships, external partners, and community rather than headcount.
Strong communicator — to developers externally and to leadership internally. You can write a crisp technical tutorial and a clear exec summary with equal ease.
Existing presence in developer communities. A following, conference talks, open source contributions, a technical blog — some signal that developers pay attention when you show up.
Strong plus:
Direct experience with model training, data processing or generative media
Familiarity with how coding agents (Claude Code, Cursor, Copilot, etc.) surface and recommend infrastructure tools
Experience working with or building on top of open source frameworks in the AI/ML ecosystem (MLflow, DVC, Ray Data, WebDataset, and MosaicML Streaming)
Prior experience running or contributing to a startup/developer program (accelerator, cohort model, or similar)
What You'll Have to Work With
You won't be starting from scratch. You'll work closely with:
A mature, capable
docs team
that can be directed toward agent-consumable documentation formats and structured reference content
A strong
engineering team
dedicated to integrating Backblaze into the AI tooling ecosystem — building connectors, working on external integrations, and driving internal product improvements for developer use cases
Flamethrower
, our startup program, which is already generating community energy and early-adopter signal among AI builders
An outward-facing
solutions engineering team
that can extend your enablement work with hands-on technical support
A
content org
that can help produce and amplify developer-facing assets
Active strategic work from
Rawkode Academy
laying the DevRel foundation: audit, persona validation, content models, and engagement strategy
Why This Matters Now
Developers are making storage decisions earlier in the stack than ever before — often before they've spoken to a salesperson, often through a coding agent recommending a reference architecture. Backblaze has the right product, the right price point, and a growing engineering investment behind this motion. What we need is the person who can translate that into developer conviction at scale.
The window to establish Backblaze as the default AI storage layer is open now. This role exists to make sure we don't miss it.
Backblaze Perks
Healthcare for family, including dental and vision
Competitive compensation and 401K
RSU grants for full-time employees
ESPP program
Flexible vacation policy
Maternity & paternity leave
MacBook Pro plus a generous workstation stipend
Childcare bonus
Fertility treatment and support
Learning & development program
Commuter benefits
Culture that supports a healthy work-life balance
Pay Transparency
To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. Final offer amounts are determined by multiple factors including candidate location, skills, depth of work experience, and relevant licenses/credentials.
The expected salary range for this role is $172,000 - $215,000 plus 20% target annual bonus and RSUs.
At Backblaze, we value being fair and good to our customers, partners, and employees. Diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We are proud to be an Equal Opportunity Employer.
Backblaze is proud to be an Equal Opportunity Employer. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education.
Location: Paris
Workplace: Hybrid
ABOUT VOODOO
Voodoo is a consumer tech company founded in Paris in 2013, with one mission: entertain the world. Today we are 1,000 people, generating $1b+ in annual revenue, profitably. Our games and apps have passed 7 billion downloads and reach 200 million+ active users every month, making Voodoo the #3 mobile publisher worldwide in downloads, after Google and Meta. We were backed by Goldman Sachs, Tencent and GBL along the way.
TEAM
Our Corporate teams support the company's performance and growth whilst putting people at the core of everything they do. As a French tech leader and global successful company, our Corporate teams are constantly looking for ways to innovate and increase organisation efficiency to keep Voodoo ahead of the market. Voodoo's Corporate function is composed of three teams: HR, Legal and Finance, working together to drive Voodoo's success.
As Voodoo continues to grow, we are transforming the way Finance uses data and technology. Our ambition is to move from fragmented, spreadsheet-heavy workflows to a modern, reliable, and increasingly automated Finance data platform.
ROLE
We're looking for a Finance Data Engineer to join our Corporate team. In this role, you'll own the technical transformation of Finance by building the data foundations, pipelines, and internal tools that enable Finance teams to operate more efficiently and make better decisions.
Reporting to the CFO, you will work closely with Finance stakeholders and Voodoo's central Data team, combining data engineering, business understanding, and product thinking to turn complex Finance needs into reliable and maintainable solutions.
