Вакансии

Развертывать и поддерживать Kubernetes-кластеры для data copilot и сервисов поиска (Airflow, Kafka, PostgreSQL); Автоматизировать CI/CD-пайплайны (GitLab CI, ArgoCD, Helm) для быстрого релиза обновлений data-сервисов;

Проектировать архитектуру AI-систем; Внедрение GPU-планировщика для шаринга нагрузки на одном железе;

Location: Ukraine; Spain; Serbia; Yerevan; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a senior pod alongside an FDE, an FDX, and Senior AI Engineers — contributing to real delivery work while building toward independent ownership. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket. Excellent communication and problem-solving skills. Comfortable with some ambiguity, with support from senior team members as you take on more. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth Hands-on experience building or contributing to RAG systems, ideally in a production or near-production setting. Solid engineering fundamentals; Python and/or TypeScript proficiency. Productive in an unfamiliar codebase with some ramp-up support. Practical AWS experience (Lambda, S3, ECS, or similar); ready to grow into Bedrock and Bedrock AgentCore . Some experience with containers and CI/CD in real projects. Exposure to evaluating non-deterministic systems — you've contributed to or run test/eval cycles, even if you haven't owned a full eval suite end-to-end. Basic working knowledge of model/agent monitoring concepts. Awareness of cost and latency trade-offs when working with LLMs. Some hands-on exposure to the Claude ecosystem (Claude Code, CLAUDE.md, hooks, skills files) is a plus, or strong ability to ramp up quickly. Practical experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) in real projects. 2+ years of software or ML engineering experience, including some exposure to production systems. Solid AI/ML foundations — you understand what the models do well enough to reason about common failure modes. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications (or actively pursuing them). A2A: Interest in agent-to-agent interoperability concepts. CI/CD pipeline experience (GitHub Actions, GitLab CI). Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа. Experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build. MCP: you can say why an agent would prefer it to a REST integration, having authored a server is an additional  plus. Responsibilities: Build and contribute to RAG system components under senior guidance, with growing autonomy. Write tests and help build out evaluation harnesses for the features you work on. Write production code across the stack (AI, backend services, data pipelines) with code review support. Help integrate AI components into backend services and RESTful APIs. Support deployment of systems to AWS (containerized, CI/CD), taking on more of this independently over time. Contribute to documentation, runbooks, and client handover materials. Participate in technical discussions and architectural decisions, with an eye toward taking on more of this independently. Support model evaluation efforts and help investigate and improve failure modes. Take on increasing ownership of components and technical decisions as you grow in the role. What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

• Прогнозировать спроса для товаров без истории продаж («новинок»): разрабатывать модели холодного старта на основе атрибутов товара, категории, характеристик продавца и... • Python, PySpark, JupyterHub, SQL, Airflow, Vertica, Kafka, ClickHouse, Grafana, Transformers.

