Вакансии

Задачи: — Создавать рекламные впечатления и разрабатывать шаблоны для веб-приложений Reddit, которые повышают производительность и функциональность рекламы. — Сотрудничать с командами по продукту, дизайну и инженерии для инноваций и реализации простых решений для сложных задач. — Участвовать в полном цикле разработки: проектирование, разработка, контроль качества, эксперименты, анализ и развертывание. Требования: — Опыт работы от 3 лет в веб-инжиниринге. — Уверенное владение TypeScript и JavaScript. — Готовность справляться с задачами по созданию данных, высокоотзывчивых и отказоустойчивых приложений. — Опыт работы с лучшими практиками проведения тестирования, планированием качества кода/шаблонов, наблюдательностью. — Умение проводить тщательную проверку кода и принимать обратную связь. — Опыт использования инструментов GenAI для повышения производительности программной инженерии. — Отличные коммуникативные навыки для сотрудничества в полностью удаленной среде и обсуждения сложных тем с техническими и нетехническими аудиториями. Предпочтительные квалификации: — Опыт работы в области рекламных технологий. — Опыт работы на сайтах, ориентированных на потребителей (высокое качество производства в масштабе). Условия: — Полный рабочий день. — Возможность удалённой работы. Технологии, используемые в команде: TypeScript, HTML, CSS, Go, React, Thrift, gRPC, Kubernetes, Docker, Codex, Cursor.

Location: Москва Ищем Системного аналитика в команду разработки AI Бизнес-помощника внутри интернет-банка для предпринимателей (СберБизнес). Цель нашего Помощника- взять на себя рутинные банковские операции, помочь подобрать сервисы, подходящие конкретному пользователю, подсказать возможные векторы развития его бизнеса на основе предыдущих результатов работы. Взаимодействие пользователя с Помощником происходит через чат, под капотом которого - LLM, RAG, MCP и, конечно, классические прикладные сервисы. Система семантически различает сотни смежных бизнес-сценариев, извлекает критическую информацию и подключает профильные GenAI-инструменты для выполнения операций. Над чем предстоит работать в ближайшее время: * научить систему лучше запоминать и использовать факты о пользователе, чтобы подстраиваться под его особенности и контекст * развивать платформу для агентов, которые действуют на опережение — сами инициируют полезные операции или предупреждают о важных событиях без явного запроса * усиливать безопасность и отказоустойчивость системы * совершенствовать архитектуру, чтобы компоненты и процессы координировались быстрее и точнее. Обязанности * выявление требований, разработка и согласование требований к программному обеспечению * управление требованиями на всём жизненном цикле разработки ПО * подготовка спецификаций и написание технической документации * предложения по улучшению существующих процессов или созданию новых * коммуникация между командами: координация взаимодействия внутри своей команды и со смежными подразделениями для эффективного выполнения поставленных задач * проработка архитектурных решений  * декомпозиция и постановка задач разработчикам * помощь в подготовке тест-кейсов * активное участие в планировании спринтов и продуктовых бэклогов (Agile/Scrum, Kanban). Требования * опыт описания и моделирования бизнес-процессов с использованием нотаций UML (sequence diagram) или BPMN, формулировки системных и функциональных требований * опыт написания технической и пользовательской документации * опыт проектирования реляционных баз данных или уверенное знание принципов проектирования * опыт проектирования интеграционных взаимодействий с нуля (REST, Kafka), базовые знания SQL и наличие опыта работы с базами данных * опыт работы с инструментами тестирования: Insomnia, Postman * уверенное владение инструментами для анализа и документирования: системы управления требованиями (Jira, Confluence, YouTrack), инструменты для построения диаграмм (draw.io, Miro, Lucidchart, PlantUML) * понимание полного жизненного цикла разработки ПО (SDLC) и практический опыт работы в Agile-командах. Будет преимуществом: * опыт работы в банковской сфере или участие в fintech-проектах * навык написания скриптов на Python для автоматизации рутинных задач (парсинг логов, сравнение данных, предварительная обработка) * теоретическое или практическое представление о векторном представлении данных (эмбеддингах) и методах кластеризации, понимание областей их применения (поиск похожих объектов, сегментация, классификация) * опыт проектирования систем с окрестратором или мультиагентных систем * формализация, постановка на мониторинг и отслеживание метрики качества ответов агентов * опыт применения современных LLM-инструментов. Условия * комфортный современный офис в Москве рядом с м. Кутузовский * 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.

Создавать и оптимизировать подходы к оценке качества моделей и AI-пайплайнов (RAG, LLM, OCR). Построение online/offline метрик качества, написание методологий оценки для мониторинга качества и регрессионного тестирования.