- Define and drive the roadmap for Finance data, automation, and internal tooling
- Build and progressively scale Voodoo's Finance data platform, prioritising the use cases that create the greatest business value
- Migrate critical data transformations and workflows from spreadsheets and legacy tools to tested, documented, code-based solutions
- Create reliable data models and pipelines for Finance reporting, analysis, forecasting, and operational processes
- Establish strong standards for data quality, observability, documentation, security, and access management
- Partner closely with Accounting, FP&A, Controlling, Treasury, and other Finance stakeholders to translate their needs into scalable technical solutions
- Collaborate regularly with Voodoo's Data leadership and engineering teams to align on architecture, tooling, and best practices
- Build intuitive dashboards and internal applications that allow Finance teams to explore data and manage workflows independently
- Identify AI and automation opportunities, take them from prototype to production, and measure the value they create
- Help Finance teams adopt data and AI tools effectively through documentation, training, and day-to-day support
PROFILE
- Significant experience in data engineering, analytics engineering, or a closely related role, including ownership of production-grade data solutions
- Proven track record of building or substantially improving a modern data platform or analytics stack
- Highly proficient in SQL and comfortable building production systems in Python
- Strong software-engineering practices applied to data work: testing, version control, code review, documentation, and monitoring
- Solid understanding of core corporate Finance and accounting concepts; familiarity with French accounting principles is a strong advantage
- Ability to translate ambiguous business needs into clear, pragmatic technical solutions
- Comfortable working autonomously, prioritising competing needs, and delivering value incrementally
- Strong communication skills with both technical and non-technical stakeholders, in French and English
- Curious about the evolving data and AI ecosystem — you test new approaches on real problems and form your own point of view
- Rigorous, detail-oriented, and focused on measurable outcomes; pragmatic in technology choices, knowing when to build, adopt open-source, or buy commercial solutions
Nice to have:
- Experience building tools or data products for Finance teams
- Experience deploying AI agents or AI-enabled workflows into production
- Familiarity with the mobile gaming, consumer apps, advertising, or digital analytics ecosystem
- Experience operating data infrastructure on AWS
OUR STACK
- Cloud: AWS
- Languages: Python, SQL, Scala
- Transformation & orchestration: dbt, Airflow, Spark
- Query engines: Athena, StarRocks
- Infrastructure: Terraform, Kubernetes
- Internal applications: Streamlit
- AI-assisted development: Claude Code, MCP-based internal tooling
BENEFITS
- Competitive salary based on experience
- Swile Lunch voucher
- Gymlib (100% covered by Voodoo)
- Premium healthcare coverage with SideCare, 100% covered for you and your family
- Wellness activities in our Paris office
- Remote Fridays
Location: Yerevan, Armenia
Problem Space
Logistics operations today are still largely:
manual
reactive
fragmented across tools
running on incomplete or late data
full of conflicting constraints
under real-time decision pressure
driven by evolving business rules
a mix of legacy and new systems
Much of this is unstructured: emails, documents, free-text updates, exceptions nobody modelled. That is where AI changes the game.
We’re building a system that:
ingests real-time operational data, structured and unstructured
supports planning and execution decisions, with AI agents that act where it’s safe and hand over to humans where it isn’t
adapts to constantly changing constraints
What You’ll Work On
AI in production.
Building LLM- and agent-powered features into production .NET services: tool calling, structured outputs, retrieval over operational data, document and message understanding.
The seams.
Designing the boundaries between deterministic business logic and probabilistic AI: validation, fallbacks, human-in-the-loop.
Trust.
Making AI measurable and trustworthy: evals, test sets, observability, guardrails and cost/latency budgets.
Ownership.
Owning features end to end, from problem framing with product to running them in production.
Design Principles
keep things simple before scalable
prefer explicit logic over magic abstractions, and that includes AI: deterministic where you can, model where you must
optimize for change, not perfection (models, prompts and providers will change)
measure AI behaviour, don’t trust vibes
avoid “framework-driven architecture”
accept that some parts will be ugly, temporarily
Tech Stack
.NET · Vue.js · service-oriented architecture · relational + operational data storage · cloud-based infrastructure · LLM APIs and agent tooling (e.g. Semantic Kernel / Microsoft.Extensions.AI, MCP) · vector/semantic search · eval and tracing tools
How We Build
AI-native development is the default. You use coding agents (e.g. Claude Code, Copilot) every day.
You own what you ship, whoever typed it: you review AI-generated code critically, test it and understand it.
What We Expect
Strong, senior-level .NET engineering
Ability to navigate uncertainty and work in ambiguity
Willingness to challenge decisions
Focus on outcomes, not just code
Understanding of trade-offs and complex systems, including when not to use AI
Preferring ownership over comfort
Strong Plus
Having shipped LLM/AI features to production and kept them running
Experience with evals, prompt/version management or AI observability
Python for prototyping and data work
Logistics or other real-time operations domain experience
What You Won’t Find Here
over-engineering everything upfront
unnecessary microservices
“clean architecture” for the sake of it
process-heavy development
AI demos that never reach production
wrapping a chatbot around a problem and calling it solved
Location: Remote
Workplace: Remote
About Prefect
Prefect builds automation for an unpredictable world. The last decade of automation was about protecting workflows from unpredictability; in the agentic era, unpredictability is the point. Our mission is to give people confidence in automated work, whether that work is a mission-critical data pipeline or a fleet of AI agents.
In August 2026, Prefect and Dagster, competitors for eight years, joined forces to build the next generation of automation infrastructure. Today, our ecosystem includes Dagster, the data platform; Prefect, the agent platform; and FastMCP, the leading open-source developer framework for the MCP ecosystem. Together, our open-source and commercial products are trusted by Fortune 500 companies, data innovators, and high-growth technology companies around the world.
We think of our culture as the operating system of the company. We’ve carefully created a supportive, high-performance environment that empowers our team to do the best work of their careers, have meaningful impact, and continue growing personally and professionally. We’re a remote-first team that values high standards, ownership, and thoughtful collaboration.
ROLE SUMMARY
Developer Success is the technical support function for Prefect's customers across the Prefect and Dagster product lines. Its mission is to resolve customer technical issues with the least possible customer effort, and to prevent those issues from recurring.
