Вакансии

Location: Москва Мы - команда GigaChat Pretrain Data, готовим pretrain данные для GigaChat и GigaChat Vision. Pretrain данные - это фундамент, с которого начинается путь современной LLM модели и то, от чего наиболее зависит ее итоговое качество. Сырых данных более 40Пб и основная задача заключается в том, чтобы из этого хаоса сделать датасет, на котором будет обучена лучшая LLM в России. Обязанности Основные задачи будут лежать в следующих сферах: Инфраструктура: * поддержка данных для обучения VLM на кластере YTSaurus. * построение удобной платформы для эффективного анализа/обработки данных (фильтрация, дедупликация и пр.) * автоматизация процессов через Airflow. RnD: * поиск и синтез данных для обучения VLM (есть несколько областей: OCR/Charts&Tables/Grounding&Counting/General и тд). * исследование пайплайнов по созданию чистых и разнообразных датасетов (на примере FineVision). Эксперименты и метрики: * Обучение VLM на подготовленных данных. * проведение исследований релевантных intrain метрик, бенчмарков для замера качества. Требования * Опыт построения дата пайплайнов и data quality процессов * Опыт работы в production ml команде (большие нагрузки как преимущество) * Понимание задач CV и современных подходов в больших языковых моделях * Опыт решения задач, связанных с влиянием данных на качество VLM * Практический опыт работы с VLM. Условия * комфортный современный офис рядом с м. Кутузовская * возможность выбрать удобный график – офис/гибрид/удаленка (в РФ) * 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 * ипотека для сотрудников по дисконтной прогамме * бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Bangalore, India GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Data Engineer at GitLab, you'll build, run, and maintain the pipelines and infrastructure that bring data from our enterprise applications, internal systems, and GitLab's software as a service (SaaS) platform into our data platform. Your work will power company reporting, data science, and artificial intelligence (AI) self-service. You'll own features end to end, from source integration to tested, monitored, documented data ready for use. You'll focus on keeping the platform reliable, secure, and cost-efficient as data volumes and AI usage grow, and making governed data ready for AI tools, agents, and Model Context Protocol (MCP)-based access. This is an AI-first role: you'll use AI coding agents every day while maintaining high standards for code review and testing. You'll report to the Director, Data Platform. What you’ll do Build, extend, and maintain extract, load, transform (ELT) pipelines from enterprise applications such as Salesforce, Zuora, Zendesk, and Marketo, internal systems, and the GitLab SaaS platform. Integrate data through application programming interfaces (APIs) and event sources such as Snowplow. Manage and maintain the infrastructure behind the platform, including SaaS tools such as Snowflake, Fivetran, and Monte Carlo, and self-managed services such as Airflow and Kubernetes. Write maintainable, well-tested, performant Python and Structured Query Language (SQL) code that meets our internal standards, and review GitLab team members' merge requests. Own day-to-day platform operations: triage and resolve failed pipelines, infrastructure issues, and GitLab team member requests. Use monitoring, service-level agreements (SLAs), data contracts, query and warehouse tuning, and data quality checks to keep the platform reliable and cost-efficient. Partner with Analytics Engineers, Data Analysts, Data Scientists, Data Governance, and business partners so data lands in the shape they need for downstream use. Use AI coding agents such as Claude Code, OpenCode, GitLab Duo, or similar tools to speed up development, debugging, testing, and documentation without compromising review rigor. Apply role-based access control (RBAC) and masking policies to make governed data available to AI tools and agents. Handle data subject to Sarbanes-Oxley (SOX) controls, material nonpublic information (MNPI), and personal data safely. Ship medium-sized features independently in small, iterative merge requests, and document architecture and runbooks in the handbook. What You'll Bring Professional experience shipping production data pipelines in Python. Deep, hands-on SQL skills and experience with a cloud data warehouse; Snowflake is preferred. Hands-on experience with ELT or extract, transform, load (ETL) pipelines at scale, including incremental loads, schema changes, backfills, and API ingestion. Experience with orchestration tools such as Airflow, familiarity with dbt, and solid data modeling fundamentals, including Kimball dimensional modeling. Experience running and troubleshooting data infrastructure, with comfort using Git-based workflows, continuous integration and continuous delivery (CI/CD), and code review. Hands-on experience using AI coding tools in your daily work, with an understanding of where they help and where they fall short. Clear written communication, the ability to use GitLab, and comfort working asynchronously in a fully remote organization in line with GitLab's values. Preferred, not required: experience with Snowflake; Docker, Kubernetes, Google Cloud Platform (GCP), or Terraform; SaaS application APIs such as Salesforce, Zuora, or Zendesk; data observability tooling; or Snowflake administration. About the team The Data Platform team within Enterprise Data is responsible for a scalable, reliable and secure data platform for data analytics at GitLab. That includes managing and maintaining the infrastructure we use, both SaaS and self-managed, and building and maintaining the data pipelines that bring data into it. We make data reliable, secure and ready for analytics, data science and AI tools. As more questions go straight to AI tools and agents, the platform underneath has to be more reliable, better governed and more cost-efficient than ever. We're fully remote and globally distributed, and work asynchronously through issues, merge requests and the handbook. How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

▫️Проектирование и реализация компонентов календарного и производственного планирования. ▫️Разработка решений для оптимизации запасов.