Location: Москва Мы развиваем продажи технологических продуктов и сервисов экосистемы Сбера корпоративным клиентам. Наша цель — помогать крупнейшим, крупным и средним компаниям решать бизнес-задачи с помощью генеративного ИИ, облачных технологий, интеллектуальной автоматизации и аналитических решений. Ищем специалиста, который сочетает коммерческое мышление и консалтинговый подход к работе с клиентами. В этой роли важно глубоко погружаться в бизнес клиента, выявлять задачи и точки роста, формировать гипотезы применения технологий и превращать их в конкретные коммерческие возможности. Специалист сопровождает клиента на всём пути — от выявления потребности и разработки решения до заключения сделки и координации внедрения. Для этого необходимо понимать возможности современных технологий, ориентироваться в сценариях их применения и уметь обосновывать бизнес-ценность предлагаемых решений. Обязанности ### **Чем предстоит заниматься:** * развивать клиентские отношения и продажи: взаимодействовать с клиентскими менеджерами корпоративного блока Сбера, организовывать совместную работу с клиентами, находить возможности для продаж и кросс-продаж. Проводить в среднем около 5 встреч с клиентами в неделю * анализировать бизнес клиентов и формировать предложения: погружаться в бизнес-модель и процессы компаний, выявлять потребности и точки роста, формировать гипотезы применения технологий и подбирать решения с учётом задач клиента и ожидаемого бизнес-эффекта * продвигать сделки: презентовать решения, квалифицировать коммерческие возможности, привлекать профильных экспертов и координировать подготовку предложений, согласование условий и заключение договоров * координировать внедрение: обеспечивать взаимодействие клиента с командами компаний экосистемы, сопровождать реализацию комплексных проектов и развивать возможности для повторных продаж. Работать с клиентским портфелем, обеспечивая реализацию сделок и/или проектов как минимум с 20 клиентами в год. Требования ### **Для нас важно:** * опыт работы с корпоративными клиентами в B2B-продажах, бизнес-девелопменте, технологическом пресейле или сопровождении внешних клиентских проектов * опыт продаж ИТ-продуктов, программного обеспечения и цифровых сервисов * опыт работы в крупных российских корпорациях, банках или технологических компаниях * практический опыт организации клиентских встреч и переговоров, выявления потребностей и продвижения коммерческих инициатив. * развитые коммуникативные навыки, умение договариваться, выстраивать отношения и влиять на решения собеседников * коммерческое мышление, аналитические способности и ориентация на результат * базовое понимание современных цифровых технологий, особенно GenAI, ИИ и облачных решений; умение ориентироваться в сценариях их применения и объяснять бизнес-ценность * умение анализировать бизнес клиента, выявлять точки роста и связывать их с технологическими решениями * базовые навыки управления проектами и портфелями проектов Условия ### **Что мы предлагаем:** * комфортный офис рядом с м.Новослободская * ежегодный пересмотр зарплаты, квартальная и годовая премия * корпоративный спортзал и зоны отдыха * уникальная система обучения Сбера для профессионального и карьерного развития * расширенный ДМС и льготное страхование для семьи * 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 * корпоративная пенсионная программа.

Location: Singapore Workplace: Remote Coder is looking for a Senior Sales Development Representative (SDR) to fuel our growth by generating qualified pipeline for our Enterprise Account Managers. You’ll help bring Coder’s Environment-as-a-Service platform to some of the world’s largest companies that are adopting AI-driven development at scale. This role is all about creating opportunities: finding and engaging the right prospects, uncovering the pain points Coder can help with, and setting up qualification calls that set our EAMs up for success. You’ll play a critical role in driving Coder’s outbound motion and helping large organizations build software faster, more securely, and at scale through the collaboration of AI coding agents and human developers.   What you’ll do here - Generate qualified opportunities for EAMs through targeted outbound prospecting - Conduct multi-channel outreach across phone, email, and LinkedIn using tools like SalesLoft, Sales Navigator, ZoomInfo, 6sense, and Nooks - Research target accounts and key personas to craft personalized and value-driven messaging - Set up qualification calls for EAMs to run and advance through the sales cycle - Work closely with EAMs to strategize account outreach and hand off qualified opportunities seamlessly - Maintain accurate activity and lead data in CRM and engagement platforms - Collaborate with marketing to align messaging and campaigns to drive higher response rates - Stay sharp on developer tooling, platform engineering, and AI-driven development trends to speak credibly with prospects   What we’re looking for - Currently based in Singapore - 1-3 years in outbound SDR or BDR roles within SaaS or developer-focused technology companies - Proven ability to generate pipeline through outbound cold calling, emailing, and social selling - Experience with SalesLoft, LinkedIn Sales Navigator, ZoomInfo, 6sense, and similar prospecting tools - Strong written and verbal communication skills; able to clearly articulate technical value propositions - Grit, curiosity, and the ability to handle rejection while maintaining a positive, proactive mindset - Highly organized and self-motivated with a focus on measurable goals and continuous improvement - Eagerness to learn about developer tools, DevOps, platform engineering, and AI workflows   Bonus tacos if you have - (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!) - Prior experience selling into engineering or DevOps personas - Familiarity with AI and GenAI developer tools - Knowledge of open source ecosystems or cloud-native technologies - Experience collaborating closely with Account Executives in an enterprise sales motion ABOUT CODER Coder is the leading platform for AI development Infrastructure, enabling enterprises to securely run human and AI-driven development workflows in consistent, governed environments. Coder provides self-hosted, agent-ready workspaces that unify developer productivity and platform governance. With Coder, enterprises can confidently evolve from human-only development to AI-assisted and autonomous workflows, without sacrificing security, compliance, or performance. Learn more at coder.com http://coder.com. INTERVIEW PROCESS  We believe that the interview process should be transparent, consistent, and enjoyable. We value your time and hope to complete the interview process in two to four weeks, if schedules allow. Through your interviews, you will meet a mix of individual contributors, managers, and senior leaders. AI USE DURING THE INTERVIEW PROCESS As an AI company, Coder embraces the use of AI tools, and we want to be transparent about our expectations as you navigate our interview process. Not permitted: Using AI assistance during conversational interviews. Permitted: Using AI tooling for take-home assessments. Please flag where and to what extent it was used in your take-home. Your submission will not be penalized for using AI as long as it is done honestly. OUR USE OF AI IN HIRING We use AI tools to help manage our recruitment process efficiently and fairly. Specifically: - Ashby and Brainerr help us review inbound applications by surfacing candidates who best match the role requirements we've defined. This tool does not make hiring decisions; it helps our team prioritize which applications to review first. - Granola takes notes during our interview calls so our team can focus on the conversation with you. All hiring decisions are made by humans. Our team reviews applications, conducts interviews, and makes final selections. AI tools assist us but never replace human judgment, and these practices are conducted in compliance with applicable data protection, AI governance, and labor laws. Your data is not used to train AI models. In accordance with New York City Local Law 144, an independent bias audit has been conducted on "Automated Employment Decision Tools"; results are available for Ashby https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf. If you're applying for a role at Coder and have questions about how we use AI in our process, or if you'd like to request information about the data we collect, please contact careers@coder.com.   CODER IS A PROUD EQUAL OPPORTUNITY EMPLOYER We are committed to providing equal employment opportunities to qualified applicants and do not discriminate on the basis of race, color, ancestry, religion, sex, pregnancy, gender, gender identity, gender expression, sexual orientation, national origin, age, marital status, genetic information, disability, protected veteran status or any other characteristic protected by federal, state, or local laws.