Location: San Francisco Bay Area, USA Workplace: Hybrid Why work at Higgsfield AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 30M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. About the role: We're looking for a Data Engineer to own the data that runs Higgsfield's enterprise business, from raw data to the numbers leadership makes decisions on. You'll own data end to end, from raw data collection through transformation, modeling and validation, to the reporting that Sales, RevOps, Finance and Product use to run the business. Revenue, contracts and commissions all run through this work, so accuracy matters. This is a hands-on role with real ownership. You'll report to our Data Engineering Lead, take on projects independently, and help make sure data is never the bottleneck as the business accelerates. We're an AI company, and we expect our data engineers to use AI to multiply what they can deliver. What you'll do: - Own end-to-end data pipelines, from raw data collection and transformation to modeling, validation and reporting. - Integrate CRM, billing, contract and product usage data into a consistent, trusted view of our B2B customers. - Build the data models and dashboards behind revenue reporting, commissions, forecasting and customer insights. - Turn ambiguous business questions from Sales, RevOps and Finance into scoped projects, and drive them to completion. - Close data gaps across teams, whether that means partnering with backend engineering to capture new data or fixing a broken pipeline. - Build AI-powered workflows (agents, reusable skills, automations) that work with our infrastructure and scale your impact. - Validate every number before it ships, with automated checks, monitoring and documentation that keep our data audit-ready. - Build executive-facing reports and dashboards (CEO / VP level) that are easy to read and highlight what needs action Requirements: - 4+ years in data engineering, analytics engineering or a related role, including building and maintaining complex production pipelines. - Hands-on experience building with AI, not just using it: for example, creating custom agents, skills or automations with tools like Claude, ChatGPT, Gemini or Cursor. You know where these tools help and where they fall short. - Strong SQL and Python, plus experience with modern data warehouses and transformation/orchestration tools (e.g., Snowflake or BigQuery, dbt, Airflow or Dagster). - Experience integrating data from business systems such as Salesforce, HubSpot or Stripe. - Structured thinking: you break ambiguous problems into clear steps and solve them methodically. - A proactive, self-directed approach. You learn fast, take ownership without waiting for instructions, and push work over the finish line. - Clear communication, including explaining technical work and its tradeoffs to nontechnical stakeholders. Nice to Haves: - Experience partnering with Finance on data that demands high precision (revenue, billing, commissions). - Early or growth-stage startup experience. Compensation & Benefits - We offer a competitive and thoughtfully structured compensation package designed to align with impact, experience, and long-term growth. - Base Salary: The anticipated salary range for this role is $200,000 - $260,000, depending on experience, skills, scope, and location. - Bonus: This role is Bonus eligible and may participate in the Company's discretionary annual bonus program. - Equity: In addition to cash compensation, employees are eligible to participate in the company’s stock option program and share in Higgsfield’s long-term growth. - Benefits: We offer a comprehensive benefits package designed to support employees professionally and personally, including medical, dental, and vision insurance, a competitive 401(k) retirement plan with company matching, and additional benefits and perks. - The opportunity to work on ambitious AI products alongside a highly experienced, fast-moving, and international team. - Significant ownership, direct impact, and opportunities for professional growth as the company scales. This is a hybrid role based in the San Francisco Bay Area. Team members are expected to work from our San Francisco office three full days per week, with the remaining days worked remotely and are expected to be available during agreed working hours and to maintain sufficient overlap with the relevant team’s time zone. We value in-person collaboration, active communication, responsiveness, and close partnership across teams. Higgsfield AI is an equal opportunity employer. We are committed to building a diverse and inclusive team and do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic.

