Вакансии

You'll build the models behind those decisions. Plan the factory.

📌Задачи на проекте. - Внедрение новых и доработка действующих приложений в системе BPM - Elma365;

-Разрабатывать новые части системы (микросервисы, SOA).

Location: Prague Workplace: hybrid Filevine is a Legal AI company delivering Legal Operating Intelligence for the future of legal work. Grounded in a singular system of truth, Filevine brings together data, documents, workflows, and teams into one unified platform—where modern legal work happens with clarity and consistency. Powered by LOIS, the Legal Operating Intelligence System, Filevine connects context across every matter to transform legal operations from reactive to proactive. LOIS reads, understands, and reasons across your data to surface insight, automate complexity, and give professionals the clarity and confidence to see more, know more, and do more. Fueled by a team of exceptional collaborators and innovators, Filevine’s rapid growth has earned AI awards and recognition from Deloitte and Inc. as one of the most innovative and fastest-growing technology companies in the country. The Depo Intelligence team powers the AI behind Filevine's deposition product line. We deliver automated post-deposition transcript analysis, timelines, summaries, and witness impressions. Our latest product, Depo Copilot, assists attorneys during deposition preparation and delivers real-time insights during live proceedings. Additionally, our intelligent insights extend support to the Filevine Meetings and Notetaking apps. As the Tech Lead for Depo Intelligence, you will drive the technical direction of our AI systems. This is a hands-on machine learning role requiring strong software engineering skills. You will spend your time designing and building LLM pipelines and evaluations, as well as leading the team's architectural and design choices. You will collaborate closely with the team's Engineering Manager, who handles people management and delivery, allowing you to focus squarely on technical leadership. Key Responsibilities Own the technical vision and system architecture for machine learning workflows driving Depo Copilot, Depo Summaries, and the Meetings and Notetaking app. Architect and build LLM pipelines capable of reasoning over extensive case files and real-time transcripts, ensuring all outputs are fully grounded in source material. Determine optimal model strategies - evaluating when custom fine-tuning or trained models are required over prompt engineering - and lead implementation. Establish evaluation frameworks alongside our legal experts and annotators, creating custom datasets, rubrics, offline metrics, and release checks to proactively prevent regressions. Optimize pipeline efficiency, latency, and operational costs for live streaming analysis using strategic model selection, fallbacks, and precomputation. Transition prototypes into production-grade systems with typed contracts, test coverage, tracing, and observability, serving as technical lead for incident response during live proceedings. Author design documents, guide architectural decisions, and partner with Product, product engineering, speech recognition, and document retrieval teams to translate roadmap goals into actionable technical plans. Mentor machine learning engineers through detailed code reviews, pair programming, and design feedback while clearly communicating technical outcomes and tradeoffs to business stakeholders. Who are you? Minimum of 5 years of experience building production ML or software systems, including at least 3 years in machine learning roles with end-to-end project ownership. Proven track record of technical leadership, including conducting design reviews, setting architectural direction, and mentoring engineers. Strong background in NLP and production LLM systems, encompassing retrieval and grounding, long-context reasoning, structured outputs, evaluation, and mitigation of common failure modes. Experience designing evaluation frameworks for generative AI systems, including developing datasets and rubrics in collaboration with domain experts and annotators. Solid software engineering foundations, including API design, data modeling, distributed and asynchronous workflows, testing, and fault tolerance. Advanced proficiency in Python, alongside hands-on experience with PyTorch or other deep learning frameworks. Experience with real-time/streaming systems or legal domain NLP is a plus. Strong written and verbal communication skills in English, a collaborative team spirit, and an autonomous problem-solving mindset. Ability to meet periodically at our Prague or Bratislava office to support in-person collaboration. Our current stack primarily utilizes Python (DSPy, Pydantic, Temporal), PostgreSQL, Kubernetes, AWS, Google Cloud, and multi-provider LLMs; strong core engineering skills are prioritized over familiarity with specific tools or frameworks. Compensation starts at 190,000 CZK per month, with the final offer determined by the candidate’s seniority and experience. This opportunity is for independent contractors and is not intended to establish an employment relationship. Contractors are responsible for their own taxes and compliance with applicable laws in their jurisdiction. This role is open exclusively to candidates currently residing in, or willing to relocate to, Czechia or Slovakia with the legal right to work in these countries. Unfortunately, we are unable to consider applications from candidates based outside of these locations due to operational and regulatory requirements Privacy Policy Notice Filevine will handle your personal information according to what’s outlined in our Privacy Policy.