Location: Montevideo, Uruguay; Remote.AR, Remote.LATAM-country; Remote.CO, Colombia; Rosario, Remote.LATAM-country We are looking for a hands on Middle MLE Infrastructure Engineer to strengthen a shared Data and AI platform. You will focus on execution across CI/CD standards, cloud resource management, identity and access security, observability, and reliable deployments that support other teams. The Shared Services Platform organization builds and operates the core environment for Data and AI products. You will work on a platform that standardizes CI/CD, security, observability, and cloud resource management so product squads can deliver on reliable infrastructure. Define and maintain homogeneous CI CD standards and pipelines for data and AI across teams. Manage cloud resources, capacity, and cost through provisioning, autoscaling, and optimization. Own identity and access management and centralized credential governance. Automate security policies through infrastructure as code and SecOps practices. Run vulnerability scanning and incident response playbooks. Build observability through metrics, dashboards, and proactive alerting for platform and products. Ensure reliable versioning and deployment standards across the platform. Act as a platform enabler for product squads on environment and product infrastructure. Proven experience as a Platform Engineer, DevOps Engineer, or MLOps Infrastructure Engineer. Experience with infrastructure as code using Terraform and configuration automation. Experience with Docker, Kubernetes, and autoscaling. Experience with CI CD tooling such as GitHub Actions and GitLab CI. Experience with Git workflows including GitFlow. Experience with Google Cloud Platform resource management, GCP IAM, billing, and cost control. Experience with observability tools such as Prometheus, Grafana, Datadog, or similar monitoring solutions. Experience with IAM, vulnerability scanning, data masking, and policy management. Ability to communicate effectively with technical and non technical stakeholders. Experience working in Agile environments. Fluency in Spanish. Exposure to MLOps platforms, model registry, and model serving infrastructure. Experience with FastAPI or Flask. Familiarity with BigQuery, pipelines, and lakehouse or warehouse environments. Familiarity with GenAI tooling such as LangChain and Agents.

Location: Belgrade, Serbia; Cluj-Napoca, Romania; Dnipro, Ukraine; Kharkiv, Ukraine; Krakow, Poland; Kyiv, Ukraine; Larnaca, Cyprus; Lodz, Poland; Lublin, Poland; Lviv, Ukraine; Odesa, Ukraine; Remote.BG, Bulgaria; Remote.GE, Georgia; Remote.PL, Poland; Riga, Latvia; Sofia, Bulgaria; Tbilisi, Georgia; Varna, Bulgaria; Warsaw, Poland; Wroclaw, Poland; Yerevan, Armenia We are looking for an AI Governance & Risk Analyst to support AI policy implementation, risk assessments, and governance activities across AI use cases. You will help define guardrails, support reviews, and improve oversight for AI systems and related vendors. This project supports the safe and practical adoption of AI capabilities within a logistics focused platform. You will help close governance gaps, guide risk tiering, and support controls for AI solutions throughout their lifecycle. Turn AI policies into practical local standards Fill policy gaps for agents, non human identities, and Superblocks with lightweight guardrails Run AI use case intake and risk tiering Guide DPIAs and vendor reviews Set agent boundaries for read and write scopes and human in the loop controls Define RAG data access tiers Check audit logging and the impact of vendor model updates Support AI solution lifecycle and decommissioning activities Experience with 2 to 4 years in IT risk, data governance, or information security compliance Experience working in a matrixed organization Understanding of GenAI basics Ability to work with stakeholders across multiple teams Experience with UK or EU DPIAs Experience with GCP governance Experience in logistics environments

Location: London, UK DataArt’s Travel, Transportation & Hospitality Practice is looking for a client-facing professional. The role connects advanced AI tools to real business impact and involves working with client account teams and the AI + Data Lab across 50+ active travel accounts to find high-value use cases, prototype fast, validate with stakeholders, and drive adoption from C-suite to delivery teams. The role covers the journey from prototype to production. You will define how solution quality is measured once a solution is live and design for the controls enterprise clients operate under. Lead ideation and scoping of AI and ML proofs of concept with client account leaders Prototype AI features such as copilots, NLP services, and recommender systems Own the full lifecycle from internal demo and stakeholder validation to client presentation and the path to production Direct internal teams to execute with clarity, velocity, and alignment Build GenAI applications using RAG variations, agentic and hybrid models, cloud AI services, LLM APIs, vector search, and agentic SDKs Integrate AI solutions with Snowflake and Databricks Define how solution quality is measured in production through evaluation sets, accuracy checks, groundedness checks, drift detection, human in the loop checkpoints, and audit records Define reusable AI building blocks and travel specific agent scaffolds for internal delivery practices Shape internal best practice for GenAI across delivery Embed AI into client products and operations for personalization, crew operations, service automation, disruption handling, post booking servicing, reconciliation, and refunds Run workshops with client teams and business leaders Act as a translator and evangelist for responsible AI adoption and ROI Hands on experience with AI services from at least one major cloud such as Azure, AWS, or GCP Experience designing and implementing RAG based applications Experience taking AI solutions beyond pilot into production Experience validating AI solution performance before go live and monitoring it after release Practical understanding of AI evaluation including defining workflow correctness, building test sets, and measuring accuracy and groundedness Strong background with Snowflake and or Databricks for data engineering and AI pipelines Proven success leading client facing proofs of concept or MVPs from inception to delivery at Director level or above Ability to turn ambiguous business goals into scoped, testable, and scalable initiatives Fluency in open source versus commercial model tradeoffs and cost efficient architecture Prior exposure to the travel, transportation, or hospitality sector Experience with vector databases Experience with context engineering Experience with orchestration frameworks such as LangChain or Semantic Kernel Familiarity with fine tuning and understanding of when it is worth the effort Experience with agentic loop engineering Experience with AI observability or evaluation tooling Awareness of responsible AI practices including fairness, explainability, and usage boundaries

