Вакансии

Задачи: — Разработка Web-интерфейса Агента AI PDLC — Участие в принятии архитектурных решений — Анализ данных проекта для определения спецификаций и требований — Документирование процедур проектирования и разработки — Обеспечение качества разрабатываемого программного обеспечения — Реализация интерфейсного дизайна сайта — Устранение неисправностей веб-сайта (при необходимости) Требования: — Профильный опыт frontend-разработки 5+ лет — Высшее образование — Уверенное владение стеком React (от 3-х лет) — Знание и опыт работы с JavaScript (ES6+), TypeScript, HTML5, CSS, AJAX Условия: — Работа в стабильной компании, "белая" заработная плата — Расширенный социальный пакет: ДМС (включая стоматологию), корпоративные скидки на посещение фитнес-клубов, футбольная и волейбольная секции — Профессиональное обучение и развитие — Яркая и насыщенная корпоративная жизнь — Снабжение всей необходимой современной техникой: мощный ноутбук привезут в день оформления — Работа в офисе в Москве

Location: Москва Наш департамент отвечает за развитие корпоративных продаж в сегменте крупного, крупнейшего и среднего бизнеса. Мы создаем собственную AI-first CRM-систему и реализуем проекты по созданию AI-агентов и мультиязычных приложений для наших корпоративных клиентов. Используем современный стек: A2A, MCP, LangGraph, LangChain, Kubernetes, Hadoop, Elastic и многое другое. Обязанности Чем предстоит заниматься: • разработка и внедрение AI-агентов в production • интеграция с внешними системами и сервисами через Kafka, REST API, gRPC, WS и другие протоколы • подготовка релизов моделей и агентов, включая документацию, демонстрационные материалы и защиту решений перед банковскими регуляторами • сотрудничество с бизнес-заказчиками, архитекторами и продуктовыми командами. Требования Мы ждём что ты: • имеешь опыт работы в качестве ML-инженера, DS, MLOPS или Python Backend-разработчика в сфере машинного обучения • имел успешный опыт создания промышленных рекомендательных систем • обладаешь опытом промышленной разработки на Python, знанием принципов ООП и паттернов проектирования, опыта работы с микросервисной архитектурой • работал с большими объемами данных и распределёнными хранилищами данных, такими как Hadoop • работал с инструментами для создания AI-агентов, такими как LangChain или LangGraph, обладаешь базовым пониманием ML/DL Будет плюсом: • опыт работы с распределёнными очередями задач и сообщений, потоковой обработкой данных (celery, taskiq, rabbitmq, Kafka) • опыт разработки высоконагруженных, геораспределённых систем, использование OpenShift/Kubernetes • навыки в инженерии данных. Условия Что мы предлагаем: * современный комфортный офис возле метро Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

- fluent Polish language. - experience in sales.

We are seeking a Sales (Conversion) Agent to join our international team at our headquarters in Limassol. - fluent English language.

Tasks: — Lead and execute core 0-to-1 initiatives in cutting-edge domains such as Agentic AI. — Translate high-level strategic vision into concrete execution roadmaps, driving rapid implementation from prototype to production. — Architect scalable solutions and drive critical milestones to position the new department for rapid growth and potentially a spin-off to attract institutional backing. Requirements: — Based in Europe or the Americas (or open to relocate/remote arrangements). — High-agency builder mindset, with proven domain expertise and the drive to take extreme end-to-end ownership. — Excellent verbal and written communication skills in English. Conditions: — 100% remote work. — Full-time employment. Additional information: — Maximum ownership: Complete autonomy to architect systems, drive strategy, and build from 0 to 1 without corporate red tape. — High-growth environment focused on strong market validation and scalable traction. — Elite team: Report directly to the department founder and collaborate with a world-class team. — Competitive compensation with equity upside.