О продукте Forecast & Replenishment (FnR) - это самый масштабный проект по цифровой трансформации в цепочке поставок и первый в России проект по созданию и внедрению полностью отечественного ПО в F&R для такого размера бизнеса в офлайн-ритейле. F&R - это высоконагруженная система прогнозирования спроса и формирования заказов, обеспечивающая сквозную end-to-end цепочку – от размещения заказа у поставщика до доставки товара в конкретный магазин. Данная система — это не микросервисы и не монолит. Это отдельные Java-сервисы, масштабирование в которых происходит за счет Apache Ignite. Задачи Выявлять и анализировать требования, определять бизнес-потребности и переводить их в системные требования. Описывать логику работы ПО, бизнес-алгоритмы, интеграции, взаимодействие компонентов системы, требования к обработке и хранению данных. Формировать спецификации, описания процессов, модели данных, API-контракты и другие материалы, необходимые команде для разработки. Декомпозировать бизнес-задачи на отдельные задачи разработки, учитывать зависимости между компонентами и участвовать в оценке трудоёмкости. Проверять соответствие реализованного функционала согласованным требованиям, выявлять расхождения и сопровождать их устранение. Готовить документацию и описания решений, представлять реализованный функционал заказчикам и согласовывать результаты работы. Требования Опыт работы системным аналитиком от 3 лет. Уверенное владение SQL и опыт работы с базами данных. Умение выявлять бизнес-потребности, формализовывать требования и описывать функциональные и нефункциональные требования к ПО. Понимание принципов работы алгоритмов и оценки их сложности. Навыки проектирования моделей данных: построение ER-диаграмм, нормализация данных. Опыт моделирования бизнес-процессов с использованием BPMN, UML и/или DFD. Опыт проектирования API-контрактов по OpenAPI, понимание подхода API First и принципов интеграции систем через REST API, брокеры сообщений и ETL/ELT-процессы. Написание запросов SQL на среднем/высоком уровне, работа с СУБД. Опыт разработки веб-приложений с нуля, работа с Git. Стек: Языки программирования: Backend, Calculation - Java, DE Pipelines - Python, Frontend - JavaScript, Vue БД: PostgreSQL, Clickhouse, H2, Apache Trino, Apache Iceberg Брокеры сообщений: Apache Kafka Распределенные вычисления: Apache Ignite Мониторинг: Prometheus, Micrometer, OpenTelemetry, Grafana Контейнеризация: Kubernetes, Docker Инструменты качества кода: SonarQube, JaCoCo, CheckStyle Условия Трудоустройство в аккредитованную IT‑компанию ДМС со стоматологией и льготными условиями для членов семьи Работу в максимально уютном офисе в центре Москвы (ст. м. Савеловская), в Краснодаре или удаленно из других городов РФ, так же есть офисы в Санкт-Петербурге (ст. м. Балтийская) и в Иннополисе Корпоративные скидки от компании и партнеров, бесплатная подписка Магнит Премиум с повышенным кешбэком по программе лояльности М+ Ежегодная программа признания с ярким праздником и впечатляющим подарком Поддержку в развитии через обучение, конференции и митапы, а также программу для руководителей — Leadership club IT‑комьюнити — среда, где быстрее находишь решения, делишься практиками, пробуешь новые роли и растешь от эксперта в стекe до лидера инициатив Мы являемся партнером Минцифры России по проекту Национальная система подтверждения IT‑компетенций Работа над масштабными продуктами и проектами (Умный магазин, роботизация, беспилотность, GenAI и другое) Социально– психологическая поддержка от >370 специалистов по направлениям: юристы, психологи, врачи, финансовые и ЗОЖ советники