Location: Ukraine; Poland; Romania; Spain; Portugal; Croatia At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed. We are looking for a Senior ML & AI Engineer to join us as part of our team. About the role PitchBook’s Machine Learning Engineer is responsible for using machine learning, statistical modeling, and natural language processing (NLP) to collect a high-volume of data for the PitchBook Platform and surface insights for the capital markets. This role will also serve as a resource and mentor for junior members of the team. A strong motivation to succeed is critical and everyone has the opportunity to shape the long-term direction of our team. About the project PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. Features of PitchBook: Advanced search / Discovery & insights / Company profiles / Workflow & efficiency / Financials and many more. Team 1 EM, 6 ML Engineers Work Environment The role offers a flexible work schedule, allowing you to adapt your working hours with the requirement to attend all team meetings. The team follows a Scrum-based Agile methodology. As a qualified expert, You will Work with GenAI & LLMs: Design, develop, and fine-tune generative AI models using transformer architectures. Implement advanced techniques to create practical solutions for real-world challenges. Use Modern Toolkits: Leverage frameworks like LangChain, LangGraph, and LangSmith to build automated pipelines and intelligent agents. Integrate these tools with vector databases for efficient similarity search and real-time analysis. Extract Data Insights: Process and analyze large volumes of unstructured data using embeddings and statistical modeling to identify meaningful insights. Build Scalable Systems: Collaborate with cross-functional teams to create production-grade ML systems that handle real-time, high-volume data processing. Mentor & Lead: Act as a mentor for junior team members and stay updated on trends in Agentic AI, transformer models, and generative systems. Collaborate & Communicate : Work with Product and Engineering teams to improve data management and support innovation. Present complex analyses clearly and effectively. Tech Stack & Focus Areas: Work with generative AI and transformer models, integrating frameworks like LangChain, LangGraph, and LangSmith to automate workflows and build intelligent systems. Use PyTorch, Scikit-Learn, and Spacy to build NLP pipelines. Implement vector databases for high-dimensional data embeddings and develop hybrid models to extract insights from diverse data sources. We’re looking for you if you have Educational Background: You hold a Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field. Experience: You bring 5+ years of production experience in the ML field, with a track record in developing transformer-based models and deploying them in scalable systems. Technical Expertise: Proficient in Python and machine and deep learning frameworks like TensorFlow, PyTorch, ScikitLearn, Spacy or other. Experienced in natural language processing and modern LLM based techniques. Experience with full ML lifecycle, data preprocessing, training, evaluation stages and monitoring techniques Skilled with SQL and data extraction methods. Innovative Thinker: You thrive on solving complex problems and are always exploring new trends in Generative AI. Collaborator & Communicator: You’re an excellent communicator able to collaborate and express your thoughts in a professional manner to team members, other engineering teams and stakeholders. Domain Knowledge: Exposure to financial services, investment banking, venture capital, or private equity is nice to have. Languages: English —Upper-Intermediate or higher; Ukrainian —fluent/native . What’s in it for You Reveal great tech solutions Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling client growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients. Experience an agile and flexible working environment Enjoy the freedom of fully remote work with a flexible working schedule. Empower yourself with a stable workload and a stable income, supported by provided laptops and licensed software. We focus on lasting cooperation and unite result-oriented individuals who stand on a high-performance approach to work. Embrace the opportunity for personal and professional growth Benefit from performance and merit reviews, elevate your skills with personal development plans, and individual learnings through the corporate library, public speaking support, and more. Be among like-minded people Work with a team of one mind who cares about what they do and how they do. Collaborate with top-notch experts who are always ready to help and support you through any challenges. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Feel supported by your HR, and take advantage of our referral bonus program. Interview steps Interview with the recruiter Technical interview (up to 90 min) System Design interview (up to 45 min) Behavioral Round with Product Manager (45 min) Final interview with Engineering Manager (30 min)