Location: Cairo Workplace: onsite We are hiring a Corporate Activation Agent to drive the acquisition and activation of Klivvr cards across corporate clients. The role is responsible for achieving card sales targets, engaging with potential clients, reviewing and processing application forms, and ensuring the successful activation of cards. The successful candidate will work closely with corporate officers and cardholders to complete required documentation, resolve application issues, activate inactive cards, and follow up on credit limit increases. This role requires a target-driven professional with strong communication skills, attention to detail, and the ability to manage multiple client requests in a fast-paced environment. What you will do : Achieving the target of selling Klivvr cards. Receiving forms from corporate officers and reviewing documents and attachments. Entering data of targeted clients into the system. Communicating with potential clients and acquiring them. Working on activating inactive cards. Completing remaining documentation for rejected forms. Following up on increasing credit limits for cardholders. To succeed in this role, you'll need to have: 1-3 years of work experience (Banking sector - Consumer finance - Insurance) is a must. Bachelor's degree. Outstanding communication skills.

Задачи: — Проверять страховые льготы и право на получение услуг пациентов. — Анализировать покрытие, долю расходов, варианты провайдеров и ограничения. — Связываться со страховыми компаниями и документировать детали льгот. — Помогать с предварительными авторизациями и апелляциями по претензиям при необходимости. — Выполнять точный ввод данных и контроль качества. — Выявлять и эскалировать недостающую информацию или проблемы с возмещением. Требования: — Среднее образование или GED. — Опыт работы не менее 2 лет или наличие 2-летнего диплома. — Предпочтителен опыт в здравоохранении, страховании, медицинском биллинге или обслуживании клиентов. — Желателен опыт проверки льгот. — Навыки работы с компьютером, коммуникации, решения проблем и внимательности к деталям. — Владение Outlook, Word и Excel. Условия: — Удалённая работа с использованием собственного оборудования (BYOD). — График: понедельник–пятница, 8:30–17:30 по восточному времени США. — Перерывы: 1 час неоплачиваемого обеда и два оплачиваемых 15-минутных перерыва. — Оплата: $17 в час. — Запрещено проживание в штатах: Калифорния, Колорадо, Коннектикут, Гавайи, Вашингтон, округ Колумбия, Иллинойс, Айова, Мэн, Мэриленд, Массачусетс, Мичиган, Миннесота, Монтана, Нью-Гэмпшир, Нью-Мексико, Невада, Северная Дакота, Нью-Джерси, Нью-Йорк, Орегон, Пенсильвания, Род-Айленд, Южная Дакота, Вермонт, Вашингтон, Западная Вирджиния.