We are hiring a Developer Success Engineer to work the combined Prefect and Dagster support queue. You will diagnose and resolve technical issues in customer environments, own each issue through resolution, and contribute to the documentation, tooling, and product feedback that reduce future volume. You will be trained on both Prefect’s and Dagster’s products.
The team is investing in agent-based automation for routine support work, which is moving the engineering focus toward complex diagnosis and escalation. This role is well suited to an engineer who wants to build deep expertise in orchestration and data platform environments and apply it directly with customers.
WHAT YOU'LL DO
- Clear the failure state, and prevent the next one. Diagnose problems across Prefect and Dagster installations, integrations, deployments, and the cloud and container environments they run in. Find the underlying "why" so your first response resolves the question and pre-empts the follow-ups. Turn what you learn into docs, debugging resources, and tooling that deflect repeat submissions.
- Own what's ours; say no clearly to what isn't. Take full accountability for root causes inside our products' domain of control. For problems outside our Scope of Support, issue a principled no that still gives the customer a way forward. Helplessness erodes trust as fast as a wrong answer.
- Support your findings, and ask customers to support theirs. Back every diagnosis with evidence and logic. Assume the customer is the expert on their own stack, ask for what you need to troubleshoot both sides of an issue, and explain why you need it. Leave room for the possibility you've missed something.
- Give the best possible update every time, and say so when you're still building it. A half-baked answer sent fast is worse than a complete one sent when it's ready; but radio silence is worse than both. When an issue needs to be escalated, you stay the customer's single point of contact, keep them updated on a regular cadence, and close the loop.
- Feed the product. File reproducible product issues and surface recurring failure patterns to Engineering and Product.
You'll work the queue independently on day-to-day issues and own moderate-complexity problems end to end, including investigations across a customer's cloud environment. You'll ask when the Scope of Support or an escalation path is unclear, and you'll build the judgment to recognize when an issue belongs with Customer Engineering or a CSM instead. We measure the role on Customer Effort Score and resolution time, held in tension: a fast answer that costs the customer effort isn't a good one.
Coverage is 9am to 5pm Pacific, with an on-call rotation shared across the team.
YOUR QUALIFICATIONS
Must have:
- Python fluency at the level of reading and debugging someone else's code, not only writing your own.
- Hands-on experience running workloads in at least one major cloud and in containers or Kubernetes, enough to troubleshoot a deployment you didn't build.
- Experience with a workflow orchestrator (Prefect, Dagster, Airflow, or comparable) and a strong interest in the data engineering space it lives in.
- A track record of technical, customer-facing work: support, solutions engineering, developer relations, or similar.
- Clear enough written communication to explain a root cause to a skeptical senior engineer and earn their trust.
Nice to have:
- Direct experience with Prefect or Dagster specifically.
- A history of open-source contribution, in any project.
- SQL and data warehouse familiarity.
- Experience building support tooling or automation.
WHAT TO EXPECT
This is a support role. There's a queue, a Scope of Support, and an on-call rotation, and the first job is always the failure state in front of you. If a defined scope and a real customer on the other end of every problem sounds like the point, this is the role. While engineers on this team do contribute code and take on consultative work, the queue comes first. Those opportunities will progressively open up as the agent tooling absorbs the formulaic work.
WHAT YOU'LL GET IN RETURN
Base Salary Ranges:
- San Francisco Bay Area & NYC Metro: $149,000–$176,000
- Washington D.C., Boston, LA Metro, Seattle: $136,000-$165,000
- Denver, Chicago, Atlanta, & all other U.S. metros: $128,000–$150,000
Actual base salary within each range depends on the candidate's location, experience, and qualifications. Please keep in mind that equity and benefits are not included in the range provided above. Your recruiter can share more about the salary range for your preferred location during the hiring process.
Perks and Benefits:
- Remote-first team with flexible-first culture
- Equity Stock Options
- 401(k) with 5% company match (vests immediately!)
- Unlimited PTO
- Medical, Dental and Vision insurance
- Generous Parental Leave
- Life Insurance and Disability benefits
- $800/month remote work stipend
And that's just the start — for more info check out our benefits and perks on our careers page.
BELONGINGNESS AT PREFECT:
Belongingness at Prefect is our commitment to ensuring mutual power, access, and opportunity among all groups and individuals who make up our community. We operationalize belongingness through actions large and small on a daily basis, but always with the goal that all groups and individuals can contribute as their most authentic self to the evolution of our product, our team, and our community.
Belongingness is also our commitment to bridge with individuals or groups not yet established in our community, acknowledge differences in a way that affirms distinct identities, and allows for a new, more expansive group identity to form.
EQUAL OPPORTUNITY AT PREFECT:
Prefect is an equal opportunity employer and encourages applications from people of all backgrounds. All applicants will be considered for employment without attention to race, religion, color, sex (including pregnancy, sexual orientation and gender identity/expression), national origin, disability or any other status protected under applicable federal, state, or local laws.
Delaney is a real live person (👋🏻) and is looking forward to learning more about you through your application.