Location: Intellias Meet your recruiter Mariia Savchenko mariia.savchenko@intellias.com https://www.linkedin.com... Vacancy details AI/ML Engineering GenAI Engineer Strong Middle Romania Hybrid APPLY NOW REFER A FRIEND Intellias helps retailers deliver consistent, omnichannel experiences through technology. Join us to develop scalable solutions that drive performance and customer value What project we have for you We are looking for a hands-on AI Engineer to lead the technical design and delivery of enterprise AI agents and MCP-based integrations. The team will develop Model Context Protocol (MCP) services for local business applications and build AI agents that consume both these local MCPs and MCP services provided by a global platform team. The Senior AI Engineer will own solution design, support use-case discovery, provide technical leadership to the engineering team, and participate directly in implementation. What you will do Develop MCP servers/services for local applications . Expose application capabilities, data and business operations to AI agents through secure MCP interfaces. Integrate MCP services with existing REST APIs, databases and enterprise applications. Develop AI agents consuming both local and global MCPs . Implement agent instructions, tool calling, workflow logic and guardrails. Implement authentication, authorization and secure access to enterprise systems. Build reusable integration components and MCP tools. Perform end-to-end testing of agents and MCP integrations. Troubleshoot agent/tool interactions and integration failures. Monitor agent performance, reliability, latency and cost. Implement automated tests and CI/CD. Work closely with the Senior AI Engineer, global AI/platform teams and application owners. What you need for this Required skills Strong Python development skills. Backend or integration engineering experience. REST API development and integration. Microsoft Azure experience. Experience with LLM applications, tool/function calling or AI agents. OAuth 2.0 / Microsoft Entra ID or similar identity technologies. SQL and JSON. Git and CI/CD. Understanding of software engineering practices, testing and production support. English communication skills. Strong advantage Model Context Protocol (MCP) experience. Azure AI Foundry / Azure OpenAI. Copilot Studio. Semantic Kernel, LangGraph or other agent frameworks. Azure Functions / API Management. Power Automate. Experience integrating AI solutions with enterprise applications. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success.

Location: India - Remote About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Technical Delivery Lead, Emerging Role: Technical Delivery Lead, Emerging Location: India Experience Level: 12+ years in software engineering or technical consulting, including 5+ years leading enterprise data or AI delivery Work Model: Full-time; India-based, working with distributed teams across the United States, India, and Latin America Reports To: Head of AI Delivery Why Join Turing Intelligence? Turing Intelligence builds and deploys production AI systems for enterprise clients. Our delivery teams work directly in client environments, translating high-value business problems into reliable systems that can operate at enterprise scale. The Emerging portfolio spans consumer goods, supply chain, real estate, manufacturing, media, and other complex operating environments. This role ensures that multiple concurrent engagements reach production on time, meet their commercial commitments, and create the confidence required to earn follow-on work. This is a high-ownership role for a technical delivery leader who can move between architecture, staffing, delivery health, and commercial decisions. Engagement managers own the client relationship; you will own how the work is engineered, staffed, reviewed, and recovered when delivery moves off plan. As the Technical Delivery Lead, Emerging, You Will Own Portfolio Delivery Health Establish a clear operating view across every active engagement, including delivery status, burn against plan, margin, staffing, technical risks, and client commitments. Identify issues early, intervene directly, and ensure recovery plans have accountable owners and measurable outcomes. Assure Architecture and Production Readiness Set and enforce the technical review bar for production AI systems. Review architecture across retrieval, orchestration, evaluation, guardrails, observability, scalability, and security, and ensure every proposed SOW receives appropriate technical review before signature. Lead Distributed Forward-Deployed Teams Build staffing plans for each active SOW, allocate engineers across competing priorities, reduce avoidable bench time through redeployment, and hire and calibrate engineers against a consistently high bar. Lead teams distributed across the United States, India, and Latin America. Shape Scope, Estimation, and Commercial Commitments Partner with pre-sales and engagement leaders on scoping, estimation, delivery plans, and change control. Challenge assumptions before commitments are made, protect delivery margin, and ensure client expectations match the work that can be staffed and delivered. Turn Delivery into Platform Leverage Work with the Chief AI Architect and platform leaders to apply shared architecture and evaluation standards, identify reusable components, and turn successful engagement work into capabilities that improve future delivery. How Success Will Be Measured First 90 Days Create a delivery-health baseline for every Emerging account, including status, burn against plan, margin, and material risks. Put an FDE staffing plan in place for every active SOW and establish a technical review before every new SOW is signed. First Year Maintain Emerging delivery gross margin at or above 40%, prevent avoidable client escalations from reaching the GM without warning, reduce bench time through active redeployment, and contribute at least two reusable components to the Enterprise AI platform. The Anti-Sell Portfolio-level accountability: This is not a single-project delivery role. You will oversee several engagements with different clients, technical risks, staffing constraints, and commercial commitments at the same time. Hands-on technical leadership: This is not a PMO or governance-only position. You must be able to inspect architecture, challenge technical decisions, and guide teams through production issues. Candidates without recent hands-on engineering judgment are unlikely to be successful. Commercial accountability: Delivery quality and margin are inseparable in this role. You will be expected to challenge weak estimates, manage change, redeploy capacity, and make difficult tradeoffs when client demand exceeds the funded scope. Client-facing pressure: You will step into troubled engagements, surface uncomfortable facts early, and work with engagement leaders to reset plans without damaging client trust. Distributed execution: The portfolio relies on teams across multiple regions and time zones. You must be comfortable making staffing and delivery decisions across the United States, India, and Latin America. Our Technical Delivery Leaders Typically Have Enterprise delivery leadership: 12+ years in software engineering or technical consulting, including 5+ years leading enterprise data or AI delivery. Portfolio and margin ownership: A track record of owning delivery outcomes and commercial performance across a portfolio of client accounts—not only a single project. Recent production AI experience: Direct responsibility for shipping GenAI or machine-learning systems to production within the last two years. Technical depth: Strong working knowledge of LLM and agentic architectures, including retrieval, orchestration, evaluation, guardrails, observability, and production operations. Delivery and commercial discipline: Experience with estimation, technical SOW review, staffing plans, change control, delivery recovery, and managing to a P&L. Leadership across seams: The ability to align engagement managers, pre-sales, architects, and distributed engineering teams while maintaining clear accountability for technical delivery. Top-Tier Candidates Will Have Experience leading forward-deployed or client-embedded engineering teams in an AI, data, or technology-services organization. Experience in consumer goods, supply chain, real estate, manufacturing, media, or another operationally complex enterprise environment. A record of turning client-specific delivery work into reusable platform components, delivery accelerators, or technical standards. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: Москва Центр компетенций по внедрению ИИ-агентов в Блоке стратегии и развития Сбера — команда из ex-консультантов, ML-инженеров и лидеров развития ИИ в России. Мы находимся в эпицентре GenAI-трансформации: работаем над наиболее инновационными задачами Сбера, создаём передовые ИИ-решения для поддержки топ-менеджмента, переосмысления и редизайна ключевых процессов банка. Ищем человека, который уверенно чувствует себя в бизнес-задачах и готов своими руками драйвить образ будущего. Предстоит находить возможности для трансформации, быстро собирать прототипы, защищать идеи перед руководителями и вместе с технической командой доводить их до внедрения. Обязанности ### Что предстоит делать: * исследовать процессы Банка, выявлять проблемы и находить сценарии, в которых ИИ-агенты могут дать измеримый эффект * формировать продуктовые гипотезы, определять границы MVP и критерии успеха * описывать бизнес-логику, пользовательские сценарии и требования к данным и интеграциям * самостоятельно собирать и тестировать прототипы с помощью ИИ-инструментов для написания кода, проверять их на реальных задачах * организовывать пилоты, собирать обратную связь и сопровождать внедрение вместе с DS и разработчиками * рассчитывать и защищать бизнес-кейсы, оценивать ROI и фактический эффект от внедрения * приоритизировать инициативы с учётом потребностей бизнеса и стратегии GenAI-трансформации Сбера. Требования ### Что для нас важно: * высшее образование в одном из ведущих вузов России (МГУ, ВШЭ, МГИМО, МФТИ, ИТМО и пр.) * опыт от 3 лет в бизнес-анализе, управлении продуктами или IT-проектами с ответственностью за результат * умение разбираться в экономике процессов, проверять гипотезы цифрами и аргументировать приоритеты * навыки вайбкодинга: умеете ставить задачи ИИ-инструментам, запускать полученный код и проверять, что прототип решает поставленную задачу * понимание возможностей и ограничений LLM, принципов работы ИИ-агентов и RAG * реализованные проекты, о которых можете рассказать через собственный вклад, принятые решения и достигнутый эффект. ### Будет преимуществом: * опыт работы в стратегическом консалтинге (MBB / Tier-2 / Big-4) * опыт внедрения AI-продуктов end-to-end с измеримым влиянием на бизнес-процессы * практический опыт программирования или анализа данных: Python, SQL, автоматизация или прикладные DS-задачи. Условия ### Что мы предлагаем: * комфортный современный офис рядом с м. Кутузовская * офисный формат работы * корпоративный спортзал и зоны отдыха * уникальную систему обучения Сбера для профессионального и карьерного развития * программу адаптации и помощь руководителя на старте * расширенный ДМС и льготное страхование для семьи * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписку Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера * корпоративную пенсионную программу.

