AI-инженер (LLM, агенты, AI product) вакансии - удалённо

- Minimum 3 years of experience building and maintaining production-level AI applications powered by LLMs. - At least 3 years of practical experience in Agentic Engineering, covering the entire process from solution design and implementation to integration, deployment, and ongoing support of AI agents.

AI / LLM Engineer (Go + Python) IT Вакансии Разработка и развитие production LLM/AI-систем и AI-агентов, построение agentic workflows, работа с prompt- и context-engineering, реализация structured output и function/tool calling, создание RAG-пайплайнов и интеграция LLM с API, базами данных и сервисами. Понимание RAG, embeddings, retrieval и reranking.

Требования: — Уверенное владение современными инструментами генерации и обработки изображений на базе ИИ — Умение работать с промптами, референсами, стилями, пресетами и настройками генерации — Умение добиваться повторяемого результата и сохранять заданную стилистику в серии изображений — Понимание принципов композиции, света, цвета, перспективы и построения изображения — Умение работать с исходным изображением продукта и интегрировать его в создаваемый визуал — Умение выявлять и исправлять характерные ошибки и артефакты AI-генерации — Базовые навыки работы в Adobe Photoshop или аналогичном графическом редакторе — Понимание требований к коммерческому визуальному контенту и подготовке материалов для дальнейшей обработки — Умение систематизировать рабочие решения: сохранять и описывать промпты, настройки, модели, пресеты и последовательность действий Задачи: — Создание и доработка визуального контента с использованием генеративных AI-инструментов: изображения, интерьерные сцены, продуктовый контент, карточки товара, баннеры и другие маркетинговые материалы — Генерация визуального контента на основе реальной продукции компании с сохранением ее внешнего вида, пропорций, материалов и ключевых особенностей — Настройка и применение AI-моделей, пресетов, промптов, стилей и шаблонов под визуальные стандарты бренда и конкретные задачи — Создание вариативного контента на основе исходных материалов: изменение окружения, фона, стилистики, цветовых решений и других элементов изображения — Подготовка и адаптация AI-сгенерированных материалов к дальнейшему продакшну: отбор лучших вариантов, устранение базовых артефактов и подготовка материалов к передаче ретушеру, дизайнеру или другим специалистам — Участие в разработке и настройке типовых AI-процессов (pipeline): генерация изображений, перекрасы, создание вариаций визуала и адаптация контента под разные каналы и форматы — Тестирование новых AI-инструментов и подходов для создания визуального контента, оценка качества и возможностей их применения в рабочих процессах — Систематизация успешных решений: создание шаблонов промптов, пресетов, простых инструкций и гайдов для повторного использования командой — Взаимодействие с фотографами, ретушерами, дизайнерами и другими участниками процесса производства визуального контента Условия: — Белая заработная плата до 120 000 рублей до вычета налога — Оформление по ТК РФ с первого рабочего дня — Выплаты дважды в месяц — Удаленный формат работы — График работы 5/2, 8 часовой рабочий день с 8.30 до 17.30 — Наставничество и обучение — Оплачиваемые отпуска и больничные — ДМС — Скидки на продукцию компании — Бонусы от партнёров — Подарки сотрудникам и детям — Программы признания и поощрения стажа — Обучение и развитие внутри компании — Возможности карьерного роста

At Salesloft, our Principal Engineer for AI sets the technical direction for how machine intelligence works across our Predictive Revenue System. You lead through technical credibility and make the engineers around you better.

➡️ Ищем AI/LLM Engineer, который будет проектировать и развивать production-системы на базе LLM. Ищем инженера, который умеет собрать LLM-систему целиком: от prompt/context logic и агентных сценариев до backend-сервисов, интеграций, тестирования и запуска в production.

Задачи: — Работа с NLP и AI-проектами, запуск AI-проектов в продакшн и построение архитектуры вокруг сторонних LLM-решений. — Обучение нейросетевых моделей на GPU-кластере. Требования: — Большой опыт разработки на Python с использованием Pandas, NumPy, Scikit-learn. — Опыт работы с LangChain, vLLM. — Опыт работы с PyTorch, Hugging Face Transformers. — Глубокое понимание машинного обучения, глубокого обучения и NLP. — Опыт запуска AI-проектов в продакшн и построения архитектуры вокруг сторонних LLM-решений. — Опыт обучения нейросетевых моделей на GPU-кластере. — Знание SQL. — Владение Git. — Высшее техническое образование в области Computer Science, прикладной математики, AI/ML или смежных областях. Условия: — Работа в команде экспертов. — Широкий технологический стек, сотни проектов. — Гибкий график работы. — Льготы и меры господдержки, предусмотренные для IT-компаний (аккредитованы Минцифры). — Возможность разрабатывать IT-решения для разных отраслей и пробовать новые технологии. — Возможность работать удалённо с доступом к просторным офисам с зонами коворкинга. — Возможность профессионального роста: стать тимлидом, архитектором, full-stack разработчиком. — Развитая система наставничества, сертификация за счёт компании, участие в конференциях, изучение английского языка. — Активный обмен опытом, митапы, хакатоны, доклады по развитию hard и soft skills. — 50+ клубов по интересам и профессиональных сообществ. — Уютный мерч. — Полный соцпакет и официальная "белая" зарплата. — Корпоративная база знаний и социальная сеть для сотрудников. — Гибкий ДМС с возможностью подключения родственников.