Location: Москва SberData отвечает за развитие платформы для работы с данными в Сбере. У нас свыше 230 Петабайт данных, около сотни продуктов и сервисов для клиентов. Мы создаем собственные сборки платформ в рамках вендорозамещения и активно сотрудничаем со всеми блоками Сбера для решения их бизнес-задач: наши пользователи сделали уже свыше 6500 витрин. SberData внедряет лучшие практики работы с данными, снижает стоимость хранения данных, повышает скорость получения данных, внедряет AI-технологии. Нашими решениями пользуются свыше 30 тыс человек. Технологический стек: Python (FastAPI / Django), Redis, PostgreSQL, Docker, CI/CD (GitLab CI/Jenkins или аналоги), REST API. Обязанности ### Задачи * разработка и развитие backend-сервисов на Python * работа с базами данных * участие в архитектурных решениях и выборе технических подходов * взаимодействие с аналитиками и другими командами. Требования ### Требования * уверенный опыт backend-разработки на Python от 3-х лет * хорошее знание SQL и понимание работы с данными * опыт проектирования и разработки API * опыт контейнеризации и сборки сервисов: Docker, CI/CD * понимание принципов построения микросервисной архитектуры * умение разбираться в существующем коде и улучшать его * опыт работы Jira, Confluence. ### Будет плюсом * опыт работы с BI-инструментами (Superset, Qlik, Tableau) * понимание ETL / data pipelines * опыт работы с Kafka или другими брокерами сообщений * опыт участия в миграциях или рефакторинге легаси-систем * опыт работы в enterprise или интеграционных проектах. Условия ### Мы предлагаем * комфортный современный офис в Москве: БЦ Даниловский форт, рядом с М.Тульская, Верхние котлы * возможность выбрать удобный график – офис/гибрид * 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: — Разработка функциональности передовой системы хранения данных (СХД) с нуля на современном технологическом стеке. — Реализация API для управления данными и учётными записями. — Взаимодействие с фронтенд-инженерами и смежными командами, занимающимися протоколами доступа к данным и ядром СХД. Требования: — Опыт программирования на Go. — Опыт разработки REST API (коммерческий или pet-проект, на любом языке). — Опыт работы с PostgreSQL, включая разработку, оптимизацию запросов и миграцию схемы. — Базовые знания Linux (shell, systemd, журнал). — Опыт работы с Git. — Знание английского языка на уровне чтения технической документации. — Будет плюсом опыт написания юнит- и компонентных тестов, работы с моками. — Опыт работы с gRPC API. — Навыки разработки спецификации OpenAPI. — Знакомство с Python. — Понимание принципов современной фронтенд-разработки. — Глубокое понимание конфигурации сетей Linux.

Задачи: — Разворачивание компонентов в Kubernetes с использованием Helm и операторов. — Внедрение GitOps-процессов для синхронизации состояния контура с git. — Сопровождение CI-пайплайнов обучения и инференса моделей. — Настройка MLOps-контура, включая MLflow и хранилища артефактов. — Поднятие сервисных зависимостей, таких как PostgreSQL и Kafka. — Построение системы observability на базе VictoriaMetrics и Grafana. — Настройка управления доступом через Istio и OIDC-провайдеры. — Обеспечение соответствия требованиям информационной безопасности. — Разбор инцидентов платформы и сопровождение запуска моделей в продакшн. Требования: — Опыт самостоятельного вывода компонентов в промышленный контур. — Глубокое знание Kubernetes, включая операторов и RBAC. — Практический опыт внедрения GitOps и CI/CD-процессов. — Понимание полного цикла MLOps от обучения до serving. — Опыт работы в банке или в контуре с высокими требованиями к безопасности. — Уверенное владение Linux и навыки диагностики систем.

Задачи: — разработка решений на Python для обработки и преобразования данных; — построение автоматизированных workflow с использованием Apache Airflow, включая планирование, управление зависимостями, мониторинг и обработку ошибок; — создание и поддержка Docker-окружений для воспроизводимого выполнения задач; — интеграция источников данных, API и вычислительных инструментов в автоматизированные процессы; — повышение надёжности, масштабируемости и сопровождаемости пайплайнов через тестирование, логирование и оптимизацию производительности; — сотрудничество с инженерными и научными командами. Требования: — сильные навыки программирования на Python и опыт разработки решений для обработки данных; — практический опыт работы с Apache Airflow или аналогичными оркестраторами; — опыт с Docker и контейнеризацией; — практический опыт с PostgreSQL и/или Snowflake; — понимание ETL/ELT-процессов, интеграции данных и автоматизации workflow; — умение разбираться в сбоях пайплайнов и строить надёжные сопровождаемые решения. Плюсом будут: — опыт с другими оркестраторами; — знакомство с AWS; — опыт проектирования и интеграции API; — знание Kubernetes и GitOps; — опыт разработки AI-приложений; — бэкграунд в life sciences, вычислительной химии, биоинформатике или поиске лекарств. Условия: — работа удалённо; — полная занятость; — сотрудничество по B2B-контракту с выплатами в USD или EUR либо по трудовому договору.

We're looking for a hands-on AI Engineer to take ownership of the architecture and development of our autonomous agent system. You'll lead the technical direction of the platform, building multi-agent orchestration systems, self-improving agent harnesses, and AI-powered backend services.