Location: United States Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. PROOF OF WORK   THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The Agent Systems team is a 0→1 engineering group building internal AI-powered agents that interact directly with company systems. The mandate is to dramatically increase internal speed of execution through automation, intelligent inference, and workflow orchestration. This team operates at the intersection of AI, backend systems, and applied product engineering. The work is pragmatic and fast-moving — prototypes are expected, but the bar for production reliability remains high. Engineers on this team move fluidly between experimentation and shipping, building systems that reason over user interactions and take meaningful action across internal tools. You’ll work closely with cross-functional partners across product, infrastructure, and internal operations to deploy agent-driven capabilities that compound leverage across the organization.   THE OPPORTUNITY - Build and ship AI-powered agent systems that automate internal workflows and decision paths - Design and implement inference pipelines that reason over user interactions across internal systems - Prototype quickly to validate agent behaviors, then productionize what proves valuable - Architect backend services that integrate with multiple internal APIs and data sources - Define patterns for safe, observable, and controllable agent execution - Collaborate cross-functionally to identify high-leverage automation opportunities - Improve system speed, reliability, and signal quality as usage scales - Contribute to foundational design decisions for a 0→1 agent platform   SKILLS YOU SHOULD HODL - 5+ years of experience building and shipping production software systems - Strong backend engineering fundamentals (APIs, distributed systems, data modeling, reliability) - Experience building fullstack systems, with comfort working across backend and occasional frontend surfaces - Hands-on experience working with AI/ML systems, LLMs, or inference pipelines in production - Ability to prototype rapidly while maintaining a clear path to production-grade architecture - Strong systems thinking — able to reason about orchestration, failure modes, and observability - Comfort operating in ambiguous, 0→1 environments with high ownership   NICE TO HAVES - Experience building or operating agent-based systems or autonomous workflows - Familiarity with prompt engineering, evaluation frameworks, or model performance tuning - Experience integrating with internal enterprise systems (CRM, support tools, analytics platforms, etc.) - Background in building developer platforms or internal tooling - Experience designing guardrails, sandboxing, or safety layers for AI systems Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: United Kingdom; Brazil; United Arab Emirates; Ireland; Peru; Sweden; Colombia; Argentina; Romania; Cyprus; Switzerland; Portugal; Lithuania; South Africa; Czech Republic; Canada; Hungary; Mexico; Chile; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. PROOF OF WORK   THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The Agent Systems team is a 0→1 engineering group building internal AI-powered agents that interact directly with company systems. The mandate is to dramatically increase internal speed of execution through automation, intelligent inference, and workflow orchestration. This team operates at the intersection of AI, backend systems, and applied product engineering. The work is pragmatic and fast-moving — prototypes are expected, but the bar for production reliability remains high. Engineers on this team move fluidly between experimentation and shipping, building systems that reason over user interactions and take meaningful action across internal tools. You’ll work closely with cross-functional partners across product, infrastructure, and internal operations to deploy agent-driven capabilities that compound leverage across the organization.   THE OPPORTUNITY - Build and ship AI-powered agent systems that automate internal workflows and decision paths - Design and implement inference pipelines that reason over user interactions across internal systems - Prototype quickly to validate agent behaviors, then productionize what proves valuable - Architect backend services that integrate with multiple internal APIs and data sources - Define patterns for safe, observable, and controllable agent execution - Collaborate cross-functionally to identify high-leverage automation opportunities - Improve system speed, reliability, and signal quality as usage scales - Contribute to foundational design decisions for a 0→1 agent platform   SKILLS YOU SHOULD HODL - 5+ years of experience building and shipping production software systems - Strong backend engineering fundamentals (APIs, distributed systems, data modeling, reliability) - Experience building fullstack systems, with comfort working across backend and occasional frontend surfaces - Hands-on experience working with AI/ML systems, LLMs, or inference pipelines in production - Ability to prototype rapidly while maintaining a clear path to production-grade architecture - Strong systems thinking — able to reason about orchestration, failure modes, and observability - Comfort operating in ambiguous, 0→1 environments with high ownership   NICE TO HAVES - Experience building or operating agent-based systems or autonomous workflows - Familiarity with prompt engineering, evaluation frameworks, or model performance tuning - Experience integrating with internal enterprise systems (CRM, support tools, analytics platforms, etc.) - Background in building developer platforms or internal tooling - Experience designing guardrails, sandboxing, or safety layers for AI systems       Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: Prague, Czechia D-ploy ist ein Unternehmen für IT- und Engineering-Lösungen mit Standorten in der gesamten EMEA-Region, darunter die Schweiz, Deutschland, Tschechien, Österreich und Großbritannien, sowie in den USA. Wir sind stolz darauf, zahlreichen branchenführenden Kunden innovative und erstklassige Services und Lösungen zu bieten. Durch den Aufbau von Beziehungen und vertrauensvollen Partnerschaften in der IT-Community optimieren wir die IT-Produktivität unserer Kunden und tragen zu ihrem Erfolg und Unternehmenswert bei. Wir freuen uns auf engagierte, flexible und lösungsorientierte Menschen, die Teil einer dynamisch wachsenden, internationalen Organisation werden möchten. Wir schaffen Mehrwert dort, wo IT zählt – werde Teil unseres Teams! Task and Responsibilities: Technischer Support und Fehlerbehebung bei Computer-Hardware und -Software, mobilen Geräten sowie weiteren technischen Tools und Produkten Sorgfältige Dokumentation von Anwenderanfragen im ITSM-Tool Arbeiten nach definierten Prozessen und Knowledge-Artikeln Management des Ticket-Backlogs Kontinuierliche Serviceverbesserung, z. B. Erstellung von Knowledge-Skripten und Aktualisierung von Schulungsunterlagen Enge Zusammenarbeit mit den IT-Technikern vor Ort Requirements Sprachkenntnisse: fließend Deutsch und Französisch, weitere Sprachen sind von Vorteil Fortgeschrittene Kenntnisse in MS-Office-Anwendungen von Vorteil Ausgeprägte Problemlösungs- und Analysefähigkeiten Gute Kommunikationsfähigkeiten Genauigkeit und Multitasking-Fähigkeit Selbstständige und effiziente Arbeitsweise Bereitschaft, Vorgaben und Best Practices zu befolgen Planungs- und Organisationsfähigkeit Teamplayer mit hilfsbereiter Persönlichkeit Vorlage eines Strafregisterauszugs (Führungszeugnis), der nicht älter als drei Monate ist Benefits Vielfältige Tätigkeiten, Aufgaben und Projekte Flexible Arbeitsbedingungen Gutscheine zum Geburtstag, zur Hochzeit und eine Überraschung zur Geburt eines Kindes „Fishing for Friends“ – unser Mitarbeiterempfehlungsprogramm Weiterbildung und berufliche Entwicklungsmöglichkeiten Freundliches und internationales Arbeitsumfeld Firmenevents Wettbewerbsfähiges Gehalt und diverse Zusatzleistungen Is IT in your DNA?