Location: Москва Команда SberNBA занимается тремя большими направлениями: * платформа коммуникаций и персональных предложений Сбера, * поведенческая foundation model человека, * бизнес направление коммуникаций от потребности клиента. Цель команды – сделать управление коммуникациями проще и эффективнее за счет гибкости платформенных инструментов и GenAI, моделировать поведение человека на краткосрочном и долгосрочном горизонте и использовать эти данные в бизнес-процессах банка, помогать человеку закрывать потребности быстрее и проще. Обязанности * В роли CDS вы будете развивать команду и компетенции трайба на уровне DS экспертизы. * Строить, развивать и реализовывать стратегию развития трайба в части ML/AI. * Участвовать в создании кампейн платформы нового поколения, основанного на агентах. * Развивать системы генерации персонализированного контента. * Развивать Foundation Model (Трансформерная модель понимания клиента на основе его действий в банке и экосистеме Сбера) и рекомендательные модели. Требования * 10+ лет в DS / 5+ лет в промышленных RecSys в крупных компаниях * Интеграция LLM в RecSys (RAG / генерация текста офферов) * Опыт управления командой 10+ DS и развития ML экспертизы на уровне подразделения * Успешный опыт реализации сложных и масштабных ML проектов с доказанным бизнес-эффектом * Хорошие коммуникативные навыки, готовность договариваться и находить оптимальные решения * Стратегическое мышление * Амбициозность и ориентация на бизнес-результат Условия * комфортный современный офис рядом с м. Кутузовская * ежегодный пересмотр зарплаты и годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития   * расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа * 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.