Location: United States Workplace: Remote At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 We're looking for a highly skilled and experienced Senior AI Engineer to join our ClickUp Engineering team, with a focus on AI evaluations. You'll own how we measure and improve the quality of ClickUp's AI: building the eval systems that tell us how well our AI is performing, the core agent harness, and the AI that performs well on those evals. You'll work on backend systems that make AI-powered capabilities scalable, reliable, and secure, while working hands-on with LLMs to solve real user problems and drive product innovation.   Key Responsibilities: - Design, build, and own ClickUp's AI evaluation system, including golden datasets, LLM-as-judge and automated scorers, regression detection, and quality tracking across AI features. - Build and evolve the core agent harness, and the AI that performs well on those evals, partnering closely with product and engineering to define what "great" looks like. - Build self-improvement loops where agents modify other agents or prompts, rerun evals, and iterate automatically. - Benchmark new models as they're released and own model selection, routing, and fallback strategies across providers (e.g., OpenAI, Anthropic, Google, open-weight), balancing quality, latency, and cost. - Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models. - Build and maintain robust APIs and backend systems that integrate AI-powered features into ClickUp's core platform. - Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance of AI services in production. - Drive best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence. - Collaborate cross-functionally with product, frontend, and data teams to deliver seamless, reliable, and user-centric AI experiences.   Qualifications: - 5+ years of software engineering experience, including 2+ years building production LLM or ML systems. - Hands-on experience building LLM evaluation systems in production (golden datasets, LLM-as-judge, judge calibration, offline and online evals), tied to real product quality. - Strong experiment design and statistical rigor, including A/B testing, offline vs. online metrics, and separating real regressions from noisy or variable results. - Proven track record of applying LLMs and AI models to real-world, customer-facing product features. - Proven experience integrating and managing multiple LLMs, including benchmarking, routing, and cost/latency/quality tradeoffs. - Deep expertise in backend engineering, distributed systems, and cloud-native technologies (e.g., Kubernetes, Docker, AWS/GCP/Azure). - Strong programming skills in Python (preferred), Go, TypeScript, or similar languages used for backend and AI platform development. - Proficiency in orchestration frameworks and workflow engines (e.g., LangGraph, Airflow, Ray, or similar). - Familiarity with search and retrieval technologies and their integration into AI-driven applications. - Excellent collaboration and communication skills, with a track record of working effectively in cross-functional teams. - Passion for staying at the forefront of AI and applying new technologies to solve real-world problems at scale.   Nice to Have: - Background in data science, applied science, or machine learning engineering. - Experience with eval tooling (e.g., Braintrust, LangSmith, Weave, Arize, or in-house frameworks). - Experience with model routing, AI gateways, or inference optimization.   #LI-REMOTE #LI-AK2 #LI-CC1 Equal Opportunity Employer ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. Privacy Notice ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice. https://clickup.com/careers-terms/candidate-privacy-notice If you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice https://t333.s.clickup-attachments-stg.com/t333/d9a53ce2-6d2c-48cd-84b1-ed4e525f9613/Philippine%20Data%20Privacy%20Notice_2024.pdf?view=open for further details. Visa Sponsorship Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions. Fraud Alert ClickUp Talent Acquisition will only initiate contact via an @clickup.com http://clickup.com email or through our official careers portal on clickup.com http://clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to support@clickup.com. AI Processing Notice ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates' employment applications against role-related criteria. These tools support, but do not replace, human decision‑making. If you have questions or need an accommodation in the recruitment process, please contact us at AskPeople@ClickUp.com.