Location: Kuala Lumpur, Malaysia
About Us
Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance.
Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution.
Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services.
About the Role
We are at an inflection point where AI is fundamentally reshaping what products can do and how users experience them. We're not just looking for a product manager — we're looking for a
hybrid product builder
who truly understands AI capabilities and can translate technical potential into real user value.
You will lead end-to-end product design for LLM / Agent-powered applications — from zero to one — across domains including intelligent customer service, personalized recommendations, AI assistants, and automated workflows. You are the critical connector between user insights, AI technical capabilities, and business objectives: someone who can discuss RAG retrieval strategies and multi-agent orchestration with ML engineers, while clearly articulating product value and delivery roadmaps to business stakeholders.
If you have genuine passion for AI-native products and the ability to define clear product direction amid ambiguity and rapid change, we'd love to build the next generation of AI applications together.
Key Responsibilities
End-to-End AI Product Lifecycle Management
Own the full product lifecycle of AI applications — including intelligent chatbots, AI assistants, recommendation systems, and automated workflows — from requirements definition and product design through to launch and delivery. Produce high-quality PRDs, interaction flow diagrams, and acceptance criteria while driving cross-functional teams to execute efficiently.
LLM / Agent Capability Productization
Deeply engage in Agent product design, including task planning workflows, tool-calling strategies (Function Calling / MCP), context management mechanisms, multi-agent orchestration logic, and graceful failure/fallback handling. Translate underlying model capabilities into meaningful, perceivable user value.
AI Evaluation Framework & Quality Standards
Build Harness evaluation frameworks for AI products — designing test scenario sets, evaluation metric systems (accuracy, hallucination rate, task completion rate, etc.), and regression test case libraries. Independently assess AI capability boundaries and drive continuous model iteration and product quality improvement.
Conversational Product Design & Knowledge Engineering
Lead platform architecture planning for intelligent customer service and conversational assistant products, covering knowledge base structure design, dialogue flow and SOP design, corpus annotation and training strategy, intelligent reply generation, and case summarization. Leverage large-scale data analysis to continuously optimize conversation quality and issue resolution rates.
Personalization Engines & Generative
UI
Products
Collaborate deeply with ML and data teams to design recommendation strategies that deliver truly personalized, individualized user experiences. Define generative UI product requirements and drive growth in core business metrics including CTR, conversion rate, and user retention. Establish comprehensive attribution analysis frameworks for recommendation effectiveness.
AI Capability Integration with Business Scenarios
Develop a thorough understanding of business goals and user pain points. Proactively identify opportunities to apply AI technologies — including RAG, Prompt Engineering, and multimodal capabilities — to concrete use cases. Define clear product evolution roadmaps that balance technical feasibility, user experience, and commercial value.
Cross-Functional Collaboration & AI-Native Product Culture
Act as the product Owner in close collaboration with algorithm, engineering, data, design, operations, and business teams. Maintain a strong sense of ownership in a fast-moving AI-native environment, continuously track industry developments, and rapidly translate emerging AI capabilities into product innovation opportunities.
Requirements
Product Experience
: 3+ years of product management experience, with at least 1 year of direct hands-on experience delivering AI application products, AIGC products, or Agent products. Must have fully shipped at least one AI-related feature module or standalone product.
AI Technical Understanding
: Deep understanding of the productization of mainstream AI technologies, including but not limited to: LLM Prompt Engineering, RAG (Retrieval-Augmented Generation) architecture, Agent fundamentals (tool calling / task planning / context window management), and conversational system design. Ability to independently evaluate the product feasibility of technical proposals.
Evaluation & Data Capabilities
: Proven ability to design AI product evaluation frameworks — independently defining evaluation metrics, building test case sets, and tracking product performance through data analysis. Familiarity with A/B experiment design and a strong data-driven decision-making mindset.
Documentation & Communication Skills
: Ability to write structured, logically rigorous PRDs, technical requirement documents, and flow diagrams. Excellent cross-functional communication skills with the ability to accurately bridge information between technical and business teams, eliminating information gaps.
User Insight & Product Thinking
: Sharp ability to translate ambiguous user needs into clearly defined product requirements. Skilled at finding the right product balance between AI capability boundaries and user expectations — avoiding both overpromising and underutilizing model capabilities.
Learning Agility & Ownership Mindset
: Sustained enthusiasm and capacity for continuous learning in a rapidly evolving AI landscape. Strong sense of ownership — able to proactively define problems, drive decisions, and take accountability for outcomes in highly ambiguous environments.
Nice to Have
Familiarity with cutting-edge AI engineering practices including
MCP
(
Model Context Protocol
), Function Calling, and multi-agent orchestration frameworks
(e.g., LangChain / AutoGen / CrewAI), enabling deep technical dialogue with engineering teams.
Experience with
AI Harness / Eval / Benchmark
platform product design or usage, with involvement in establishing and maintaining LLM evaluation systems.
Background in
Fintech / e-commerce / SaaS
industries, with an understanding of the unique product design requirements for AI in high-concurrency, compliance-sensitive environments.