Location: Chicago, IL or Remote CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy , creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at www.cccis.com . The Role As a Senior AI Engineer you will own LLM-powered systems and agentic workflows for our customers. These systems automate the routine parts of a claim and guide customers on the rest, so they have to earn that trust with a measured accuracy you can defend as models change and usage grows. Agents run as steps inside deterministic workflows, and privacy and security are design baselines, not review gates. Agentic coding tools are how you move fast. What you add is what they are worst at: system architecture, code quality, security, and the debugging nobody else gets to the bottom of. You own a product area end to end and define the eval bar it ships against. Salary range is: $180,000 - 225,000 This position is bonus eligible. Key Responsibilities: Own the delivery of LLM-powered systems in Python and TypeScript, from an ambiguous customer problem, scoped with product managers and data scientists, through production operation. Set the evals and guardrails strategy for your area: what gates a release, what production signals the team watches, and how a change is simulated against historical claims before it ships. Raise the bar for how the team works with agentic coding tools: sharpen the specifications, instruction files, hooks, and permission policies they run under, and hold generated code to the same review standard before it merges. Design the NLP pipelines that turn unstructured claim data into structured data customers can act on, choosing where semantic search, classical NLP, or an LLM fits. Build and operate durable, event-driven, multi-tenant systems in which agents run as steps inside deterministic workflows, designing their failure modes, replay semantics, and cost profile before they show up under load. Own tracing and audit for your area: every model call and agent step recorded, so any recommendation can be reconstructed and cited back to its sources by on-call and auditors alike. Set the privacy and security baseline every system in your area starts from: tenant isolation, least-privilege access for agents and their tools, redaction, retention, and what data may reach a model provider. Author the design documents for complex systems to get feedback and buy-in, review other engineers' designs and code with the same care, and mentor the engineers in your area. Take part in a shared on-call rotation for the systems you own. Requirements: 6+ years of professional software engineering experience, including an LLM-powered system you architected, shipped to external customers, and carried through at least one model or prompt migration. Python and TypeScript at the level of setting a team's conventions: the async model, typing strictness, and test strategy for a shared codebase, plus a performance problem you profiled and fixed. An evals and guardrails strategy you set for a product area others built in: where human approval was required, and how production corrections re-entered the evals. A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work, plus changes you turned back, and why. Pipelines you designed that blend LLMs, semantic search, and classical NLP, including a retrieval design you can defend and a case where a classical technique beat an LLM on cost, latency, or reliability. Durable, event-driven systems you designed with deterministic orchestration around non-deterministic model steps: compensating actions, idempotency, backpressure, and event-sourced replay. Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made. Systems architected and operated on Azure or AWS, with CI/CD and infrastructure as code, and hands-on time with a durable workflow engine such as Temporal or the Durable Task Scheduler. Technical design documents you have authored for systems that span more than one team, used to get feedback and buy-in before building, and that those teams then built to. Clear writing and discussion for technical and non-technical audiences: drawing out a customer's real problem and explaining the trade-offs back to them. Even Better if You Have: React and TypeScript experience, so you can deliver a full-stack feature end to end, especially chat, streaming, and citation-heavy AI experiences. Experience with agent frameworks, LangGraph, PydanticAI, and the Microsoft Agent Framework among them, and with the ways agents reach their tools: the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices. Experience with LLM observability and evaluation tooling such as LangSmith, Arize, or Braintrust, and with OpenTelemetry-based tracing. Experience designing A/B tests for AI features. Exposure to the insurance, claims, or automotive repair domains. What Success Looks Like: In your first six months, every model change in your area is gated by evals you designed, regressions are caught before a customer sees them, and you can show the accuracy number held or moved. You are trusted with the high-stakes, ambiguous problems, and you turn them into a roadmap, a shipped system, and a number you can put in front of a customer. You are energized by what agentic coding tools make possible. Your team ships more than its headcount suggests, and your specifications and reviews are why the output survives production. You have a passion for systems that last: the ones you design have their failure modes understood in advance, and when one fails anyway, the trace says exactly where. Privacy and security reviews of systems in your area find nothing that was not already designed in. Standards you set for evals, reviews, and design documents outlive the project they started on. Engineers you mentor ship LLM-powered features with evals and guardrails in place without your direct involvement. You enjoy getting a product manager, a data scientist, and a customer's team into one room and coming out with a single agreed scope, and you can argue a position without needing to win it. You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued. Interview Policy & Privacy Notice: A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available HERE . About CCC's Commitment to Employees: CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most. At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success. CCC offers competitive compensation and benefits to support you and your families, including: 401K Match Paid time off Annual Incentive Plan Performance Bonus Comprehensive health insurance Adoption Assistance Tuition Reimbursement Wellness Programs Stock Purchase Plan options Employee Resource Groups For more information about our benefits, please check out our careers site . Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture here