Задачи: — Разрабатывать и поддерживать backend-сервисы на Python (FastAPI, asyncio) — Развивать логику диалогового агента: сценарии и состояния звонка, извлечение данных из реплик, работу с LLM — Писать интеграции с МИС и CRM клиник (расписание врачей, запись пациентов) и с внешними API — Проектировать REST API для веб-интерфейса операторов и админки клиник — Работать с фоновыми задачами и очередями (Celery / TaskIQ, RabbitMQ, Redis) — Проектировать схемы данных и оптимизировать запросы в PostgreSQL — Разбирать логи звонков, находить и исправлять ошибки в поведении агента — Участвовать в код-ревью, покрывать код тестами, улучшать кодовую базу — Деплоить и сопровождать сервисы в Docker на Ubuntu Требования: — Коммерческий опыт разработки на Python от 1 до 3 лет — Опыт разработки на FastAPI и уверенное понимание async/await в Python — Pydantic (v2): валидация данных, схемы запросов и ответов, настройки — PostgreSQL: уверенный SQL, индексы, оптимизация запросов — Опыт с SQLAlchemy — Alembic: написание и сопровождение миграций — Celery: фоновые и отложенные задачи, ретраи, периодические задачи — RabbitMQ: понимание очередей, exchange и routing, гарантий доставки — Redis: кэширование, брокер/бэкенд для задач, TTL, базовые структуры данных — Docker и Docker Compose: умение собрать образ, поднять окружение из нескольких сервисов и разобраться, почему оно не стартует — Git и pull request-флоу (GitHub) — Linux (Ubuntu) на уровне повседневных задач: логи, процессы, сеть — Умение читать чужой код, задавать вопросы и доводить задачи до прода Будет плюсом: — Опыт интеграции с LLM API (OpenAI-совместимые API, vLLM), промпт-инжиниринг, structured output — Знакомство с LangGraph, LangChain или другими фреймворками для агентов — Опыт с real-time системами: WebSocket, стриминг, работа с аудио — Знакомство с IP-телефонией (SIP, Asterisk, LiveKit) или с медиапайплайнами (Pipecat) — Опыт интеграций с медицинскими информационными системами — Тесты на pytest как привычная часть работы Условия: — Зарплата 80 000–120 000 ₽ на руки, конкретная сумма — по итогам собеседования — Удалённая работа — Оформление по ТК или как самозанятый — Короткий путь от задачи до прода, без месяцев согласований — Прямое влияние на технические решения: открытость к предложениям по стеку и архитектуре

Задачи: — Проектировать и разрабатывать AI-агентов: реализовывать сценарии, оркестрацию, tool calling и интеграции с внутренними сервисами — Превращать прототипы и модели Data Science в надёжные промышленные решения: упаковывать, встраивать в сервисы и пайплайны, версионировать и сопровождать — Разрабатывать на Python сервисы, библиотеки и пайплайны, писать автотесты и участвовать в код-ревью — Проектировать, строить и сопровождать витрины данных для ML-моделей и агентов — Обрабатывать большие объёмы данных с помощью SQL, Hadoop и Spark, оптимизировать запросы и вычислительные задачи — Обеспечивать качество и наблюдаемость решений: логирование, мониторинг, обработку ошибок и контроль качества данных Требования: — Опыт промышленной разработки на Python от 2 лет — Умение писать поддерживаемый код: типизация, тестирование, обработка ошибок, логирование и работа с зависимостями — Уверенное владение SQL: сложные запросы, оконные функции, оптимизация и работа с большими наборами данных — Опыт построения и сопровождения ETL/ELT-пайплайнов и витрин данных — Опыт вывода сервисов, моделей или data-продуктов в промышленную эксплуатацию — Понимание принципов работы AI-агентов: оркестрация, tool calling, управление состоянием и интеграция с API — Понимание жизненного цикла ML-модели — от артефакта и данных до инференса, мониторинга и обновления Будут плюсом: — опыт с LangGraph, LangChain, LlamaIndex или собственными оркестраторами — LLM, RAG и векторные хранилища — оркестрация в Airflow — Kafka и событийные архитектуры — Docker, CI/CD и Kubernetes — Hadoop и Spark — внедрение ML/LLM-сервисов во внутреннем контуре — опыт в банковском домене или продуктах для юридических лиц