Location: Москва Наша команда (70+ человек) создает технологический фундамент для внедрения GenAI в экосистему банка. Мы разрабатываем RAG-платформу, фреймворк исполнения агентов и системы обработки неструктурированного контента (документы, коммуникации). Наши сервисы оборачивают базовые LLM в готовые интерфейсы, позволяя бизнесу быстро создавать собственных агентов и GenAI-приложения. Мы обеспечиваем полный цикл разработки (E2E) Мы в поиске играющего тренера - руководителя направления анализа и подготовки данных для AI. Команда 5 человек Обязанности * создавать и оптимизировать подходы к оценке качества моделей и AI-пайплайнов (RAG, LLM, OCR) * построение online/offline метрик качества, написание методологий оценки для мониторинга качества и регрессионного тестирования * проводить эксперименты, проверять гипотезы по улучшению текущих AI-решений * выявлять уязвимости в качестве в AI-пайплайнах и оперативно предлагать решения для устранения проблем в production (проводить A/B-тестирования) * отвечать за качество данных и методологию их подготовки для AI/ML-проектов * поддержка и оптимизация полного цикла работы с данными: сбор, хранение датасетов, разметка, авто-разметка (LLM-as-a-judge), валидация * автоматизация data-циклов: сбор данных, разметка, подсчет метрик, оценка качества * совместно с ML-инженерами определять требования к моделям и к данным (состав, объем и качество датасетов) * руководить командой Data-аналитиков, Data-менеджеров, разметчиков * говорить на одном языке с «бизнесом» и ML-инженерами: сбор и анализ бизнес-требований, понимание применимости и ограничений AI. Требования * любить data-driven подход) * кросс-функциональное уметь разговаривать с DS и разработчиками * python, SQL, уверенный vibe-coding * понимание процесса деплоя моделей * понимание работы LLM и знание понятий типа RAG, fine tuning, skills/tools, Data Governance * знание подходов по оценке качества LLM, RAG * знание матстата * jira, agile итд * soft skills (уверенный problem-solving) * системное мышление Будет плюсом: * опыт построения процессов по оценке качества GenAI * опыт работы с данными для LLM и AI-агентов * опыт управления разметчиками * опыт создания пайплайнов data lifecycle * знакомство с LabelStudio, Toloka * опыт работы с качеством разметки (consistency, honeypots, golden dataset) Условия * комфортный современный офис - м. Кутузовская * гибридный формат работы * ежегодный пересмотр зарплаты, годовой бонус * 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 * корпоративная пенсионная программа.

Location: Москва Команда блока Финансы реализует масштабный проект внедрения платформы для управления финансовой моделью Группы. Реализуемая система будет включать в себя широкое пространство взаимосвязанных финансовых сервисов, в том числе систему сценарного моделирования финансовой модели Группы Сбер. Перед командой проекта стоят задачи проектирования и реализации на базовых сервисах платформы решения, обеспечивающего автономное определение лучшего варианта управления финансами Группы в условиях ограничений, комфортный клиентский путь всех участников процесса. Обязанности ### **Чем предстоит заниматься:** * формированием стратегической концепции продукта, продуктового видения, детальных тактических планов производства и внедрения отдельных фичей * организацией и проведением глубокой проработки методологии решения * формированием обеспечивающего реализацию целей блока бэклога команды и его приоритизация, а также пополнением и актуализацией по результатам проведения клиентских исследований, анализа отраслевых практик, осуществления сбора и анализа клиентских предпочтений * обеспечением качественной и своевременной поставки инкремента в соответствиями с концепцией развития продукта и потребностями стейкхолдеров * обеспечением достижения качества реализации процесса и удовлетворенности пользователей * выстраиванием эффективного взаимодействия с заказчиками, контрагентами и стейкхолдерами * обеспечением качества разработки, поставки, эксплуатации, сопровождения АС, поддержки пользователей, управление инцидентами по АС. Требования ### **Мы ждем, что вы:** * имеете опыт построения сложных финансовых моделей и их систем, моделирования прогнозов, сценарной аналитики * владеете математическими или статистическими методами оптимизации, практическая реализация промышленных кейсов решения оптимизационных задач * имеете опыт успешного внедрения систем класса EPM, знание бизнес-процесса создания продукта (ИТ) * имеете опыт руководства командой/подразделением/проектом * опыт выстраивания автономных процессов или внедрения решений с GenAI будет являться преимуществом. Условия ### **Что мы предлагаем:** * комфортный современный офис рядом с м. Кутузовская * ежегодный пересмотр зарплаты, годовую премию * корпоративный спортзал и зоны отдыха * уникальную систему обучения Сбера для профессионального и карьерного развития * расширенный ДМС и льготное страхование для семьи * гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ * подписку Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера * корпоративную пенсионную программу.

Location: Remote-Florida; Remote-Connecticut; Remote-New Jersey Workplace: Remote LIFE AT UIPATH The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose. Could that be you? YOUR MISSION Finance teams lose hours every week chasing approvals, re-keying data, and reconciling records across systems that don’t talk to each other. As a member of UiPath’s product marketing team, you’ll bring our agentic solutions for the Office of the CFO to market, focusing on the source-to-pay and order-to-cash functions. These solutions orchestrate work across the ERP, procurement, and receivables systems customers already run. Drawing on your knowledge of how finance organizations buy and what they’re measured on, you’ll own positioning, launches, and sales enablement that speak to finance leaders in their own terms. WHAT YOU’LL DO AT UIPATH - Lead go-to-market strategy and launch planning for source-to-pay (invoice processing, procurement, and supplier communications) and order-to-cash (collections and cash application), working with the field marketing and sales teams that bring it to market. - Define positioning and messaging for the full CFO buying center, from AP, AR, and procurement leaders to controllers and the CFO, presenting UiPath as the layer that orchestrates work across their existing systems rather than replacing them. - Build the sales story and the tools to tell it: pitch decks, battlecards, ROI calculators, demo narratives, objection handling, and sales training. - Recruit customer advocates and turn their results into proof points tied to finance KPIs such as DSO, cost per invoice, and on-contract spend. - Run buyer research, including personas, buying journeys, and win/loss analysis, and share what you learn with product management to shape the roadmap. - Develop the messaging, content, and audience insight behind campaigns across demand generation, field, and partner channels, and support analyst relations. - WHAT YOU’LL BRING TO THE TEAM - 10+ years in B2B marketing, consulting, or product development, ideally including SaaS product marketing for finance, procurement, or order-to-cash software. - Deep knowledge of source-to-pay and order-to-cash processes and the finance leaders who own them. Experience in finance operations, shared services, or finance advisory is a strong plus. - Working knowledge of enterprise SaaS, GenAI, agentic AI, and automation, including how they integrate with ERP and other systems of record, and the ability to explain them in terms of business outcomes. - A track record of successful launches built on sharp positioning, messaging, and sales collateral. - Clear, persuasive communication with every audience, from AP specialists to the CFO, in writing, in meetings, and on stage. - Experience partnering closely with marketing, sales, partners, product management, and engineering. - Hands-on use of AI tools in your day-to-day work, such as research, content development, and analysis, is a plus. - A degree in business, finance, accounting, engineering, or a related field, or equivalent experience. Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned. Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected. We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy https://www.uipath.com/legal/trust-and-security/privacy-policy.

