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Location: Remote, Canada; Remote, Poland; Remote, United Kingdom; Remote, United States 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. About the role We are looking for a Principal Engineer to help build GitLab Duo Agent Platform, the agentic orchestration layer that runs AI agents and flows across the entire software lifecycle. Principal Engineers at GitLab are recognized experts across multiple technology domains and represent the senior technical leadership within their organization. In this role you will set technical direction for a significant part of the Agent Platform, working across several teams to turn agentic capabilities into something engineering organizations can actually depend on: predictable, observable, governable, and fast enough to sit in the critical path of real development work. The Agent Platform is not a single service. It spans agent execution and orchestration, flow definition and event-driven triggering, the AI Catalog through which customers discover and manage agents, model routing and evaluation, and the governance surface that decides which agents may act where and under whose identity. It runs on GitLab.com, GitLab Dedicated, and Self-Managed installations, including deployments that use self-hosted models to meet compliance requirements. You will work on the parts of that system where the hard architectural questions live, and you will do it hands-on. This role reports into the VP of the AI Engineering organization and works closely with Engineering Managers, Staff Engineers, Product Management, Infrastructure and Security. What you'll do Define the technical direction for a significant area of Duo Agent Platform across several teams, and partner with Engineering Managers and Product to turn it into a roadmap with a six-month horizon. Build the orchestration layer that makes agents and flows reliable: session lifecycle, tool invocation, context assembly, concurrency, retries, timeouts, and failure modes that degrade gracefully instead of stalling a developer's workflow. Hands on work on driving topics throughout the whole organisation from POC level, architecture to full implementation. Participate in Incident Management on-call rotation, to help meet availability goals for GitLab.com. Strong product builder and ownership mentality. Understanding of product strategy, technical strategy, delivering customer value and iteration towards a successful product Write clear, opinionated design documents, architecture narratives, and decision records that let other teams make aligned decisions. Ensure the architecture holds across multi-tenant GitLab.com, Dedicated, and Self-Managed deployments, including self-hosted model configurations, and respects data governance boundaries in each. Use the platform on our own work, find where it falls short of what we claim, and feed that back through improvements into the product. Mentor Staff and Senior Engineers, and raise the bar for experimentation rigor and cross-team collaboration. Work across the whole platform on different projects, features and teams. This reaches across: Design the extensibility surface so customers can build custom agents and flows, connect their own tools and internal systems, and bring external agents such as Claude Code and Codex into GitLab workflows without weakening the platform's guarantees. Drive down the cost and latency of agentic requests, and work with Product on how model selection, routing, and credit consumption behave as usage grows. Define the evaluation practice for the platform: offline benchmarks and online experiments that measure task completion, correctness, tool-call accuracy, latency, and cost per task, and that catch regressions before customers do. Build the governance and safety surface with Security and Compliance: policy-driven controls over which agents and models may run where, permission and identity semantics that align to existing roles and group structure, human-in-the-loop checkpoints, traceability of every flow session, and audit that stands up to enterprise review. Complete Interview Training and participate in hiring for the department as a technical interviewer or panel member. What you'll bring 8+ years of software engineering experience, including 3+ years at Staff, Principal level or equivalent senior technical leadership. Hands-on production experience building on large language models: agent loops, tool calling, context management, retrieval, prompt and model evaluation. Experience shipping this to real users, not only prototyping it. Strong background in distributed systems, including service decomposition, fault tolerance, observability, and operational resilience under multi-tenant load. A track record of defining evaluation frameworks and using benchmark and experiment results to make architecture decisions, rather than shipping on intuition. Experience designing human-in-the-loop controls, safety guardrails, and responsible AI practices for systems that act on a customer's behalf. Ability to drive alignment across Engineering, Product, Infrastructure, and Security on problems that start out ambiguous. Experience mentoring senior engineers and shaping technical direction across multiple teams without direct authority. Comfort working in one or more of Ruby, Go, Python, or TypeScript, and willingness to work across the stack the platform spans. Excellent written and asynchronous communication, and the ability to work effectively in a fully remote, globally distributed organization. About the team The AI engineering organisation is building the product and infrastructure that make GitLab an effective environment for running agents across the software development lifecycle. We’re distributed across the world and partner with teams throughout GitLab to help the GitLab Duo Agent Platform become the backbone of GitLab's AI features. You will report directly to the VP of Engineering for AI and especially work together with all the teams, the engineering management and other principal engineers in the AI department. This is an opportunity to lead a consequential group as AI changes how software is built. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $250,000 — $325,000 USD 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 .