Задачи: — проектирование и разработка витрин данных (финансы, торговля, клиенты); — участие в трансформации хранилища в рамках дата‑продуктов; — автоматизация финансовой и управленческой отчётности; — создание отчётов и дашбордов; — анализ источников данных (брокерские системы, торговые платформы, CRM); — выполнение разовых аналитических задач и выгрузок; — документирование процессов и витрин; — поддержка витрин, отчётов и процессов подготовки данных; — сбор и анализ требований от бизнеса (финансы, продажи, продукт). Требования: — уверенное владение SQL и опыт с реляционными и аналитическими СУБД (MSSQL, Greenplum, ClickHouse) с пониманием особенностей каждой системы и оптимизацией запросов; — умение создавать и редактировать хранимые процедуры (работа с переменными, параметрами, управляющими конструкциями); — опыт построения трансформаций на dbt (модели, тесты, документация); — навыки работы с Airflow: разработка и поддержка DAG; — понимание проектирования витрин данных, ETL/ELT‑процессов и слоёв DWH; — опыт документирования структуры данных и бизнес‑логики; — знакомство с Arenadata Data Catalog; — способность самостоятельно разбираться в новых источниках данных; — опыт сбора и формализации требований от бизнес‑заказчиков с переводом бизнес‑вопросов в технические постановки; — опыт с BI‑инструментами (Tableau, Superset); — понимание финансовых показателей брокерского бизнеса (финансовый результат, комиссионный доход, NIM, объём торгов, AUM, клиентская база, обороты, сделки). Будет плюсом: — опыт работы с Data Vault; — опыт работы с финансовой отчётностью; — знание Python для автоматизации и анализа данных; — опыт работы с брокерским бизнесом.

В задачи входит анализ существующих решений и витрин данных, миграция витрин со стека Hadoop на стек Apache Iceberg + Spark 3.5 + Apache Airflow, реализация недостающих реплик, переработка текущих решений на целевом стеке, построение и развитие витрин, участие в тестировании, наполнение и актуализация технической документации.