AI-native Developer IT Вакансии Студия DreamVR ищет инженера, который умеет самостоятельно превращать продуктовые задачи в работающие системы, предполагающие полную ответственность за результат. Разобраться в контексте, определить критерии готовности, выбрать решение, реализовать его и проверить результат после запуска.

You will lead and execute core 0-to-1 initiatives in cutting-edge domains such as Agentic AI. You will translate high-level strategic vision into concrete execution roadmaps, driving rapid implementation from prototype to production.

— обработка Excel, PDF и сканов; — извлечение и нормализация данных;

— быстро собирать прототипы и рабочие продукты; — искать нестандартные технические решения;

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

Мы ищем: Талантливого NLP-разработчика на стажировку, которому предстоит работать над интересными высоконагруженными проектами. Требования: — Опыт разработки на Python от 1–2 лет; — Базовое понимание LLM и AI-агентов; — Практический опыт или уверенное понимание RAG-подхода; — Опыт работы с векторными БД или embeddings (FAISS / Qdrant / аналоги — базовый уровень); — Опыт backend-разработки (FastAPI / Flask); — Понимание REST API, JSON, асинхронности; — Готовность развиваться в AI-направлении. Будет плюсом: — Опыт работы с LLM API (OpenAI / open-source модели); — Знакомство с LoRA / PEFT (pet-проекты, эксперименты); — Базовый опыт работы с брокерами сообщений (Kafka, RabbitMQ, NATS); — Docker (базовый уровень); — Pet-проекты с AI-агентами или RAG. Условия: — Работа в команде экспертов; — Широкий технологический стек, сотни проектов; — Гибкий график работы, который позволяет высыпаться и выделять время на хобби; — Возможность разрабатывать IT-решения для разных отраслей, пробовать новые технологии; — Организована удалённая работа, при этом есть просторные офисы с зонами коворкинга; — Возможность прокачаться во всех интересующих направлениях: стать тимлидом, архитектором, разработчиком full-stack; — Развитая система наставничества, сертификация за счёт компании, участие в конференциях, изучение английского языка; — Активный обмен опытом, внутренние и внешние митапы, хакатоны, доклады по развитию hard и soft skills; — 50+ клубов по интересам и профессиональных сообществ внутри компании; — Корпоративная база знаний и социальная сеть для удобства общения с каждым из 1500+ сотрудников. Дополнительно: — Решение Министерства цифрового развития, связи и массовых коммуникаций РФ о предоставлении государственной аккредитации организации, осуществляющей деятельность в области информационных технологий от 10.03.2022 №АО-20220309-3771014210-3

-писать интеграции AI-агентов с корпоративными системами. -допиливать внутренние сервисы: авторизация, логирование, личные кабинеты, дашборды.

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.

About Sezzle: With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. They are redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. Sezzle is building an innovative, dynamic team passionate about creating a unique shopping journey. About the Role: We are seeking a talented and motivated AI Engineering Intern who is best in class with a high IQ plus a high EQ. This role offers an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement. You will join the Data Science team and play a key role in designing and building foundational A.I. systems at Sezzle. What You'll Do: — Design A.I. systems from the ground up — Generate reliable and accurate training data for A.I. systems — Collaborate closely with engineers, data analysts, and business end users to build effective systems — Write accurate and efficient SQL queries What We Look For: — Proficiency in SQL and Python — Solid understanding of data analysis and database structures — Currently enrolled in a postsecondary institution studying MIS, Business Analytics/Data Analytics, Computer — Demonstrated experience working with Claude or equivalent large language model tools is required; candidates must be comfortable leveraging AI to enhance productivity, research, and communication. About You: — You have relentlessly high standards and continually raise the bar — You ensure defects do not get sent down the line and fix problems permanently — You are not bound by convention and enjoy developing new ways to do things — You value speed and calculated risk-taking in business decisions — You earn trust by listening attentively, speaking candidly, and treating others respectfully — You can respectfully challenge decisions when you disagree and commit once a decision is made — You focus on delivering key inputs with quality and timeliness, rising to occasions despite setbacks Interview Process: — Application submitted — Wonderlic test (30-40 min) — SQL and Python Questions (30 minutes) — Interview with recruiters (30 min) — Interview with engineers (1 hour) — Interview with engineering leadership (30-45 min) — Offer Sezzle’s Technology Stack: Languages: Golang, Typescript, Python Frontend: Typescript - React and React Native Backend: Golang Database: MySQL, Postgres, Elasticsearch DevOps & Cloud: AWS, Kubernetes Version Control: Git CI/CD: Gitlab Testing: Developer-driven, focus on automated unit, integration, and end-to-end tests Compensation: The salary for the A.I. Engineering Intern is $1,000 USD monthly gross.