Location: Chicago, IL or Remote CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy , creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at www.cccis.com . The Role As an AI Engineer you will build and ship LLM-powered features and agentic workflows for our customers. These features automate the routine parts of a claim and guide customers on the rest, so they have to earn that trust with measured accuracy, not a convincing demo. Agents run as steps inside deterministic workflows, and privacy and security are design baselines, not review gates. Agentic coding tools are how you move fast. What you add is what they are worst at: system design, security, and hard debugging. You own features end to end. Salary range is: $170,000 - 195,000 This position is bonus eligible. Key Responsibilities: Ship LLM-powered features and agentic workflows in Python and TypeScript, from a problem scoped with product managers and data scientists through production traffic, and help set the metrics you will be measured against. Write the evals, guardrails, and feedback loops that make your features trustworthy, and hold them to explicit token and latency budgets. Use agentic coding tools every day, and own the review of what they produce: catch the correctness, security, and design problems in generated code before you open the pull request. Maintain and extend the NLP pipelines that turn unstructured claim data into structured data customers can act on, blending semantic search, classical NLP, and LLMs. Build and operate durable, event-driven services in which agents run as steps inside deterministic workflows, with checkpointed model outputs so a retry does not re-invoke a completed LLM step. Trace every model call and agent step so a recommendation can be reconstructed and audited, with citations back to the source documents, and wire that tracing into your alerts. Model and query claims data across relational, document, and graph stores. Design privacy and security in from the start: tenant isolation, least-privilege access for agents and their tools, and a clear rule for what data may reach a model provider. Write a technical design document before any significant change, and use it to get feedback and buy-in from the team before you build. Take part in a shared on-call rotation for the services you build. Requirements: 3+ years of professional software engineering experience, including at least one LLM-powered feature you shipped and then operated in production. Python and TypeScript: typed, tested, async code in both, and real depth in one. Evals you have designed for LLM output, plus guardrails you have shipped. A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work. Pipelines that blend LLMs with semantic search and classical NLP: structured output, tool calling, embedding-based retrieval, and a case where a classical technique beat an LLM. Services built on message- or event-driven architectures, including long-running workflows with retries, idempotent handlers, and event-sourced state, plus an LLM or agent step you ran inside one. Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made. Backend services built and operated on Azure or AWS, and exposure to a durable workflow engine such as Temporal or the Durable Task Scheduler. Technical design documents you have written to get feedback and buy-in from a team before building, and that the team then built to. Clear writing and discussion for technical and non-technical audiences, and code review you can give as well as take. Even Better if You Have: React and TypeScript experience, so you can deliver a full-stack feature end to end. Chat, streaming, and citation-heavy AI experiences especially. Experience with CI/CD pipelines and infrastructure as code such as Terraform or Bicep. Experience with agent frameworks, LangGraph and the Microsoft Agent Framework among them, and with the ways agents reach their tools: the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices. Experience with LLM observability and evaluation tooling such as LangSmith, Arize, or Braintrust, and with OpenTelemetry-based tracing. Experience designing A/B tests for AI features, or what-if simulations that replay historical claims through a proposed change before it ships. Exposure to the insurance, claims, or automotive repair domains. What Success Looks Like: In your first six months you ship an LLM-powered feature, its evals run in CI, and you can name the metric it moved. When a model migration or prompt change causes a regression, the evals you wrote catch it before a customer does. You take ownership from concept to production with light direction, asking the right questions early. You care that things hold up: the services you build survive retries, partial failures, and model migrations without incidents a customer can see. When something goes wrong in production, the trace tells you which step and which model call, and you can show an auditor the same thing. Privacy and security reviews of your features find nothing that was not already designed in. You enjoy the craft, and it shows: engineers pick up your patterns without being told to. You enjoy the back-and-forth that gets a feature scoped, and you can argue a position without needing to win it. You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued. Interview Policy & Privacy Notice: A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available HERE . About CCC's Commitment to Employees: CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most. At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success. CCC offers competitive compensation and benefits to support you and your families, including: 401K Match Paid time off Annual Incentive Plan Performance Bonus Comprehensive health insurance Adoption Assistance Tuition Reimbursement Wellness Programs Stock Purchase Plan options Employee Resource Groups For more information about our benefits, please check out our careers site . Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture here