Location: Paris; London Workplace: Hybrid 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. ABOUT THE JOB As a Applied AI, Frontier Data Engineering, Staff, you will build the systems behind some of the hardest problems Mistral takes on. You join our team of engineers in Applied AI. We gravitate towards hard problems, decide how to solve them, and ship fast. You work closely with our customer-facing teams, and what works goes into production with our customers and across the company. When a project needs it, you work directly on customer engagements. We're looking for a strong software engineer who builds end to end and has shipped ML or GenAI systems to production. You've felt the pain of models that pass every eval and fail on real data, and of quality that drifts after launch. You've also felt the data engineering pain: pipelines that break silently, schemas that change under you, and backfills that take a weekend. Data engineering is your edge. You turn messy, large-scale data into systems that hold up. You think like a founder. You start from the customer's problem, not the technology. You measure success by the value you deliver, and you care about building experiences people love to use. You like working at the edge of what AI can do today, and you push past it. Your scope is end to end, from first prototype to production. Your depth in data architecture helps set the standard for how the team designs and delivers systems. You know lakehouse and data mesh patterns well enough to know when they fit and when they're overkill. You've designed ontologies and data models, and you know that getting them right is as much art as science. WHAT YOU WILL DO - Build AI systems end to end, from first prototype to production. - Design the data architecture underneath them: ingestion, processing, storage, and the data models and ontologies that make messy data usable. - Build distributed pipelines that process large volumes of documents, code, logs, and multimodal content for retrieval, agentic workflows, and fine-tuning. - Turn what works for one customer into patterns and platforms that work across many, without rebuilding each time. - Make systems hold up under real load: throughput, latency, cost, and failure recovery are part of the design from the start. - Build data governance into the systems themselves: ownership, access control, lineage, retention, and privacy for sensitive enterprise data. - Build the evaluation loop: labeling with LLMs and humans, versioned eval datasets, and checks that catch quality drift before customers do. - Set the standard for how the team designs and ships data systems. - Work with researchers, engineers, and customer-facing teams to turn hard problems into systems people rely on. WHAT WE'RE LOOKING FOR - You have full ability to ship across the stack: proficient NodeJS e.g. NextJS/Express/Fastify or similar or Python e.g. FastAPI. You are confident with TypeScript + React/NextJS or similar. Solid beats polished. - You have 5+ years of experience building and running production data-intensive pipelines with distributed processing (for example Spark, Ray, Beam, or Dask) and orchestration tools (for example Airflow, Dagster, or Prefect) with structured and unstructured data. - You have experience with retrieval-augmented generation, agentic use cases, or LLM evaluation, and a clear view of how data quality drives model quality. - You work autonomously: you find the problem, decide the approach, and own the outcome. - You communicate clearly with technical and non-technical audiences, and are fluent in English. - You ship in increments, are obsessed with time to value and are comfortable making and articulating product-technical tradeoffs. IDEALLY YOU HAVE - A passion for graph-based systems (e.g. Neo4j) and ontology design - Hands-on experience building data pipelines for LLM training, fine-tuning, or evaluation, and contributions to open-source projects, particularly in data or LLMs. - Hands-on experience with data governance and privacy requirements (for example GDPR), secure data handling, CI/CD and infrastructure as code, or an affinity for security engineering. HOW WE WORK IN APPLIED AI - We care about people and outputs. - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week. - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care. - No politics. Low ego, high standards. - We embrace an unstructured environment and find joy in it. 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: Нижний Новгород Мы – команда экспертов, объединенных общей страстью к искусственному интеллекту и рекомендательным системам (RecSys). Нашей главной задачей является создание современной, масштабируемой рекомендательной платформы, способной предвосхищать ожидания пользователей, предлагая персонализированные рекомендации на каждом этапе их взаимодействия с экосистемой Сбер. Наши решения охватывают широкий спектр отраслей: от финансов и e-commerce до индустрии развлечений и здравоохранения. Развитие нашей платформы строится вокруг внедрения новейших state-of-the-art (SOTA) моделей. Мы следим за мировыми трендами, экспериментируем с новыми подходами, внедряем их как часть платформы и доводим до конкретного применения в бизнесе. Обязанности * извлекать и обрабатывать большие объемы данных (ETL-процессы) с помощью SQL, Python и Spark для анализа воронки рекомендаций * строить дашборды, автоматизированные отчеты и визуализации в BI для продуктовых и ML-команд * проводить статистический анализ (когорты, сегментация, регрессия) метрик retention, LTV, ARPU, выявляя корреляции и причинно-следственные связи * генерировать data-driven гипотезы по рекомендациям, настраивать A/B-тесты и анализировать результаты с фокусом на p-value и uplift. * оптимизировать пайплайны данных (Airflow), работать с логами и сырыми датасетами. Требования * опыт в аналитике данных от 2 лет, с уклоном в обработку Big Data * свободное владение SQL, Python (Pandas, NumPy), Spark для работы с терабайтами данных * опыт работы с A/B-тестированием, сегментацией пользовательской базы, когортным/регрессионным анализом * знание базового ML (кластеризация, feature engineering и т.д.) * опыт работы с инструментами визуализации и построении дашбордов * самостоятельность, инициативность, аналитический склад ума * умение ясно презентовать и отстаивать результаты своей работы * способность работать в быстро меняющейся среде и находить решения сложных задач. **Будет большим плюсом:** * опыт в сферах e-commerce или развлекательных стриминговых сервисов (аудио/видео) * опыт работы в области рекомендательных систем (RecSys) и/или поиска * опыт работы с Kafka и/или другими streaming-платформами для real-time анализа данных * высшее образование в области IT, математики, Data Science или смежных дисциплин * навыки работы с генеративными AI-моделями, опыт использования GigaChat, Kandinsky и аналогов в продуктах * навыки создания и использования AI-агентов инструментальное владение AI для анализа, генерации и автоматизации. **Стек технологий:** Python (Pandas/NumPy/Scikit-learn/Statsmodels), SQL, Spark/ClickHouse, Tableau/Superset/Amplitude, Airflow, Git Условия * ежегодный пересмотр зарплаты и годовая премия * расширенный ДМС и льготное страхование для семьи * уникальная система обучения Сбера для профессионального и карьерного развития * выгодная ипотека для сотрудников * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера * корпоративная пенсионная программа.