Location: Sydney ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE As a Applied AI Engineer on the Applied AI team, you will bridge the gap between Mistral’s cutting-edge AI research and real-world enterprise applications. This role exists to ensure our solutions are robust, scalable, and aligned with both customer needs and Mistral’s technological vision. The Applied AI team is Mistral’s customer-facing technical organization, working directly with enterprise clients from pre-sales through implementation. We combine deep machine learning expertise with strong customer engagement, operating like startup CTOs who own end-to-end project execution. By joining this team, you will drive the adoption of Mistral’s products, helping customers deploy AI solutions that deliver measurable business impact across industries. WHAT YOU WILL DO - Deploy production-ready AI use cases with significant business impact across diverse industries. - Develop state-of-the-art GenAI applications, from consumer products to industrial solutions, driving technological transformation for customers. - Collaborate with researchers, AI engineers, and product teams on complex customer projects involving fine-tuning, advanced LLM applications, and contributions to open-source codebases. - Participate in pre-sales calls to understand client needs, challenges, and aspirations, providing technical guidance on Mistral’s products. - Work with product and science teams to continuously improve model and product capabilities based on customer feedback. WHAT WE'RE LOOKING FOR - Fluency in English. - Experience as a technical individual contributor (data scientist or software engineer) on AI-based products. - Proven track record in implementing AI or machine learning products with APIs, back-end, and front-end interfaces. - Hands-on experience with fine-tuning LLMs, advanced RAG, or agentic use cases. - Deep understanding of machine learning and LLM concepts and algorithms. - Strong technical coding skills in Python. - Ability to explain complex technical concepts clearly to both technical and non-technical audiences. - Contributions to open-source projects, particularly in the LLM space. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Montevideo, Uruguay; Remote.AR, Remote.LATAM-country; Remote.CO, Colombia; Rosario, Remote.LATAM-country We are looking for a hands-on Data Engineer (Middle/Senior) to design, build, and maintain reliable, scalable pipelines that keep information timely, clean, secure, and well-structured for downstream consumers. This is an execution-focused role combining pipeline development, query and cost optimization, data governance, and production monitoring. The engineer will work closely with business, analytics, and data science teams to make data available and trustworthy across the organization. The Data & AI chapter of the Passenger Journey builds and operates the data foundation that turns raw data into trusted, strategic assets for analytics, product, and business teams. The team works on Google Cloud Platform (GCP) under Agile and DataOps practices, with a tech stack centered on BigQuery and SQL, Dataform (including assertions) for transformation, and Python (Pandas) for processing and automation. Pipelines run on Cloud Run, Cloud Run Jobs, Dataflow, Pub/Sub, Cloud Storage, Cloud SQL, and Cloud Scheduler, with Git/GitLab, CI/CD, and Terraform for delivery, and IAM and policy tags for access control. Data is organized under a medallion architecture (Bronze, Silver, Gold), with cost and performance optimization (FinOps) treated as a first-class concern. Design, implement, and maintain reliable, scalable ingestion and transformation pipelines that ensure data quality, integrity, and availability for business and analytics. Optimize processing and storage by reducing execution time and costs (FinOps) across pipelines and queries to maximize the value of data. Apply data governance standards, including quality, naming conventions, cataloging, and a medallion architecture (Bronze, Silver, Gold), to ensure consistency and traceability. Protect sensitive data through role-based access control (IAM) and policy tags, ensuring compliance with applicable regulations and standards (GDPR, LGPD, ISO, and local regulations). Monitor pipelines, respond to incidents, and adapt them to new business requirements while meeting availability and performance SLAs. Enable controlled, cross-functional access to data for broad consumption. 3+ years of proven experience as a Data Engineer or in a similar role. Strong SQL skills and hands-on experience with BigQuery, including query optimization, partitioning, and clustering. Experience building and maintaining ELT/ETL pipelines and data models with Dataform (or a similar framework, such as dbt, with skills readily transferable to Dataform), including assertions. Experience with Python for data processing and automation (Pandas). Solid GCP experience across Cloud Run / Cloud Run Jobs, Dataflow, Pub/Sub, Cloud Storage, Cloud SQL, and Cloud Scheduler. Knowledge of medallion architecture (Bronze/Silver/Gold) and sound data-modeling fundamentals. Knowledge of data governance and compliance, including IAM, policy tags, and regulatory awareness (GDPR, LGPD, ISO). Experience with Git/GitLab, CI/CD, and Terraform for delivery and infrastructure as code. Experience with pipeline monitoring and observability (Cloud Monitoring; Grafana is desirable). Exposure to GenAI-assisted development and tooling, including prompt engineering, OpenAI API/SDK, Vertex AI, and MCP (desirable). Experience with API development using FastAPI / REST services (desirable). Experience with BI and data visualization tools such as Looker Studio or Google Data Studio (desirable). Ability to communicate effectively with technical and non-technical stakeholders, and experience working in Agile environments. Fluency in Spanish (the team's working language) and intermediate English proficiency for documentation and international collaboration.