Location: Palo Alto 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   Mistral is seeking Research Engineer - Full Stack to facilitate the adoption of its products among internal stakeholders and collaborate with them to address complex technical challenges.   What You Will Do   • Collaborate closely with researchers, AI engineers, and product engineers on complex customer projects, integrating cutting-edge AI models into clients’ software products. • Design, develop, and maintain scalable and robust full-stack applications, ensuring seamless integration between front-end and back-end systems. • Develop complex use cases with our internal stakeholders, providing guidance and ensuring the best production integration with back-end and front-end interfaces. • Collaborate with our product and science team to continuously improve our product and model capabilities based on internal feedback.   WHAT WE'RE LOOKING FOR   • You are fluent in English • You hold a degree in Computer Science, Software Engineering, or a related field. • You have 2+ years as a technical individual contributor on cutting-edge technologies • You have strong technical coding skills in Python and TypeScript • You have experience with front-end frameworks such as React, NextJS, or VueJS. • You have experience with back-end technologies such as NodeJS. • You have a solid understanding of software development principles, including design patterns, data structures, and algorithms. • You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences   Ideally you have: • Experience with LLM/GenAI models • Contributed to open-source projects or libraries • Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager 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.

Bitmanager.ai — AI-стартап в категории conversational AI agents, создающий платформу для голосовых и текстовых AI-агентов в клиентских коммуникациях.

Компания МТС Банк использует современные цифровые решения и развивает технологичные банковские сервисы для B2B и B2C. Команды создают сайты на TypeScript + React + Next.js с SSR и реализуют проекты в Kubernetes-среде для обеспечения надежности. Задачи: — развивать платформу: участвовать в архитектурных обсуждениях, принимать ключевые технические решения, взаимодействовать с инфраструктурными командами и разработкой — управлять стратегией: формировать и реализовывать дорожную карту инфраструктуры с учетом масштабируемости, отказоустойчивости и безопасности — внедрять инновации: оценивать новые технологии и принимать решения об их интеграции — обеспечивать стабильность: мониторить состояние кластеров, сервисов и хранилищ — оптимизировать ресурсы: анализировать использование мощностей и предлагать меры по снижению расходов — поддерживать порядок: вести актуальную документацию — улучшать процессы: проводить ретроспективы, искать возможности для автоматизации и повышения эффективности Требования: — 5+ лет в SRE/devops/платформенной эксплуатации — глубокие знания Linux, сетей (L3/L4/L7, DNS, TLS, BGP, GSLB), контейнеризации и Kubernetes (Ingress, Istio, Helm, Kyverno, Keda) — навыки поиска узких мест и деградаций — опыт построения мульти-ЦОД кластеров Kubernetes — навыки работы с service mesh — знания и практическое применение сетевых плагинов Kubernetes (Calico, Cilium) — навыки работы и администрирования кластеров с ArgoCD, Vault, Consul — опыт работы с объемными плейбуками Ansible — опыт настройки CI/CD пайплайнов — практика построения мониторинга и алертинга: метрики, логи, трейсы (Opentelemetry, Jaeger, VictoriaMetrics, AlertManager) — будет плюсом опыт работы с Keycloak, Kubevela, OpenBao

Компания МТС Банк ищет специалиста на позицию ML/DevOps Engineer в Москве. Задачи: — деплоить и интегрировать модели, сопутствующие сервисы и инструменты, автоматизировать поставку и оптимизировать потребление ресурсов — мониторить и поддерживать работоспособность — обеспечивать соответствие политикам информационной безопасности и стандартам надёжности при развёртывании ML‑решений Требования: — уверенное администрирование Linux, понимание сетевых протоколов и потенциальных точек отказа — опыт конфигурации и распределения мощностей видеокарт для обучения и инференса моделей — опыт настройки мониторинга инфраструктуры и метрик деградации моделей — опыт работы с vllm, Triton Inference Server, FastAPI, KServe или TorchServe — опыт построения сложных многоэтапных пайплайнов с упором на безопасность Технологический стек включает Docker, Linux, Kubernetes, Bash, GitLab CI, Ansible, Terraform, Airflow, Python, vllm, cuda, triton, Prometheus/Victoria Metrics, Grafana, SQL, Postgres, Elasticsearch, MLflow, Qdrant, Nexus, Vault.