Ищут опытного инженера, который поможет создать мобильный SDK с нуля и внести вклад в несколько инициатив по продукту.

Location: Bangalore Workplace: OnSite 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? ABOUT THE ROLE Join the Vertical Solutions team and build UiPath's most ambitious product - an AI agentic orchestration platform that's been recognized as our Invention of the Year for two consecutive years. As a Senior Software Engineer, you'll be at the forefront of our Act 2 strategy, building the infrastructure that allows enterprises to seamlessly orchestrate AI agents, robots, and human-in-the-loop workflows to achieve critical business outcomes. You'll be working with Lax and the Maestro backend team to build the core orchestration engine that powers enterprise AI automation. This is a high-visibility, high-impact role on UiPath's biggest strategic bet. What You'll Do - Build and Scale: Design, develop, and maintain full stack for Vertical Solutions products leveraging AI Coding Assistants. - Hands-On Development: Write production-quality code daily, leveraging AI tools (Claude, GitHub Copilot, etc.) to enhance your development workflow - Prototype and Ship: Take ideas from Prototype to validate with real customers and turn the ones that prove value into production systems. - Measure what matters: Design evaluations, measure quality against real customer data, and understand when metrics mislead. Our systems are often non-deterministic. Responsible shipping means measuring honestly, not chasing vanity numbers. - Customer-Centric Engineering: Deeply understand who will use the features you build and why they need them, translating customer needs into elegant technical solutions - Ensure Reliability: Contribute to building highly scalable, reliable distributed systems that enterprises depend on. What We're Looking For: - Builder mindset — you enjoy turning ideas into working systems and taking ownership from Concept through, Customer impact and Production - Strong full stack knowledge including frontend systems like React and backend systems -Python and/or C# — most Vertical Solutions product development is Python (agents, APIs, ETL), while core platform work includes C#, frontend in React. Willingness to work across both is important. - Experience building production AI systems — LLMs, tool-calling, multi-agent architectures, orchestration frameworks (LangGraph, LangChain, or equivalent), structured outputs, orchestration, and evaluation of model behavior in real-world workflows - Distributed systems experience — designing resilient systems with idempotency, replay ability, state management, and long-running jobs - Strong analytical thinking — able to reason quantitatively about system quality and make sound decisions using imperfect signals - Comfortable with ambiguity and rapid prototyping — able to move from idea to proof-of-concept quickly and iterate based on customer feedback. - Experience with healthcare Tech/ Finance Tech/ Procurement Tech systems experience will be a big plus. What You'll Bring to the Team - Bachelor's/Master's degree in Engineering, Computer Science or equivalent experience. - 7+ years of software engineering experience, with 4+ years focused on distributed systems and backend architecture. - Strong proficiency in one or more system-level languages – Javascript / C# / Java etc - Full-stack experience: ability to work across backend services and frontend layers (REST/GraphQL APIs, basic UI integration, component contracts). - Deep understanding of object-oriented programming, architectural design patterns, system design, and data structures & algorithms. - Experience with React, TypeScript, or other modern frontend frameworks for deeper full-stack contribution. - Strong grasp of multithreading, asynchronous programming, synchronization, and cloud-native programming models. - Hands-on experience with cloud ecosystems: Azure, AWS, or GCP. - Proficiency with containerization and orchestration: Docker, Kubernetes, or equivalent. - Hands-on experience with AI coding tools and coding agents (e.g., GitHub Copilot, Cursor, Claude Code, or similar) and a demonstrated ability to integrate these into daily engineering workflows. - Experience driving team adoption of AI-powered productivity tools – setting norms, measuring impact, and iterating on usage patterns. - Familiarity with modern engineering practices: agile development, CI/CD, DevOps, and infrastructure as code. - Excellent verbal and written communication skills; proven success collaborating with globally distributed teams and managing complex, time-bound deliverables. - Ability to understand, communicate, and drive complex technical decisions with stakeholders at all levels. Nice to Have - Experience with healthcare Tech/ Finance Tech/ Procurement Tech systems experience will be a big plus. - Data science and evaluation - Experience with applied ML techniques such as classification, anomaly detection, ranking, or predictive modeling - Experience evaluating AI systems using experimentation, metrics, and empirical analysis to improve quality and reliability - Data and retrieval systems - Experience with large-scale data platforms (Snowflake, columnar warehouses, denormalized data models) - Familiarity with retrieval-heavy architectures, RAG systems, or citation-grounded AI workflows - Engineering for trustworthy AI - Experience blending deterministic and probabilistic systems (rules engines + AI) - Experience designing eval-driven systems, regression testing for LLM outputs, or human-in-the-loop review workflows - Platform and product development · Frontend familiarity (React, TypeScript) · Workflow orchestration platforms (Temporal, Airflow, Maestro, BPMN, Step Functions) · Kubernetes and distributed infrastructure · Experience in startups, applied research, or 0→1 product environments · Open-source contributions How We Work Vertical Solutions operates like an internal startup inside UiPath: small teams, fast iteration, and real customers in the loop. We build quickly, test ideas with users, and turn the best ones into products. Some ideas won’t make it — that’s expected. You’ll work in short cycles, demo frequently, and adapt as we learn. We care more about solving the right problem than protecting a plan that no longer fits. If you enjoy ambiguity, rapid feedback, and building where product boundaries move fast, you’ll likely thrive here. Why Join Us - Work on cutting-edge AI technology that's shaping the future of enterprise automation - Be part of a team building Times top 100 Invention of the Year (2 years running) - Collaborate with talented engineers who value rapid iteration and customer impact - Contribute to UiPath's Act 2 strategy - our most important product initiative. 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.

Опыт системного анализа от 3 лет, обязательно с DWH и аналитической отчётностью. Уверенный SQL: JOIN, CTE, оконные функции, сложные запросы, оптимизация.