Location: Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Key Responsibilities Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development Independently lead small research projects while collaborating with team members on larger initiatives Design, run, and analyze scientific experiments to advance our understanding of large language models Optimize and scale our training infrastructure to improve efficiency and reliability Develop and improve dev tooling to enhance team productivity Contribute to the entire stack, from low-level optimizations to high-level model design Qualifications Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field Strong software engineering skills with a proven track record of building complex systems Expertise in Python and experience with deep learning frameworks (PyTorch preferred) Familiarity with large-scale machine learning, particularly in the context of language models Ability to balance research goals with practical engineering constraints Strong problem-solving skills and a results-oriented mindset Excellent communication skills and ability to work in a collaborative environment Care about the societal impacts of your work Preferred Experience Work on high-performance, large-scale ML systems Familiarity with GPUs, Kubernetes, and OS internals Experience with language modeling using transformer architectures Knowledge of reinforcement learning techniques Background in large-scale ETL processes You'll thrive in this role if you Have significant software engineering experience Are results-oriented with a bias towards flexibility and impact Willingly take on tasks outside your job description to support the team Enjoy pair programming and collaborative work Are eager to learn more about machine learning research Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximize the impact of your insights Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term. Sample Projects Optimizing the throughput of novel attention mechanisms Comparing compute efficiency of different Transformer variants Preparing large-scale datasets for efficient model consumption Scaling distributed training jobs to thousands of GPUs Designing fault tolerance strategies for our training infrastructure Creating interactive visualizations of model internals, such as attention patterns The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

IG Group is looking for a Marketing Data Engineer to build APAC marketing data infrastructure, pipelines, integrations and measurement capabilities.

IG Group is looking for an AI Enabler Engineer to build internal tools, integrate systems, and deliver AI-powered agents and copilots.

Inworld is looking for a Senior Machine Learning Engineer Inference to optimize and deploy high-performance AI inference systems at scale.

Location: Poland; Moldova; Montenegro; Bulgaria; Azerbaijan; Cyprus We’re hiring an Engineering Coordinator to support our fast-paced installation team. You’ll coordinate daily tasks, manage schedules, and communicate with both field crews and clients — while also applying your technical understanding to ensure projects are installation-ready. Key Responsibilities: Assign daily tasks to field teams and track progress in ClickUp Communicate with clients about visit schedules, delays, or rescheduling Verify technical readiness of openings before installation (measurements, drawings, materials) Review shop drawings or specifications to identify potential issues before dispatch Ensure crews are prepared with the correct materials, glass, and hardware Book hotels for traveling installers Monitor vehicle mileage and documentation (registration, insurance) Support project managers with coordination and issue tracking Review quality of completed work and report problems if needed Requirements 1+ year of experience in construction or engineering coordination Engineering or technical background (construction, architecture, or related field) Confident English (B2+ or above) and Russian C1 Strong communication and organizational skills Ability to read and understand basic technical drawings and measurements Comfortable using task management tools (ClickUp or similar) Benefits Competitive compensation package based on experience and performance. Fully remote job opportunity. 8.30 AM - 5 PM EST (NY time zone). Joining a highly professional and dynamic team. Exciting experience working with prestigious clients in the US market. Transparent career growth opportunities with a focus on professional development. B2B contract.

Location: Ukraine; Poland; Spain; Portugal; Romania; Czechia 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 Middle 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: Engineering Manager, 6 MLE’s. 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. Technical Stack: Python, PyTorch, Scikit-Learn, Spacy, LangChain, LangGraph etc. 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. 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 4+ 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 others; experienced in natural language processing and modern LLM-based techniques; experience with full ML lifecycle, data preprocessing, training, evaluation stage, 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 professionally express your thoughts 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 clients 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 Work fully remote around the globe, or in a hybrid work model from our office hubs which are equipped with everything needed for comfortable work. Enjoy a flexible working schedule and create work and rest balance for yourself. Empower yourself with a stable workload and a stable income, focusing on lasting cooperation and high-performance culture. Embrace the opportunity for personal and professional growth Take advantage of performance review and career path. Elevate your skills with mentorship program, personal development plan, and individual learnings through the corporate library, public speaking support, and more. Feel cared about Be among like-minded people and feel supported with collaboration, open communication and mutual respect. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Interview steps Pre-Screening with the recruiter Technical interview (up to 90 min) System Design interview (up to 45 min) Final interview with Engineering Manager (60 min)