Location: Brazil, Colombia We are looking for a motivated Senior Software Engineer (Java) willing to continuously improve the newly developed system and respond to production incidents. If you're interested in more than just writing code, and want to build technical solutions that unlock new opportunities for users in a live system processing thousands of orders, then you are exactly who we're looking for. Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. About the Client The American memorabilia manufacturer is primarily known for producing yearbooks and class rings for high schools and colleges. The company also produced photobook products for Disney’s PhotoPass photography service at theme parks and resorts. In addition to its headquarters near Minneapolis and operational offices in Owatonna, Minnesota, the customer has facilities throughout the United States. What You’ll Do Develop and Review code and share feedback to keep our quality high Collaborate with cross-functional teams to analyze, design, and ship new features Participate actively in discussions, presentations, and decisions about back-end development Tackle bugs and address production issues Collaborate in an Agile team where ideas move fast and learning never stops What You Bring Experience in Java programming language Solid background in REST, Spring Boot, security, Kafka, Elasticsearch or SOLR, AWS Solid understanding of Microservice architecture, Design Patterns, Being able to develop sustainable and long-term solutions, explain pros and cons. Strong troubleshooting skills, understanding performance optimization Competency in JPA and writing complex SQL queries in PostgreSQL Knowledge of using IntelliJ, Git(GitHub and GitLab), JIRA, Docker, Maven Proactive team player In-depth understanding of SDLC and CICD processes Availability to work till 3 pm CST Nice to have Experience with e-commerce, preferably Broadleaf Commerce English level Upper-Intermediate Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more Reasonable accommodations are available to enable individuals with disabilities to perform essential functions Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs Compensation details are shared with candidates at the early stage of the recruitment process. The offer is not binding until a signed contract is in place. Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. International projects In-office, hybrid, or remote flexibility Medical healthcare Recognition program Ongoing learning & reimbursement Well-being program Team events & local benefits Sports compensation Referral bonuses Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Location: New York The Role As Consumer Engineering Leader, you’ll be the engineering counterpart to our Consumer Product Leader. Together you’ll own a simple question: How can we extend our product suite to be integrated deeper with our customers’ financial lives? Engineering leadership at Taptap Send is hands on. You’ll be building POCs while managing/coaching a team of super passionate, high caliber engineers. We are looking for someone who finds themselves on the cusp of product and engineering and is excited to shape the next generation of products at a company with millions of customers. The mandate is to move fast and autonomously, understand our customers, build new products they love, and become the financial home for the immigrant communities we serve. Key Responsibilities - Own the Outcomes: Partner with Product to set and hit targets on adoption, retention, and how well our products serve the range of a customer’s financial life. You’re accountable for how well these products work, not just for shipping them. - Run the Experiment Loop: Take ideas from hypothesis to live test in weeks, not quarters. Build POCs yourself. Instrument everything. Read the data honestly and recommend, kill, or scale. - Spot the Opportunities: Bring your own ideas. You should be looking at our customers, our data, and the market and arriving with a point of view on the next unmet need worth solving. - Ship the Winners: When a bet proves out, lead the work to harden it and get it into the core app at production quality with reliability, security, and compliance standards intact. - Stay Hands-On: Contribute code. You set the technical direction for consumer product engineering and you’re in it with the team. - Build and Lead a Small, High-Leverage Team: Hire, coach, and retain product-minded engineers who thrive on ambiguity and speed. - Work Across the Company: Partner with teams across the business to get experiments live and learnings shared, building on our existing systems and creating new ones that other teams can plug into. What We’re Looking For - Product-Minded Engineers: Your background is building user-facing products and the services behind it. You’re comfortable owning a feature end-to-end, from backend through to what the user touches. - Track Record of Rapid Experimentation: You can point to things you built in weeks that tested a real hypothesis, and to things you killed. Candidates whose experience is entirely long-horizon builds won’t be a fit. - 0 to 1 Experience: You’ve done your best work at Series B-E companies or standing up new products/businesses within a larger company. You know what it’s like to build with real constraints and real growth pressure. - Comfort with Compliance: You’ve shipped in regulated environments and treat compliance as a design constraint to build around from day one, not a hurdle at the end. - Commercially Grounded: You reach for the business case before the architecture diagram. You can judge whether an idea is worth the company’s time, and you hold a high engineering bar while doing it. - Leadership Range: You can lead and grow a team without stepping away from the technical work. This isn’t a role for someone who has moved fully into management. Our Stack TapTap Send is an AWS-first, polyglot engineering organisation. Across a small set of major product and platform systems, we use Kotlin/Spring Boot and Python/FastAPI for backend services, React Native/TypeScript for mobile, React/TypeScript for web, PostgreSQL for transactional data, and Redshift + dbt for analytics. You don’t need to have used all of this, but you should be able to get productive in it quickly. About Us   We’re building the world’s leading cross-border fintech for emerging markets - empowering families, fuelling local economies, and changing how millions access financial services.   Since our launch in 2019, we have transformed how money moves across borders with our operations spanning 6 out of 7 continents and covering both the busiest and most underserved (remittance) corridors. We tapped into a massive shift - from banks to phones - bringing digital finance to places where traditional systems never reached. The next stage of growth will fuel a network of services and products especially designed to make money more accessible to diaspora communities including local cards, and additional savings and payments features.   We’re growing fast, backed by world-class investors, and scaling a product that blends real world impact with cutting edge fintech innovation.   Here’s a little more: - Founded by Harvard grads and 3-time founders who previously built Segovia (acquired) and GiveDirectly (>$300M revenue, fastest-growing NGO in the world) - Backed by top investors including Spark Capital, Canaan, Reid Hoffman, Breyer Capital, Unbound, Wamda, and more - Built by global top performers from Bain, Google, McKinsey, Uber, Checkout, Bolt, and beyond - we move fast, stay humble, and care deeply about our mission - Truly global team - 250+ people, 50+ nationalities, 50+ languages - Guided by our values - ownership, impact, humility, and heart - in deed, not just word   TAPTAP VALUES https://www.taptapsend.com/our-values Impact first Team next Accept reality Propose solutions Win with grit Be proactively candid, with yourself and others Love the particular Own it Create positive energy Maybe, even have fun   Taptap Send is an equal opportunity employer dedicated to building an inclusive and diverse workforce. All employment decisions are decided on the basis of qualifications, experience and business need. We strongly encourage applications who are members of underrepresented communities to apply. If you require reasonable adjustments to be made during the recruitment process, please do not hesitate to let us know. Any information you provide us in this respect will only be used to accommodate your requirements. Note: we recognize imposter syndrome is real - any candidate that does not perfectly fit every characteristic of this role is still strongly encouraged to apply.