Работа в гибридном формате: около 1–2 дней в месяц в офисе в Wallingford, Великобритания.

TripleTen is an international platform of digital re-skilling products that helps people from diverse backgrounds learn new professions and build sustainable careers in tech. Languages: English (C1+). Remote work.

TripleTen is an international platform of digital re-skilling products that helps people from diverse backgrounds learn new professions and build sustainable careers in tech. Languages: English (C1+). Remote work.

Buffer is a social media management platform for scheduling, publishing, and analyzing posts across social networks. Remote work. 4-day workweek.

Buffer is a social media management platform for scheduling, publishing, and analyzing posts across social networks. Remote work. 4-day workweek.

Задачи: — Проектировать и строить backend-системы, которые являются чистыми, тестируемыми и эффективными. — Архитектурно создавать масштабируемые API и инфраструктуру, способную обрабатывать высоконадежные и высоконагруженные требования. — Вносить сильные мнения по тестированию, качеству и долгосрочной поддерживаемости в каждый проект. — Решать сложные продуктовые задачи, глубоко анализируя потребности пользователей и поведение системы. — Формировать инженерные практики и техническую культуру через сотрудничество и практическое лидерство. Требования: — Опыт работы backend-инженером от 5 до 7+ лет, предпочтительно 7+ лет. — Владение как минимум одним backend-языком, таким как Node.js/TypeScript, Python, Go или Java; опыт с Node.js и TypeScript является большим плюсом. — Опыт проектирования и архитектуры масштабируемой backend-инфраструктуры для высоконадежных или регулируемых сред, таких как финтех, платежи или идентификация. — Опыт работы с реляционными базами данных (Postgres или MySQL). — Опыт работы с очередями сообщений или событийно-ориентированными архитектурами (RabbitMQ, Kafka или аналогичные); знание паттернов Event Sourcing будет плюсом. — Опыт развертывания и управления приложениями в контейнеризированных или облачных средах (Kubernetes, AWS или аналогичные). — Сильное системное мышление, способность рассуждать о долгосрочных архитектурных последствиях, а не только о отдельных функциях. — Умение ясно коммуницировать, разбирать сложность и тесно сотрудничать с командой. — Комфорт в работе в условиях неопределенности и на ранних этапах развития, где практики активно формируются. — Обязательное проживание в европейском часовом поясе. Условия: — Полностью удаленная работа с обязательным нахождением в европейском часовом поясе. — Команда собирается лично периодически в течение года. — Базовая годовая зарплата от 116000 до 146000 евро, без индивидуальных переговоров по зарплате. — Визовая поддержка не предоставляется.

Location: Poland Workplace: Remote HI THERE!👋🏻 WE’RE TOOPLOOX 💎, A SOLVD INC. COMPANY We create AI-powered products and services that make a real difference. Our team of nearly 200 specialists - including a 40+ person R&D team with many PhDs - has pioneered AI solutions across industries from healthcare to e-commerce. We’ve published research in top-tier venues like NeurIPS and ICML, while delivering real-world applications that help our clients innovate and scale.   WHAT YOU WILL DO: - Collaborate with cross-functional teams to design and build AI Agentic solutions. - Contribute to defining technical requirements and implementing features across the software lifecycle - from proof of concept through implementation to evaluation and production. - Take ownership of assigned tasks and deliver high-quality, maintainable code. - Manage backend tasks while contributing to frontend development. - Stay informed about trends and advancements in AI and related fields, continuously learning and integrating new knowledge. - Employ a pragmatic, evaluation-driven approach to adopting innovative AI solutions.   EXPERIENCE AND SKILLS YOU NEED TO JOIN US: - Experience in full-stack development using mainly NodeJS (with TypeScript). - At least 1 year of experience in AI Engineering role. - Versatile in technology use, comfortable working across backend and frontend tasks. - Track record in staying current with AI and Agentic technologies, including best practices and architecture. - Openness to client collaboration, fostering clear communication and effective partnership. - Strong commitment to learning new technologies and swiftly adapting to new products and APIs. - Understanding of Retrieval-Augmented Generation (RAG) and its applications. - Familiarity with Multi-Agents concept, tools usage and MCP Servers. - Hands-on experience with LLM APIs/SDKs (e.g., OpenAI, Anthropic). - Knowledge of LLM orchestration and frameworks like Langchain or LlamaIndex, with practical implementation experience. - Understanding of prompt design principles and an ability to create effective prompts. - Experience configuring services on cloud platforms (e.g. AWS, Azure, GCP). - Basic experience with CI/CD pipelines and DevOps best practices. - Competence in REST API usage and efficient database integration. - Fluency in English language.   IT WOULD BE GREAT IF YOU ALSO HAVE: - Basic knowledge of machine learning principles. - Understanding Python source code. - Experience with React. - Experience with model fine-tuning and distillation. - Familiarity with LLM evaluation. - Experience with Model Context Protocol (MCP). - Experience with graph databases. - Familiarity with other programming languages and frameworks. - Familiarity with Voice Agents concepts and related frameworks e.g. Pipecat HOW WE WORK: At Tooploox 💎, you have the flexibility to choose your working hours ⏰ and location 📍. While we value remote work, we also believe in building relationships 🤝and invite you to join us in our Warsaw and Wrocław offices 🏢. Enjoy a relaxed atmosphere 🍃 and try some “home-made” pizza 🍕 from our office pizza oven. We love having pets 🐶 in the office, so feel free to bring yours along.😁 Join us and shape the future of AI while working the way you like!