Location: Remote - Canada What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote Little more about the team: AI agents at Honeycomb investigate, reason, and act on real observability data. They live in Canvas: the agentic workspace where engineers go to understand their systems. The Agentic Intelligence team has shipped Canvas, the Honeycomb MCP server, and the Canvas Agent and Canvas Skills surfaces. What we're looking for today is someone who brings deep agent expertise and uses it to expand what the team can build: new agents, new surface area in Canvas, memory, spatial awareness, improved performance on our Bedrock loop. Honeycomb's data store is fast and accepts high cardinality data; that's what makes agents built on top of it different from anything built on a conventional observability backend. This role is about taking advantage of that building agents that can do things no other observability product can do because the underlying data makes it possible. Some of this work will start as a prototype. The expectation is that the code makes it through the full arc, from the rough first version through to something that holds up in production. What you'll do Design and deliver production-grade agents. Build agents that investigate, reason, and act on live observability data inside Canvas. These agents must be trustworthy to engineers in high pressure situations, including mid-incident. Take one from rough first version to something that holds up under production traffic. Own the agent work; support the whole product. Scope, build, ship, and maintain the agents including the evals that tell you whether they got better or are just different. This role is agent-focused and also includes some fullstack development. Build agents only Honeycomb can build. Use a data store that returns high-cardinality queries in seconds to reason over signal a conventional backend can't serve at this fidelity correlating across services, drilling into a single trace, comparing before and after a deploy. Extend the surface, and decide what's next. Ship new capability into Canvas, the MCP server, and Canvas Skills memory, spatial awareness, a faster Bedrock loop and make the case for what comes after with working code. Distinguish hype from signal in a field with plenty of both. Define what "good" means for agents here. Set the bar: measurable against real evals, maintainable, and honest about their limits. Example projects Multiple agents collaborating on one shared Canvas investigation each claiming a hypothesis, publishing findings, and narrowing the search space for the others so it resolves faster (blog). Auto-investigation the moment an SLO burn alert fires the agent forms hypotheses and prepares visualizations before a human looks, cutting mean-time-to-insight for on-call (o11ycon 2026). Skills that encode a team's domain expertise e.g. Kubernetes thresholds so agents and human colleagues can lean on them (o11ycon 2026). What you'll bring: AI and agent engineering experience. You've shipped LLM-based systems people relied on in production not demos, not fine-tuned models in a research context. You know where agent systems break and how to design around it. End-to-end ownership. On a small team there's no handoff queue. You can take something from rough prototype to production-grade without needing someone behind you to do the durable engineering. Current judgment, not just past experience. You have informed opinions about what's shifted in agent design in the last six to twelve months that would change how you'd build today. Agent architecture depth. You understand how a fast, high-cardinality data store changes what an agent can reason about, and how to design for that. Product judgment. You can look at what the agent layer does today and see what it should do next and make that case with a prototype, not a deck. Even better Observability or developer-tools background. Engineers are your users; you'll ramp faster with fluency in that world, and the work is better. Familiarity with eval frameworks, agent tooling, RAG, and prompt engineering. Base Salary based on level of experience $250,000 — $280,000 CAD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Требования: — Уверенная прикладная статистика и дизайн экспериментов — Понимание LLM-систем — Желание глубоко разбираться в оценке агентов — Свободный английский язык (Fluent English) Компания Dwelly занимается диджитализацией и оптимизацией аренды квартир в Великобритании. Формат работы: удалённо (вне России и Беларуси). Размер команды: 40 человек. Инвестиции: венчурные (VC-backed). Контакт для отклика: @eugenekozlov в Telegram (при отклике указывать, что вы из @dev_connectablejobs).