Location: Москва Workplace: Гибрид, Удаленно, Офис Объединённая компания Wildberries и Russ — это международная технологическая компания, образованная в результате слияния двух лидеров рынка — IT-компании Wildberries и оператора наружной рекламы Russ. Обязанности анализ данных и проверка гипотез для решения бизнес-задач; разработка и валидация ML-моделей (регрессия, классификация, кластеризация, ансамбли) feature engineering: подготовка и проектирование признаков; построение интерпретируемых моделей и explanation-инструментов (XAI); подготовка прототипов моделей и передача их в пилотирование / промышленную эксплуатацию; визуализация результатов, подготовка презентаций и консультирование заказчика. Требования опыт от 5 лет на позиции Data Scientist / аналитика данных; уверенный Python (scikit-learn, pandas, numpy), SQL, опыт с PostgreSQL и ClickHouse; понимание валидации моделей и борьбы с переобучением; навыки визуализации данных и подготовки презентаций; математическое моделирование, статистика, системный анализ. Условия Обучение и развитие: языковые клубы, собственный корпоративный университет, программы развития управленческих навыков и многое другое; Благополучие сотрудников: корпоративный пакет ДМС со стоматологией, корпоративный спорт, консультации психолога и дополнительные возможности аккредитованной IT-компании; Множество сообществ: клуб спикеров, футбола, йоги, шахмат и т.д.; Забота о семьях: создаем условия, в которых легко сочетать карьеру и заботу о близких – от гибкого подхода до масштабных проектов для детей сотрудников; Скидки и партнерские программы: на обучение, страхование, покупки и многое другое; Комфортная рабочая среда: бесплатное питание в офисе, современные офисы рядом с метро, корпоративная техника и портал для сотрудников.

Конфигурация, настройка и администрирование серверов под управлением ОС семейства Linux, в том числе с технологиями оркестрации и контейнеризации; Оптимизация работы ОС Linux под различный стек задач;