Bilingual fluency in Chinese and English
(spoken and written), with the ability to independently drive product collaboration and cross-cultural communication within international teams.
Why Join Us
At Bybit, we are committed to fostering a supportive and enriching work environment.
Our benefits include:
- Study Growth Fund: We support your professional development and continuous learning.
- Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation.
- Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world.
- Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company.
- Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.
Задачи:
— развитие клиентского frontend и admin panel
— проектирование и реализация новых фич end-to-end: от технического решения до релиза
— работа с React, TypeScript, Node.js
— SSR, prerendering, BFF
— интеграции с Go-backend
— WebSocket, SSE
— white-label / multi-theme архитектура
— runtime config, design tokens
— unit и integration tests
— code review и участие в технических решениях
Требования:
— 3-4+ года коммерческой разработки
— сильный React и TypeScript
— JavaScript, HTML/CSS, adaptive / cross-browser
— state management: Redux, Zustand, MobX или аналоги
— понимание HTTP, REST, базовые знания SQL
— Git, CI/CD
— frontend security: XSS, tokens, validation
— умение проектировать решения, читать и ревьюить чужой и AI-generated code
Будет плюсом:
— опыт с white-label / multi-tenant продуктами
— знание design systems / theme systems
— опыт работы с Figma → code / design tokens
— знание Go
— опыт в fintech, crypto, Web3
— понимание agentic workflows, MCP, AI в CI
Условия:
— полностью удалённая работа
— полная занятость
— зарплата $2500-3000
— минимум бюрократии и микроменеджмента
— много новых продуктовых задач
— влияние на архитектуру и продукт
— компания оплачивает AI-инструменты
Задачи:
— Проектировать и развивать LLM/AI-системы и AI-агентов;
— Строить многошаговые agentic workflows: routing, tool calling, state management;
— Работать с Prompt Engineering и Context Engineering;
— Управлять контекстом, памятью и состоянием диалога;
— Реализовывать structured output и function/tool calling;
— Строить RAG-пайплайны: chunking, embeddings, retrieval, reranking;
— Интегрировать LLM с API, базами данных и внутренними сервисами;
— Разрабатывать backend-сервисы на Go и AI-компоненты на Python;
— Исследовать новые модели и подходы, быстро проверять гипотезы;
— Выбирать модели с учетом качества, latency и стоимости;
— Строить систему оценки качества: evals, regression tests, golden datasets, LLM-as-a-judge;
— Анализировать логи и traces, улучшать качество и стабильность агентов;
— Реализовывать retries, fallbacks, timeouts и обработку ошибок;
— Доводить решения от прототипа до стабильного production.
Требования:
Go:
— production-сервисы;
— REST/gRPC API;
— concurrency;
— работа с БД;
— микросервисная архитектура.
Python:
— AI-сервисы и backend;
— async;
— API;
— обработка данных;
— быстрое прототипирование.
Также важно:
— Практический опыт разработки production-приложений с LLM;
— Понимание архитектуры современных AI-систем: prompt → context → tools → agent → state → evaluation;
— Опыт Prompt Engineering: system prompts, few-shot, prompt chaining, structured output;
— Опыт Context Engineering: memory, summarization, динамическая сборка контекста;
— Опыт создания AI-агентов и agentic workflows;
— Работа с LLM API и понимание особенностей разных моделей;
— Понимание RAG: embeddings, vector search, retrieval, reranking, hybrid search;
— Понимание evals, regression testing и анализа production-логов;
— Опыт с PostgreSQL, MongoDB, Redis, Docker, Git, CI/CD;
— Понимание production-подходов: observability, scalability, latency, retries, fallbacks и контроль стоимости.
Будет плюсом:
— Multi-agent системы;
— LangGraph;
— MCP;
— Langfuse / LangSmith;
— Elasticsearch / OpenSearch;
— Open-source LLM: Qwen, Llama, DeepSeek и др.;
— vLLM / Ollama;
— Kafka / RabbitMQ;
— Kubernetes;
— Оптимизация token usage, latency и стоимости LLM;
— Guardrails и защита от prompt injection;
— Highload-системы.
Ищем инженера, который воспринимает LLM не как простой API, а как компонент большой production-системы. Важно уметь проектировать всю логику вокруг модели: какие данные передать в контекст, какого агента или инструмент вызвать, как проверить результат, обработать ошибку и определить следующий шаг. Ищем software engineer с сильной AI/LLM-экспертизой, который умеет не только написать хороший промпт, но и довести всю систему до стабильного production-решения.
Location: Bengaluru, India
We are looking for a Senior AI Quality Engineer (L3+) with strong Python skills and hands-on experience testing AI and ML systems. You will analyze requirements, define evaluation strategies, build automated checks, validate models and outputs, test APIs and data pipelines, verify defects through resolution, and contribute to release readiness for your assigned product area. You will both evaluate AI systems and design, build, and operate QE agents for the software testing life cycle.
AI-assisted work is part of everyday QE practice on this engagement, with Ragas, DeepEval, promptfoo, Cursor, and other AI and ML tools used for evaluation, scripting, test generation, analysis, and maintenance.