Location: United Kingdom (Hybrid); United Kingdom (Remote); Spain; Netherlands Workplace: Hybrid Most money apps talk at you. Cleo talks back ✨ We're not building another finance app. We're building the world's first AI financial assistant, one that actually understands your money and makes you better at it, and we're changing the world's relationship with money in the process 💰 For everyone, whatever their background or balance. The proof: profitable, fast-growing, a unicorn with over $300M in ARR, and millions of people who now feel differently about their money. We love original thinkers who challenge the status quo. We move fast, tell the truth, and there's nowhere to hide from good work here. If that excites you more than it scares you, you'll fit right in. Follow us on LinkedIn https://www.linkedin.com/company/cleo-ai/ for new features and the occasional roast 🔥 MEET THE TEAM 👥 Here at Cleo, we have ~45 ML engineers ✨ They are the builders behind the AI that powers our product. They design experiments, create models that personalise financial insights, deploy fraud detection systems and scale our conversational AI, making sure that what we build genuinely helps people feel better about their money. From shaping product features and building the models that personalise our users' money journeys, to tackling fraud, scaling our systems and giving leaders the insights they need, our data team is at the heart of it all. ABOUT THE ROLE ✍️ We're hiring an ML Engineering Manager to join the existing data science function at Cleo - a collaborative team of ML engineers, analysts, and data engineers - to build and deploy production models that go directly into the product. You'll lead the ML workstream behind our Financial Assistant feature, shaping how Cleo uses LLMs to have more engaging, accurate, and personalised conversations about money. This is a people management role: you'll manage the ML engineers across your squads, own the headcount plan, and be responsible for hiring and team development in your area. - Understand the core problems faced by the Financial Assistant team and coordinate the ML function's contribution to solving them - Find opportunities for model and product improvements in Cleo's extensive customer behaviour datasets - Manage the ML engineers in your squads - coaching and developing them to deliver on the roadmap - Build out the headcount plan and own hiring and team development within your area to support growth WHAT WE'RE LOOKING FOR 🕵️ - Extensive experience building and deploying machine learning models to production - Experience managing and developing high-performing teams of data scientists and ML engineers - A habit of keeping abreast of the latest research and experimenting productively with new technologies, including LLMs and LLM agent design - Experience owning an ML roadmap, driving new ideas through to business impact - Ability to write production-quality Python code, with a willingness to stay somewhat hands-on - Nice to have: domain knowledge of NLP, including evaluating LLM systems and fine-tuning LLMs or other transformer models - Nice to have: a strong ability to communicate findings to non-technical stakeholders concisely and engagingly - Nice to have: experience with containers and container orchestration - Kubernetes, Docker, and/or Mesos - Nice to have: experience using vector databases such as OpenSearch WHAT WE OFFER We offer benefits package built to support you in and out of work. Benefits vary by country 🌍 and include meaningful equity, comprehensive health insurance, mental health support, a paid one-month sabbatical after four years, a learning & development platform, pension or retirement contributions, and location-specific leave entitlements. For the full breakdown on what's available in your location, visit our Candidate Hub https://meetcleo.notion.site/Cleo-Candidate-Hub-3b95c63b874580e9a068fdc6c8929ebf 👈 WHAT MATTERS Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their merits. We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know. We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!