Location: Москва Наша команда работает над флагманским продуктом компании - программой долгосрочных сбережений, которая является основным продуктом Негосударственного Пенсионного Фонда. Мы ищем возможность усилить команду за счет опытного Java-разработчика уровня Senior. Первый этап отбора на эту вакансию – общение с AI-рекрутером. После отклика вам на почту и в чат на платформе HeadHunter придет приглашение пройти первичное интервью с ГигаРекрутером в Telegram. Диалог займёт примерно 10 минут. Его задача — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. ГигаРекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным! Обязанности * Управление командой разработки ИС: планирование ресурсов, распределение задач, контроль сроков, качества и бюджета; проведение 1:1, оценка эффективности, наставничество; * Участие в развитии архитектуры: проектирование и контроль реализации API, микросервисов, интеграций и CI/CD; обеспечение доступности, масштабируемости и отказоустойчивости; * Организация процессов разработки: ведение бэклога, планирование спринтов, контроль code review, тестирования (unit/integration), баг-трекинга и управления релизами; * Обеспечение качества кода и архитектуры: организация аудитов, выявление уязвимостей и несоответствий требованиям безопасности, координация исправлений; * Внедрение SDD и AI SDLC: адаптация генеративных инструментов для кода, тестов и документации, автоматизация рутинных задач, повышение производительности команды; * Координация взаимодействия с frontend-разработкой, тестированием, аналитиками, DevOps, отделом безопасности и инфраструктурными подразделениями; управление ожиданиями стейкхолдеров; * Контроль DevOps-решений и observability: централизованное логирование, метрики, трассировка, алертинг; * Участие в согласовании технических решений, оценке трудозатрат, рисков и сроков; проведение техсобеседований и участие в найме; * Обеспечение исполнения заявок и соблюдения стандартов работы с ИТ-ресурсами, принятых в Фонде; * Взаимодействие с отделом безопасности по вопросам соответствия ПО текущим стандартам; * Управление инцидентами: организация диагностики, устранение узких мест, оптимизация производительности, проведение ретроспектив и внедрение улучшений. Требования * Опыт управления: Руководство командой разработки от 3 лет, общий опыт Java-разработки от 5 лет; * Управление проектами: Опыт планирования, оценки сроков, управления рисками и бюджетами в проектах по разработке высоконагруженных Spring Boot приложений; * Опыт работы с архитектурой: Проектирование модульных, масштабируемых систем с использованием DDD, Clean Architecture, Event Sourcing. * Опыт построения CI/CD, опыт с Docker, Kubernetes (Helm, service mesh), GitOps; * Опыт работы с базами данных: Глубокое владение SQL и NoSQL (PostgreSQL, MongoDB), опыт оптимизации, проектирования схем, шардирования и партиционирования. * Практический опыт с Kafka, настройка потоков данных, гарантии доставки. * Опыт настройки мониторинга (Prometheus/Grafana, Jaeger/OpenTelemetry) и управления секретами (Vault/K8s Secrets), понимание OAuth2/OIDC. Условия * Гибридный формат работы (современный офис в Москве, м. Шаболовская); * Льготные ипотечные условия кредитования; * Подписка Прайм с возможностью совместного использования на трёх близких; * ДМС с первого дня и скидки на страхование для близких; * Корпоративная пенсионная программа; * Детский отдых и подарки за счет Компании; * Обучение за счет Компании: онлайн курсы, неограниченный доступ к библиотеке и обучение на базе Корпоративного университета, тренинги, митапы и возможность получить новую квалификацию.

Workplace: Удалённый, Офис, Гибридный Ищем талантливого Kotlin-разработчика, который поможет нам ускорить создание и масштабирование умного финтех-сервиса на базе AI-агентов. Вам предстоит участвовать в сквозной разработке: от интеграции AI‑технологий до создания мобильного интерфейса и написания бэкенда. Мы — стартап‑команда в сфере Финтеха внутри Яндекса. Наша цель — создавать прорывные финансовые сервисы на стыке передовых технологий и AI. Сейчас наш ключевой фокус — запуск и масштабирование agentic-finance-продукта (умного финтех-сервиса на базе AI-агентов). Ищем талантливого Kotlin-разработчика, который поможет нам ускорить разработку и вывести продукт на новый уровень. Вам предстоит участвовать в сквозной разработке: от интеграции AI‑технологий до создания мобильного интерфейса и написания бэкенда. Дух стартапа в нашей команде означает, что мы ценим скорость, гибкость и готовность экспериментировать. При этом вы будете работать в надёжной экосистеме Яндекса с доступом ко всем её ресурсам и возможностям. Наш технологический стек: * Mobile: Compose Multiplatform, Swift * Backend: Kotlin, Spring Boot * AI: интеграция с LLM (YandexGPT, Eliza), построение агентных сценариев * Данные и инфраструктура: YDB, PostgreSQL Обязанности Сквозная разработка Вам предстоит проектировать гибкую архитектуру и писать код для бэкенда, мобильных интерфейсов и AI-компонентов. Быстрый запуск фич Вам предстоит собирать и тестировать MVP продуктовых гипотез в сжатые сроки, оперативно выводя их на реальный рынок. AI-driven-разработка Вы будете активно использовать LLM и AI-агентов для автоматизации и кратного ускорения процессов написания кода. Техническое лидерство Нужно будет приносить идеи для оптимизаций, глубоко погружаться в продукт и отвечать за широкий круг инженерных задач. Больше о бэкенде в Яндексе — в канале Yandex for Backend Требования * Занимались коммерческой разработкой бэкенда от пяти лет * Уверенно используете AI‑агентов для написания кода: понимаете, как выстроить процесс взаимодействия с ними для разных типов задач, умеете оптимально распределять ресурсы * Умеете прорабатывать архитектуру систем с учётом перспектив масштабирования * Имеете практический опыт быстрого запуска новых фич и работы в режиме MVP * Предлагаете идеи по оптимизации процессов и улучшению продукта * Гибко мыслите и готовы адаптироваться к меняющимся приоритетам проекта * Готовы брать на себя ответственность за широкий круг задач и погружаться в незнакомые сферы * Нацелены на интенсивную работу и быстрый результат