You will also build golden datasets, calibrate LLM-as-judge methods, test agentic workflows and RAG systems, implement self-healing and intelligent test approaches, and diagnose quality, safety, performance, and cost failures across distributed AI services.
This position is intended for Hyderabad-based candidates who are available to work from the office.
The client delivers AI agents, retrieval systems, models, and data pipelines across a broad technology landscape. Quality is part of delivery through evaluation gates, automated regression, model and data validation, security and privacy checks, and evidence that a release is ready.
Python is the primary language for AI evaluation, model validation, API testing, data-pipeline quality, and QE agent design. The role combines deterministic automation with probabilistic evaluation to assess AI behavior across models, data, retrieval, tools, and integration surfaces, and designs and operates agents that support the software testing life cycle.
Analyze requirements and define evaluation strategies, golden datasets, regression benchmarks, baselines, thresholds, and blocking metrics with domain-expert review.
Design, build, and orchestrate AI agents, persona-based workflows, and reusable skills for the STLC using LangChain, LangGraph, or Semantic Kernel.
Build automated evaluations and benchmarks for LLMs, agents, RAG, retrieval, tool trajectories, and contracts using Ragas, DeepEval, and promptfoo.
Calibrate LLM-as-judge against human grading, manage non-determinism through repeated runs, and detect regression and drift.
Write and maintain Python and pytest automation for AI, ML, API, data, and integration workflows.
Use Cursor and agentic tools to analyze requirements, generate and review tests, and maintain evaluation suites.
Validate deep-learning, reinforcement-learning, and predictive models using LangChain.
Build AI-assisted STLC workflows for requirements analysis, test design, script generation, execution, self-healing, failure analysis, and defect triage, plus intelligent test selection and defect prediction.
Integrate LLMs, APIs, embeddings, vector databases, retrieval pipelines, and enterprise data sources into QE frameworks using Python.
Test REST and streaming APIs, agent tools, and RAG and MCP integrations, including authentication, errors, retries, and recovery.
Test data and retrieval pipelines for schema integrity, lineage, idempotency, fallback, promotion gates, and rollback.
Integrate evaluations, benchmarks, and agent workflows into QE frameworks and CI/CD on GitHub Actions, review Allure results, and keep TestRail aligned with automated coverage.
Test prompt injection, jailbreaks, unsafe tool use, data exfiltration, access control, PII controls, and guardrails.
Measure accuracy, relevance, groundedness, hallucination, retrieval quality, agent reliability, latency, throughput, token use, and cost, and diagnose distributed failures.
Implement tracing, monitoring, and production evaluation using Langfuse, LangSmith, or a comparable AI observability platform.
Deploy and operate QE agents on Amazon Bedrock AgentCore or a comparable agent platform, with governance and human oversight.
Deploy and validate AI and ML solutions on AWS or Azure, including secrets, database services, and cloud-native test infrastructure.
Report, track, and verify defects in Jira, and work with domain experts, product, and engineering on traceable coverage and untested scope.
Contribute to release readiness for the assigned product area without owning sign-off for the whole team.
Strong Python proficiency with pytest for test and evaluation automation.
Hands-on experience building and orchestrating AI agents and agentic workflows with LangChain, LangGraph, Semantic Kernel, or comparable frameworks.
Hands-on experience building AI evaluations and benchmarks with Ragas, DeepEval, promptfoo, or equivalent tools.
Hands-on use of Cursor or agentic development tools for test generation and maintenance.
Experience defining AI evaluation strategies, golden datasets, regression benchmarks, and LLM-as-judge calibration, including non-determinism and drift.
Experience validating deep-learning, reinforcement-learning, and predictive models with LangChain.
Experience building AI-assisted STLC workflows for requirements analysis, test design, script generation, execution, self-healing, failure analysis, defect triage, intelligent test selection, and defect prediction.
Experience integrating LLMs, APIs, embeddings, vector databases, and retrieval pipelines with automation frameworks in Python.
Experience testing REST and streaming APIs, agent tools, RAG workflows, and MCP integrations.
Experience testing data and retrieval pipelines for correctness, lineage, and safe promotion.
Experience integrating AI evaluation and agent workflows with automation frameworks and CI/CD using GitHub Actions, Allure, TestRail, or equivalent tools.
Experience testing AI security, privacy, access control, and guardrails.
Experience measuring accuracy, relevance, groundedness, hallucination, retrieval quality, agent reliability, latency, throughput, token use, and cost, and diagnosing distributed failures.
Experience with AI tracing, monitoring, and production evaluation using Langfuse, LangSmith, or comparable tools.
Familiarity with AWS, Azure, or GCP cloud AI services and agent platforms for deploying and validating AI and ML solutions.
Experience deploying and operating agents on Amazon Bedrock AgentCore or a comparable agent platform, with governance and human oversight.
Experience managing defects through resolution in Jira or an equivalent tool.
Ability to work with domain experts, product, and engineering on ground truth and coverage gaps.
Experience contributing to release readiness for an assigned product area.
Playwright and TypeScript experience for UI and API automation.