Задачи: — Определять приоритеты развития платформы с учётом задач клиентов, продуктовых метрик и целей бизнеса. — Общаться с пользователями и заказчиками, в том числе на английском. — Разбираться, как они используют продукт, где сталкиваются с трудностями и за какие возможности готовы платить. — Улучшать интерфейс и возможности платформы, чтобы клиентам было проще создавать, настраивать и использовать AI-агентов. — Самостоятельно собирать работающие прототипы с помощью AI-инструментов. — Проверять идеи на конкретных сценариях и передавать инженерам решения для дальнейшей разработки. — Вместе с командой определять, как измерить результат изменений, оценивать бизнес-эффект после релиза и на этой основе принимать следующие решения. — Разбираться в архитектуре AI-агентов и возможностях используемых технологий. — Вместе с инженерами оценивать, как технические решения влияют на качество, скорость работы и стоимость продукта. — Изучать конкурентов, пробовать новые продукты и инструменты, находить полезные для клиентов идеи и проверять собственные. — Доводить продуктовые решения до релиза вместе с разработчиками и следить за тем, как ими пользуются после запуска. Требования: — Опыт развития технологического продукта на уровне Senior Product Manager в Т-Банке, Яндексе, Авито, Точке или сопоставимых продуктовых компаниях. — Умение показывать личный вклад в решения и их влияние на метрики и бизнес. — Практический опыт создания или внедрения AI-агентов. — Понимание архитектуры, технического стека и ограничений AI-агентов. — Умение подробно объяснить устройство AI-продукта, выбор технологий и решённые проблемы. — Регулярное использование AI-инструментов в работе. — Умение самостоятельно собирать работающий прототип, проверять его и готовить к передаче разработчикам. — Опыт работы с продуктовыми и коммерческими метриками: выбор показателей, проверка гипотез и оценка результата. — Способность быстро принимать решения при неполных данных, выбирать разумный объём первой версии и проверять её на практике. — Внимание к пользовательскому опыту и способность упрощать сложные сценарии. — Свободный английский для общения с международными клиентами, проведения интервью и обсуждения продукта. Плюсы: — Опыт голосовых AI-агентов, речевых технологий или B2B-платформ. — Опыт развития продукта для международного рынка. — Инженерный опыт и собственные работающие продукты, которые можно показать. — Опыт работы в продуктовых командах с быстрым выводом изменений к пользователям и оценкой влияния на бизнес. Условия: — Офисная позиция в Москве с возможностью гибридного графика. — Компенсация на уровне рынка и выше + опцион, условия обсуждаются индивидуально. Компания Bitmanager.ai — AI-стартап, создающий платформу для разработки и запуска голосовых AI-агентов, автоматизирующих клиентские коммуникации. Платформа позволяет быстро адаптировать агентов под процессы клиента с учётом безопасности, производительности и масштабирования. Роль предполагает полную ответственность за продукт и прямую работу с фаундером без менеджерских прослоек.

MEDvidi, a US-based mental healthcare platform, is seeking an AI Product Analyst to focus on Voice AI Agents that engage with patients and automate key parts of their care journey. The role involves analyzing AI behavior in production, identifying failure patterns such as hallucinations and inconsistencies, and assessing AI quality and reliability through examination of call transcripts, conversation logs, and operational data. Responsibilities include developing monitoring frameworks and dashboards to track AI performance, detecting anomalies and shifts in quality, and measuring the impact of AI on patient experience and business outcomes. Collaboration with Product, Engineering, QA, and Operations teams is essential. Candidates should have over three years of experience in Product, Data, or Operational Analytics, proficiency in SQL and Python for handling large text datasets, familiarity with ML pipelines or AI products, and an understanding of LLM limitations and AI failure modes. Experience in building monitoring systems and strong communication skills to translate insights into product decisions are required. Fluency in Russian and English (B2+) and availability during CET-overlapping hours are necessary. Preferred qualifications include experience with conversational AI, evaluating LLM outputs, and knowledge of AI quality metrics. The position offers remote work, involvement with impactful AI healthcare products, and benefits such as health insurance and paid leave.