Location: China We are seeking an AI Engineer to join our Data & AI team and contribute to the development and continuous improvement of our AI Validation platform. Who we are: Founded in 2006, CXG is a global customer experience company uniquely positioned at the intersection of data-driven retail performance, customer experience transformation, and operational execution across 200+ luxury brands worldwide. The mission of our 270 team members is to help brands transform customer and employee experiences through tailored insights, strategy, and implementation. We are passionate about delivering impact. Our clients include the world’s most admired luxury houses, and our solutions combine research, technology, and human expertise to elevate every customer interaction. What will your role be: This role focuses on evaluating, deploying, monitoring, and optimizing AI models used to process and analyze multilingual content. Given the nature of the project, a deep understanding of both Mandarin Chinese and English language nuances is critical. Therefore, native-level proficiency in Mandarin Chinese and advanced proficiency in English are mandatory. The ideal candidate combines strong AI engineering skills with a pragmatic, production-oriented mindset and is passionate about delivering reliable and measurable AI solutions. What you will be doing: AI Development & Deployment Develop, deploy, and maintain AI-powered applications and services. Integrate and operationalize machine learning and generative AI models. Monitor model performance, quality, and reliability in production. Troubleshoot and resolve issues related to AI systems and model outputs. Continuously improve model performance through testing, evaluation, and optimization. AI Validation & Quality Assurance Contribute to the development of the AI Validation platform. Evaluate AI-generated outputs for accuracy, consistency, and linguistic quality. Design and implement validation methodologies and evaluation metrics. Benchmark different AI models and approaches. Analyze model failures and recommend improvements. Collaboration Work closely with Data Scientists, Data Engineers, and business stakeholders. Translate business requirements into scalable AI solutions. Document technical solutions and best practices. Requirements Technical Skills Advanced proficiency in Python. Strong proficiency in SQL. Solid experience with Git and collaborative software development practices. Hands-on experience deploying and maintaining machine learning or generative AI models in production. Experience working with Large Language Models (LLMs) and modern AI frameworks. Sound understanding of model evaluation, testing, and performance monitoring. Language Skills (Mandatory) Native-level Mandarin Chinese. Advanced English. Ability to assess linguistic quality and cultural nuances across both languages. Professional Attributes Strong analytical and problem-solving skills. Attention to detail and commitment to quality. Ability to work independently and collaboratively in a fast-paced environment. Excellent communication skills. Nice to Have Familiarity with Snowflake. Experience with dbt and Airflow. Experience with RAG architectures, agent-based systems, or AI evaluation frameworks.

Location: Riyadh, Saudi Arabia; Dubai, United Arab Emirates; Delhi, India; Cairo, Egypt Summary We are looking for an experienced ServiceNow Cloud Migration Engineer to lead and carry out the migration of a ServiceNow platform from on-premise (self-hosted) to the cloud, preferably Google Cloud Platform (GCP). You will assess the current ServiceNow environment, plan the migration, and move the instances, data, customisations and integrations to the cloud securely, with minimal downtime and no data loss. You will work closely with platform owners, infrastructure, security and business teams through to go-live. ⚠️ Must Have: Proven hands-on experience migrating ServiceNow from on-premise (self-hosted) to the cloud . Applications without ServiceNow on-premise to cloud migration experience will not be considered. Responsibilities Assess the current on-premise ServiceNow environment, including instances, versions, customisations, scoped apps, integrations and data volumes. Plan the migration approach, timeline, cutover and rollback plans. Prepare and build the target cloud environment, preferably on GCP, including networking, security, access and connectivity. Migrate ServiceNow instances, configurations, customisations and data to the cloud. Reconfigure and test integrations, MID Servers, IntegrationHub, REST/SOAP and LDAP/SSO connections after migration. Review and fix customisations and scripts so they work in the cloud and on the target version, upgrading where needed. Run full testing (functional, integration, performance and user acceptance testing), using the Automated Test Framework (ATF) where possible. Make sure the migrated platform meets security, compliance and data residency requirements. Keep downtime to a minimum during cutover, then provide hypercare support after go-live. Create clear documentation, runbooks and handover materials for the platform and operations teams. Requirements Must: Hands-on experience migrating ServiceNow from on-premise (self-hosted) to the cloud. Bachelor’s degree in Computer Science, IT or a related field. 6+ years of ServiceNow experience (administration, development or architecture). Strong knowledge of the ServiceNow platform: instance management, upgrades, cloning, update sets, scoped applications, data import/export and the CMDB. Experience with ServiceNow integrations: MID Server, IntegrationHub, REST/SOAP APIs, LDAP/SSO. Strong ServiceNow scripting skills (JavaScript, Business Rules, Script Includes, Client Scripts). Understanding of cloud infrastructure, networking and security. Strong problem-solving, documentation and communication skills. Preferred Experience with Google Cloud Platform (GCP), especially migrating workloads to GCP. Experience with ServiceNow modules beyond the core platform: ITSM (Incident, Problem, Change, Request) HR Service Delivery (HRSD) Legal Service Delivery , including contract management Others such as ITOM, ITAM, CSM, GRC/IRM or SPM ServiceNow certifications: Certified System Administrator (CSA), Certified Application Developer (CAD), Certified Implementation Specialist (CIS-ITSM, CIS-HR, etc.) or Certified Technical Architect (CTA). Google Cloud certifications: Associate Cloud Engineer or Professional Cloud Architect. Experience in the Saudi or GCC market, including local data residency requirements.