Real-device and cross-browser execution using LambdaTest, Sauce Labs, or an equivalent platform.
Knowledge of AI-driven test optimization and coverage analytics using SeaLights or an equivalent platform.
Experience contributing reusable components to shared automation frameworks and reviewing automation code through Git and GitHub workflows.
Experience managing test data and troubleshooting test environments needed for reliable execution.
Experience triaging security findings and validating operational readiness, monitoring, rollback, and recovery controls.
Experience producing audit-ready evaluation reports and improving shared evaluation patterns, automation libraries, and datasets.
Задачи:
— исследование клиентского опыта в рамках процессов оздоровления и взыскания, поиск «узких» мест в процессах и использование передовых инструментов для проведения локальных исследований (графовый анализ, LLM для поиска инсайтов, самовоспроизводящиеся ИИ-решения, disrupt-проекты)
— регулярные встречи с Заказчиками для определения зон роста, предоставления непредвзятого взгляда на процессы и предложения к их трансформации
— создание ИИ-решений, влияющих на клиентский опыт
— построение чистого эксперимента и валидация ИИ-решения
— проработка технологической реализации при поддержке команд разработчиков, data и OPS-специалистов
— контроль внедрения ИИ-решения и последующего поведения решения в ПРОМ-контуре, анализ результатов внедрения
— создание AI-агентов на базе LLM для оптимизации рутинных процессов: оптимизация документальной и рутинной работы, речевая и текстовая аналитика взаимодействия с клиентом, выявление сущностей для автоматизации внутренних процессов, качественная суммаризация текста для составления профиля клиента
— разработка и внедрение ML/AI-моделей: оценки и прогноза финансового состояния клиента, подбор индивидуальных условий для урегулирования задолженности, антифрод и выявления мошенничества, скоринг клиентов, прогнозирование дефолта по обязательствам, What-If / Uplift моделирование и каскады моделей для выстраивания процессов с использованием ИИ, графовый анализ компаний, их руководителей и бенефициаров, анализ новостного контента и других источников информации о клиентах.
Требования:
— опыт работы 3+ лет в традиционных направлениях машинного обучения (ML), обработки естественного языка (NLP), глубокого обучения (DL)
— знание библиотек и фреймворков: pandas, pyspark, catboost, pytorch, tensorflow, langchain/langgraph
— опыт валидации AI-решений и их "боевого" пилотирования решений
— прикладной опыт в использовании LLM, контроле качества ответов и выстраивания графовой архитектуры с использованием LLM tools / MCP
— знания математической статистики и основ A/B-тестирования
Будет плюсом:
— опыт руководства проектами или самостоятельного обеспечения всего цикла производства ИИ-решения от гипотезы до реализации
— знание основ финансового анализа и бухгалтеского учета
— опыт курирования или наставничества, работа в крупных AI-проектах с смежными командами
— английский язык — уровень Intermediate и выше
— опыт в проектах, связанных с клиентским опытом / бизнес-анализом / исследованием очень больших данных
— опыт использования AI-инструментов в разработке (LLM-ассистенты для написания и ревью кода, агенты для автоматизации рутинных операций, инструменты автодополнения вроде GitHub Copilot)
Условия:
— возможен гибридный формат работы, локация офиса пр-кт Кутузовский, 32 к3 стрА
— ежегодный пересмотр зарплаты, 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
— гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ
— подписка Прайм с возможностью совместного использования на трёх близких
— вознаграждение за рекомендацию друзей в команду Сбера.
Задачи:
— Писать детальные спецификации для AI-агентов, определять архитектурные решения и создавать технические спецификации на естественном языке для генерации production-ready кода.
— Основная часть задач связана с пользовательскими витринами на Angular, часть — с BFF и более глубокими слоями, требуется опыт Fullstack.
— Иногда править код вручную, если это быстрее, чем перезапускать агента.
— Управлять мульти-агентными сессиями разработки, организовывать цепочки задач между AI-агентами, контролировать контекст, использовать MCP-серверы и .md-файлы для управления поведением агентов.
— Проводить AI-code review без написания кода, управлять правилами генерации тест-кейсов и критериев приемки, анализировать результаты тестов и корректировать агента.
— Настраивать AI-driven CI/CD пайплайны, автоматизировать деплой, генерацию hotfix'ов, создание скриптов миграций и исправление проваленных тестов.
Требования:
MUST HAVE по AI-инструментам:
— Минимум 6 месяцев ежедневной работы с Cursor, Cline, Claude, Codex, OpenCode или аналогами.
— Портфолио проектов с кодом, сгенерированным AI (git history с характерными коммитами).
— Опыт работы с контекстными окнами 100k+ токенов, умение оптимизировать и настраивать плагины.
— Навык написания системных промптов и agent instructions (.cursorrules, SYSTEM.md).
MUST HAVE по технологиям:
— Современные версии Angular и опыт работы со старыми версиями для обновления.
— Знание Figma и MCP для ИИ-агентов.
— .NET 6+ с опытом 2+ года.
— Понимание архитектуры: REST API, gRPC, message brokers, CQRS, DDD.