Организация пайплайнов потоков данных (конвейера движения данных в компании); Разработка, поддержка и оптимизация производительности Корпоративного Хранилища Данных (EDWH);

Самостоятельная разработка, реализация и поддержка интеграционных решений на стеке технологий, принятых в команде (Java, Groovy, Apache Nifi, Airflow);

Проектировать и разрабатывать пайплайны загрузки данных. Делать это оптимально в зависимости от потребностей команд потребителей;

Location: Intellias Meet your recruiter Samprati Muddalkar samprati.muddalkar@intellias.com https://www.linkedin.com... Vacancy details Software Engineering Scala Engineer Senior India, Pune Hybrid APPLY NOW REFER A FRIEND Our client is a is a location data and technology platform company that empower customers to achieve better outcomes – from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely. They create solutions that fuel innovation, provide opportunity and foster inclusion to improve people’s lives. If you are inspired by an open world and driven to create positive change, join us! As a Senior Backened Engineer in the Map Data Processing group you will develop smart Map Data processing tools for the state-of-the-art Mapping Technologies. You will work self-sustained in an agile team. Your responsibility will cover developing, extending and maintaining tool and services that processes map data for global navigational database. For that you will be translating product strategies into technology strategies, leading the long-term architectural direction and helping design and build industry-grade customer-facing geo-data-intensive products. You will work closely with other engineering & operations teams, internal users of tool chains your team develops and partner with product managers and the larger map operations business units. What project we have for you Join our engineering organization to build the next generation of automated map data processing for a global provider of location and mapping solutions used in automotive and mobility. You will work on the platform — a system that takes road data from multiple sources (GPS traces, traffic signs, open map data), detects errors in the map, and either auto-corrects them or flags them for human review. The platform produces quality signals and road attribute corrections that feed directly into navigation and autonomous driving products. Working as part of an agile, cross-functional team on Rakhee’s team, you will build and maintain backend services and distributed data pipelines that keep this platform accurate, reliable, and ready for production load. The primary language on this team is Scala — strong engineers in either language are welcome. What you’ll work on: Distributed batch pipelines for large-scale road dataset processing (Spark on EMR) Error detection, confidence-based auto-fix logic, and manual review workflows for map attributes Data validation, quality gates, and traceability across the pipeline Cloud-native execution environments (infrastructure automation, CI/CD, operational readiness) Technologies: Scala Python( Good to have) Apache Spark Kafka SQL / PostgreSQL AWS (Step Functions, ECS, Lambda, EMR) Apache Airflow Java ( Good to have) CI/CD (GitHub / GitLab) What you will do Design and implement scalable backend services and data processing pipelines Contribute to architecture and design discussions with reasoned technical input Own delivery end-to-end: development, testing, performance optimization, and production support readiness Implement and maintain testing practices (Unit, Integration, E2E) for owned components Contribute to monitoring, alerting, and observability of production systems Improve code quality via reviews, automated testing, and engineering best practices Contribute to estimations, planning, and iterative delivery in an Agile/Scrum process Share knowledge and support junior team members’ growth What you need for this Required Skills 5+ years building backend systems with Scala as your primary language (strong core competency in one — not a shallow familiarity in both) Distributed data processing — Apache Spark or equivalent (production usage required, regardless of whether your primary language is Scala or Python) Kafka — event-driven architecture, producers/consumers, production usage AWS — practical experience with EMR, Step Functions, ECS, or Lambda Strong SQL and data modeling — ideally PostgreSQL (schema design, query optimization, indexes) Solid knowledge of data structures, OOP, and design patterns Good understanding of concurrency and multithreading concepts LLD: modular architecture, clean abstractions, component design API design awareness: RESTful services, backward compatibility Testing strategy: unit, integration, E2E — deliberate approach to coverage Monitoring & observability: logging, metrics, alerting, dashboards in production systems CI/CD pipelines (GitHub / GitLab) and engineering best practices English: Upper Intermediate+ (written and spoken) Nice to Have The other primary language — if your primary is Scala, Python is a plus; if your primary is Python, Scala is a plus Java Apache Airflow or similar pipeline orchestration LLM/MCP tooling experience Experience with geospatial/map-related data or large-scale data quality systems 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. Skills Apache AWS BigData DataEngineer EMR Kaffka Scala Spark

Задачи: — создавать новые сервисы музыкальных рекомендаций, проектировать их архитектуру и ускорять существующие Требования: — опыт работы с Python от 3 лет — опыт работы с FastAPI — опыт работы с PostgreSQL — опыт работы с нагруженными приложениями — знание GraphQL, Kafka, Airflow и ClickHouse будет преимуществом Holyweb — сервисная IT-компания, разработчик подключится к одному из её проектов.