-Знание принципов построения хранилищ данных. -Опыт работы с экосистемой Hadoop/ навыки Data Engineer, HDFS/Hive (HDFS/YARN/Spark/kafka/Nifi/Sqoop/flume и т.д.).

Построение Lakehouse для работы с файловыми и табличными данными, создание надежных потоков данных для промышленной эксплуатации. - Практический опыт проектирования и построения Lakehouse.

the ask: ex tier-1 cex only.

- Проектирование архитектуры хранилищ, моделей данных и стратегий партиционирования. - Разработка DAG, кастомных операторов и интеграций на Python с использованием Apache Airflow.

The Technical Support Engineer 2 (TSE2), Triage & Discovery is the front line of Alloy’s technical support experience. Serve as the first technical point of contact for incoming support requests—respond quickly, ask targeted follow-up questions, and build a clear understanding of what the customer actually needs.

-As a Technical Support Engineer at Turnkey, you’ll help developers integrate, debug, and succeed with our SDKs and APIs across a range of environments — from React and mobile apps to backend servers and CLI tools.

Location: Croatia; Georgia; Poland; Romania; Turkey; Czechia Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. Role Overview We are looking for an experienced Forward Deployed AI Engineer to design and deliver production-grade AI applications directly with enterprise product and engineering teams. This is a highly hands-on, client-facing role focused on turning complex business requirements into scalable solutions using Python, Large Language Models, RAG, agentic workflows, LangChain / LangGraph, and modern web technologies . You will own the full delivery lifecycle, from discovery and rapid prototyping through production deployment, adoption, and continuous optimization. CONTRACT: Contractor, long-term engagement COMMITMENT: Full-time LOCATIONS: Remote — Turkey, Croatia, Czech Republic, Estonia, Georgia, Poland, or Romania START: ASAP DURATION: 6+ months, with possible extension based on performance NOTES: Fluent English and strong stakeholder communication skills are required. Key Responsibilities Work directly with business, product, and engineering stakeholders to understand complex requirements and translate them into production-ready AI solutions . Design and build applications using LLMs, RAG, AI agents, tool/function calling, and structured outputs . Develop agentic workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies . Design retrieval architectures using vector search, embeddings, document pipelines, and contextual retrieval techniques. Build robust backend services and application logic in Python . Develop user-facing AI applications using React, Next.js, or similar frontend technologies . Integrate AI applications with enterprise APIs, internal platforms, data systems, and authentication / IAM environments. Deploy applications using cloud platforms, Docker, and CI/CD pipelines . Monitor and improve AI application quality, reliability, latency, security, and business performance. Contribute reusable engineering patterns, components, and implementation best practices across projects. Requirements 6+ years of professional software engineering experience , with strong production-level Python expertise. Hands-on experience building LLM-powered applications in production. Strong experience with LangChain, LangGraph, LlamaIndex, or comparable AI orchestration frameworks . Strong understanding of Retrieval-Augmented Generation (RAG), vector retrieval, embeddings, and LLM integration patterns . Experience designing AI agents, agentic workflows, tool/function calling, structured outputs, and automation systems . Experience with React, Next.js, or similar modern web technologies . Experience deploying production applications using cloud platforms, Docker, and CI/CD . Strong understanding of enterprise integrations, secure API design, IAM, and AI / LLM-specific security considerations. Strong ability to translate business needs into technical architecture and communicate effectively with both technical and non-technical stakeholders.