— Умение читать AI-сгенерированные диффы в Git по 500+ строк.
Red flags:
— Использование ChatGPT для простых SQL-запросов не подходит.
— Использование Copilot для автодополнения не считается AI-first разработкой.
— Готовность учиться без реального опыта не подходит.
Условия:
— Работа в аккредитованной IT-компании, входящей в состав Холдинга РЖД.
— Официальное оформление, отпуска, больничные по ТК, стабильный доход.
— График работы 5/2, 8-часовой рабочий день, работа в офисе.
— ДМС, включая стоматологию.
Location: United States, San Mateo, CA
Why Sony Interactive Entertainment?
Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.
Are you passionate about Responsible AI and ensuring products are built and deployed ethically and safely? Sony Interactive Entertainment is seeking a highly motivated and experienced Senior Responsible AI & Governance Technical Specialist to help ensure our AI products and technologies are developed and deployed ethically, safely, and in alignment with our values. Demonstrable experience in Responsible AI and AI Governance is required. Technical skills are also a must.
In this role, you will operate at the intersection of modern AI technology, policy, and ethics. You will design and implement technical governance frameworks, guidelines, and best practices that support responsible AI innovation across the organization. You will identify and assess potential risks, conduct technical and business evaluations, and partner closely with cross-functional stakeholders to embed responsible AI principles into product development lifecycles, adapting to AI-enabled and agentic systems in particular, and identifying where AI-specific guidance or risk mitigations are needed.
This is a highly collaborative role working across engineering, product, information security, legal, and business teams to ensure AI initiatives align with regulatory requirements and SIE’s broader strategic goals. The ideal candidate brings a strong understanding of generative AI use cases, technical and sociotechnical risk, and product development, balancing responsible AI commitments with internal and external innovation.
If you are passionate about AI Governance and Responsible AI, and have demonstrable experience and skills required for this position, we encourage you to apply. This is an opportunity to build and mature an AI governance program within a fast-evolving landscape.
What You’ll Be Doing:
Contribute to long-term strategies for building safe, ethical, and innovative AI products and tools
Serve as a technical Responsible AI advisor for generative and agentic AI systems, helping teams assess architectures, tool integrations, MCP implementations, data flows, permissions, autonomy, and appropriate human oversight and guardrails
Engage stakeholders across the organization to gather feedback and address AI Governance and Responsible AI technical considerations
Use AI governance, risk tooling and discovery insights to identify emerging risks and support appropriate remediation and technical solutions
Experiment hands-on with emerging AI capabilities, including agents, MCP servers, tool integrations, APIs, and evaluation frameworks, to understand their capabilities and risks and translate findings into practical governance guidance
Sit on relevant domain boards as a technical specialist, partnering closely with Product and Engineering
Conduct ethical and safety risk assessments, advising teams on mitigation strategies related to bias, fairness, robustness, transparency, and societal impact
Partner with engineers, product managers, designers, online safety and more, to proactively identify unintended consequences and emerging risks of AI
Coordinate with Information Security and relevant technical teams to align AI governance reviews and risk assessments with security requirements and technical controls
Contribute to company-wide best practices for responsible AI development and deployment, including AI literacy materials and case studies
What We’re Looking For:
1+ years of experience in AI Governance, Responsible AI, Corporate Governance, AI safety, AI policy, or a related field, with meaningful experience evaluating AI technologies and systems
At minimum, 5 years of experience contributing to or leading cross-functional programs from strategy through operational implementation, partnering with product, engineering, legal, security, and operations teams
Strong technical fluency in modern AI systems, including LLMs, agentic architectures, tool use/function calling, APIs, cloud services, and automation
Hands-on experience working with or evaluating agentic AI systems; familiarity with MCP or comparable protocols and agent/tool integration frameworks strongly preferred
Experience with AI red teaming, adversarial testing, or other technical approaches to identifying risks in LLM and agentic systems
Understanding of agentic and sociotechnical AI risks, including excessive agency, permissions and data access, unintended tool use, human oversight, systemic risk, and emergent behaviors
Ability to translate technical findings and risks into practical controls, mitigations, and guidance for engineering, product, and business teams
Ability to independently drive outcomes across cross-functional teams with minimal supervision
Strong analytical and communication skills, sound judgment, and the ability to challenge assumptions and navigate ambiguity in a fast-moving environment
Ability and curiosity to stay current with emerging AI capabilities, risks, frameworks, and industry developments, particularly within technology, entertainment, and gaming
Preferred Qualifications:
Familiarity with relevant regulations, standards and ethical guidelines (e.g., EU AI Act, OECD Principles, NIST AI RMF, ISO/IEC 42001)
Proficiency in producing meaningful visualizations and reports, and effectively presenting technical results to diverse audiences
Industry experience in tech, gaming or (interactive) entertainment
At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.
Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location.
In addition, this role
is eligible
for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products.
This role also may be eligible for a bonus package.
Click
here
to learn more.
The estimated base pay range for this role is listed below.
$132,800
—
$199,200 USD
Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.
Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.
Equal Opportunity Statement:
Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.
We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.
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