Задачи: — Анализировать процессы и находить задачи для автоматизации — Создавать AI-решения для смет, коммуникации, контента и базы знаний — Интегрировать Telegram, Google Calendar/Tasks/Sheets, OpenAI — Работать с Railway и Supabase — Тестировать решения, исправлять баги и контролировать качество — Следить за достоверностью данных, особенно в финансовых задачах — Измерять эффект от автоматизации Требования: — Высшее образование в программировании — Опыт от 3 лет — Знание Claude Code, Cursor, Copilot, ChatGPT — Умение читать, править и дорабатывать код на Python — Опыт создания готовых решений через Cursor / Claude Code — Ответственность за результат и внимательность к деталям Условия: — Полностью удалённо — До 100 000 ₽ на руки — Выплаты 2 раза в месяц — Оформление по СЗ — Отбор: HR → тестовое → CEO → рекомендации → 3-дневная стажировка

Ищем Python-разработчика / AI Engineer уровня Middle+ / Senior на проект по автоматизации обработки и сверки финансовых документов. Проект связан с разработкой сервиса, который будет принимать акты сверки и внутренние выгрузки, извлекать из них данные, сопоставлять документы, находить расхождения и формировать понятный результат для пользователя. Задачи: — Разбирать и обрабатывать документы в форматах Excel, PDF и сканы. — Извлекать табличные данные из документов. — Нормализовать даты, номера документов, суммы и другие поля. — Проектировать и реализовывать логику сопоставления данных. — Выявлять расхождения между двумя источниками. — Обрабатывать сложные кейсы: разные периоды, отличающиеся номера, частичные совпадения и другие неоднозначные ситуации. — Интегрировать OCR и Document AI-инструменты. — При необходимости использовать LLM для интерпретации и формирования человекочитаемых объяснений. — Разрабатывать backend/API для сервиса. — Участвовать в проектировании архитектуры MVP. — Работать с реальными обезличенными финансовыми документами и тестировать качество решения на исторических данных. Требования: — Коммерческий опыт разработки на Python от 3 лет. — Уверенное владение Python. — Опыт работы с pandas и табличными данными. — Опыт обработки Excel / CSV. — Опыт парсинга PDF. — Опыт разработки backend-сервисов и REST API. — Понимание алгоритмов сопоставления, нормализации и очистки данных. — Умение проектировать решение самостоятельно, а не только работать по готовому ТЗ. — Опыт работы с Git. Будет большим плюсом: — Опыт с OCR: Tesseract, PaddleOCR или аналогами. — Опыт с PyMuPDF, pdfplumber, Camelot, Tabula. — Опыт с fuzzy matching. — Опыт работы с Document AI / Intelligent Document Processing. — Интеграция LLM API: OpenAI, Azure OpenAI, YandexGPT или аналогов. — Опыт разработки систем reconciliation / data matching. — Опыт работы с финансовыми, бухгалтерскими или другими структурированными документами. — Опыт On-Premise решений. — Опыт построения решений, где нужно сочетать детерминированную бизнес-логику и AI. Что здесь не требуется: — Мы не ищем классического Data Scientist и не планируем обучение собственных ML-моделей с нуля. В проекте важнее: — сильная прикладная Python-разработка; — работа с документами и данными; — построение надежной логики сопоставления; — понимание, где действительно нужен AI, а где лучше использовать обычные алгоритмы. О проекте: — На первом этапе планируется разработка MVP без глубокой интеграции с внутренними учетными системами. — Базовый сценарий: пользователь загружает акт сверки и внутреннюю выгрузку, система извлекает и нормализует данные, выполняет сопоставление, показывает совпадения и расхождения, формирует структурированный результат для пользователя. — Ожидаемый результат — рабочий прототип, который можно проверить на реальных исторических данных. Условия: — Удалённая работа. — Проектная занятость / аутстафф. — Возможна полная или частичная загрузка — обсуждается индивидуально. — Проект стартует с этапа MVP, с возможностью продолжения. — Работа в составе небольшой проектной команды. Ожидаемый уровень: Middle+ / Senior Нам нужен специалист, который сможет самостоятельно разобраться в предметной области, предложить техническое решение и довести его до рабочего результата. Будет преимуществом в отклике: — опыт похожих задач: обработка документов, OCR, reconciliation / matching, financial data processing, Document AI, LLM-интеграции. — указание текущей доступности, возможной загрузки в часах в месяц, часовой ставки, формата работы (ИП / самозанятый / другой).