Location: Metn, Lebanon About the Toters Toters is an on-demand e-commerce and delivery platform that enables customers to get anything in their city with the highest level of convenience. Technology is at the heart of everything we do. Our product and engineering teams work every day to build experiences that make customers’ lives easier while continuously improving internal systems to deliver faster and at the best cost. If you’re excited about working in a high-growth startup environment and want to be part of a team shaping the future of how people shop in the Middle East, we’d love to hear from you. About the Role We are looking for a Senior AI Backend Engineer to join Toters and help us build and scale the next generation of AI-powered products and engineering systems . This role sits at the intersection of Backend Engineering, AI Engineering, Platform Engineering, and Developer Enablement . We are looking for someone who not only builds AI-powered systems, but also understands how AI is adopted across an engineering organization and can help teams use AI effectively in their day-to-day development and product delivery. The ideal profile is similar to an Forward Deployed Engineer (FDE) : highly hands-on, comfortable working across different technical areas, able to understand ambiguous problems quickly, and capable of turning emerging AI capabilities into practical solutions. You will help define what good looks like for AI engineering at Toters , build reusable foundations, and enable engineering teams to adopt AI tools, agents, and AI-powered development practices. What You’ll Do Design and build backend systems and services powered by AI , integrating AI capabilities into production-grade products and internal platforms. Own and contribute to the AI engineering lifecycle , from experimentation and prototyping through deployment, observability, evaluation, and continuous improvement. Build and evolve AI-enabled developer and engineering platforms that improve productivity and accelerate software delivery. Lead the adoption of AI tools and workflows across engineering , helping teams identify high-value use cases and turn them into scalable solutions. Establish engineering standards and best practices around AI-powered development, agents, evaluation, observability, reliability, and productionization . Explore and implement emerging agentic engineering patterns , including agent-to-agent protocols, agent SDKs, tool calling, orchestration, and autonomous workflows. Build systems that leverage knowledge bases, knowledge graphs, retrieval, and contextual data to make AI applications more useful and reliable. Work closely with Backend, Platform, ML, Product, and Engineering leadership to identify opportunities where AI can meaningfully improve products and internal workflows. Prototype rapidly, validate ideas, and move successful experiments into reliable production systems. Develop reusable frameworks, libraries, and services that allow other engineers to build AI-powered applications without reinventing the foundations. Define and improve AI observability and evaluation practices, including monitoring quality, performance, reliability, cost, and model behavior. Stay current with rapidly evolving AI technologies and translate them into practical engineering solutions for Toters. What We’re Looking For 6+ years of experience software engineering , with a strong background in Backend Engineering, Platform Engineering, or a similar technical discipline. Strong experience building production-grade backend systems , preferably at significant scale. Strong programming skills in one or more backend languages such as Go, Java, or PHP . Hands-on experience building or integrating AI-powered systems and applications . Strong understanding of the AI application lifecycle , from experimentation to production deployment and monitoring. Experience with AI developer tools, LLMs, agents, agent SDKs, and AI-assisted software engineering workflows . Demonstrated experience leading AI adoption or enablement across an engineering team or organization. Ability to understand emerging AI technologies and distinguish between what is genuinely useful in production and what is experimental. Strong understanding of software architecture, distributed systems, APIs, and backend infrastructure . Experience with observability, reliability, monitoring, and production operations for complex systems. Strong problem-solving skills and the ability to work effectively in ambiguous, fast-moving environments. A builder mindset: you are comfortable going from "we should try this" → prototype → production . Nice to Have Experience working with AWS or other major cloud platforms. Experience with Platform Engineering or Developer Experience / Developer Enablement. Experience with MLOps or ML/AI infrastructure. Experience building AI agents and agentic workflows . Experience with Agent SDKs, agent-to-agent communication protocols, and orchestration frameworks . Experience with knowledge graphs, knowledge bases, RAG, or other approaches for grounding AI systems in company/domain knowledge . Experience building AI-powered developer tools or internal engineering platforms. Previous experience in an FDE, Solutions Engineer, Developer Experience, AI Platform, or similar highly cross-functional engineering role . Experience working with modern AI coding and development tools such as Claude or similar AI development platforms .