AI-инженер (LLM, агенты, AI product) вакансии

Обязанности: • разработка и сопровождение AI-агентов для автоматизации процессов оценки кредитного риска • интеграция LLM и ML-моделей в агентные пайплайны (оркестрация, tool-calling, memory, RAG) • проектирование агентных архитектур: определение инструментов, стратегий и логики принятия решений • написание технической документации: описание агентов, регламенты, схемы взаимодействия. Требования: • опыт разработки на Python от 3 лет, особенно в контексте написания бизнес-логики или скриптов автоматизации • уверенное и архитектурных паттернов • опыт работы с агентными фреймворками: LangChain, LangGraph, AutoGen, CrewAI или аналоги • понимание ML (train/inference): xgboost, catboost, lightgbm, pytorch — опыт интеграции моделей в продуктовые системы • работа с Python-библиотеками pyspark / pandas / numpy для анализа данных • опыт работы с HTTP(S), RESTful API (интеграция агентов и моделей с внешними сервисами) • опыт работы с Docker; базовые знания Kubernetes и Helm • опыт работы с Git Условия: • комфортный современный офис рядом с м. Кутузовская • график работы- гибрид • ежегодный пересмотр зарплаты, годовая премия • корпоративный спортзал и зоны отдыха • более 400 образовательных программ СберУниверситета для профессионального и карьерного развития • расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа • гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ • бесплатная подписка СберПрайм+, скидки на продукты компаний-партнеров • вознаграждение за рекомендацию друзей в команду Сбера.

Требования: — От 6–12 месяцев активного интереса к AI — Понимание различий между AI-моделями — Наличие собственных проектов или экспериментов — Базовое понимание кода и API — Системное мышление Обязанности: — Разработка и внедрение AI-автоматизации — Работа с Claude Code и AI-агентами — Отслеживание новых моделей и инструментов — Декомпозиция бизнес-задач и автоматизация Условия: — Полностью удаленный формат, частичная занятость — Стартовая ставка 60–80 тыс. ₽/мес. — Оплата профессиональных подписок — Бюджет на эксперименты и доступ к данным e-commerce

Задачи: — разработка и поддержка сервисов на Python с использованием async — работа с Large Language Models (LLM) и их интеграция — разработка на LangChain и LangGraph — оптимизация SQL-запросов — prompt-инжиниринг и настройка LLM-инференса Требования: — высшее образование в области технических или физико-математических наук — опыт работы с различными LLM — опыт разработки на LangChain и LangGraph — актуальный опыт работы на схожей должности от года — 3+ года опыта программирования на Python — опыт работы с async-сервисами — глубокое знание SQL и оптимизации запросов — опыт prompt-инжиниринга и настройки LLM-инференса Условия: — полная занятость — офис в Москве — зарплата от 260 000 до 325 000 ₽ в месяц

Location: Ireland; OPEN TO ALL LOCATIONS Workplace: remote Irish Speaker - AI Testing Project Remote Opportunity | AI Testing Project – Irish Speakers Are you a proficient Irish speaker with an interest in AI and flexible remote work? We’re looking for detail-oriented individuals to help test and improve an exciting new tool developed by a top global tech company. This is a remote, part-time project with flexible hours — perfect if you want to earn extra income while contributing to the future of technology. Project Details: Pay: $20–$35 USD/hour Hours: Up to 15 hours per week Duration: Minimum 2 months (with possible extension) Location: 100% remote – work from anywhere! Your Profile: Proficient Irish speaker Good command of English (to follow instructions and complete simple reports) Comfortable with basic tech setups (installing apps, following troubleshooting steps) Familiar with Microsoft 365, especially MS Teams Owns a computer with speakers and a mic Available to work 1–3 hours per day over 8–12 weeks Curious about AI and emerging technologies Open to a standard onboarding check  No prior experience in AI needed – just a sharp mind and a willingness to learn! Interested? Apply now or send us a message to learn more at vaishali.gonty@lionbridge.com Help shape the future of AI – in your own language.

Требования: - Знакомство с LLM-харнесом - Базовый код на Python / JS / TS - Опыт работы с Linux, Docker, git - Самостоятельность в выполнении задач - Английский на уровне чтения документации Обязанности: - Писать интеграции AI-агентов - Допиливать внутренние сервисы - Собирать лендинги и продуктовые страницы - Делать UI поверх AI-сервисов Условия: - Удаленная работа, гибкий график - Минимальная стажировка или стажировка с гарантией продолжения сотрудничества - Подписки на ведущие AI-инструменты за счет компании

Задачи: — Разработка desktop приложений на TypeScript + React (Electron / Tauri). — Работа с Node.js, WebSocket, стримингом и очередями. — Интеграция топовых AI-провайдеров и работа с локальным инференсом. — Создание функционала AI-агентов (tool calling, automation, sub-agents). — Интеграции с Telegram, Discord, Slack и WhatsApp. — Релизы, CI/CD и обеспечение качества продукта. Требования: — 2+ года коммерческого опыта с TypeScript, Node.js и React. — Реальный опыт работы с Electron или Tauri. — Уверенное владение WebSocket, Docker и GitHub Actions. — Активное использование AI-инструментов в работе. — Английский для чтения документации и рабочих задач. Будет плюсом: — Знание Python (FastAPI), MCP и опыт LLM-интеграций. — Опыт с Playwright или нативными API macOS/Windows. Условия: — Работа в офисах в Санкт-Петербурге и Москве. — 28 дней отпуска. — Компенсация профессионального обучения и курсов. — Гибкое начало рабочего дня. — Работа над передовым продуктом в сфере искусственного интеллекта. — Постоянный обмен опытом и возможность быстрого роста.

Location: Europe; Brussels; Munich; London; Edinburgh; Paris; Berlin; United Kingdom; France; Frankfurt; Germany Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! ABOUT NORTH: North https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. WHY THIS ROLE? This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. We’re looking for Software Engineers with Applied AI experience who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs), from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows. You’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one. In this role, you will: - Work closely with our enterprise customers to translate high-value, ambiguous business problems into well-framed agentic workflows with clear success criteria and evaluation methodologies - Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools, APIs, and sensitive enterprise data sources, with enterprise-grade reliability and performance - Build and ship features for North, our AI workspace platform, working across the full product lifecycle from conceptualisation through production - Take ownership of scoping and shaping use cases end-to-end, flexing into whatever technical area the problem demands (including frontend) to drive the most effective solution - Contribute to shared frameworks and patterns that enable consistent, high-quality delivery across customers and teams - Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization - Travel up to 20–40% to work on-site with customers and partners You may be a good fit if: - You have hands-on experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code - You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute - You're deeply familiar with the LLM stack: frontier models, vector databases, and orchestration frameworks - You have a proven ability to build robust evaluation frameworks, moving well beyond trial and error, to measure agent accuracy, safety, and latency - You’re experienced working directly with customers and can lead technical discussions with enterprise stakeholders, translating ambiguous business needs into concrete technical specs - You have experience owning the full scope of a use case end-to-end - You thrive in fast-paced and ambiguous environments and can execute well even when priorities are shifting It's a bonus if you have: - Experience setting architectural standards for AI and agentic systems across distributed teams - Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it - Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms) - Experience with enterprise security, compliance, or auditability requirements for AI systems FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Location: Hong Kong, Hong Kong SAR Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity You will be responsible for product planning and solution design for an enterprise-grade AI Native engineering platform, driving the deep integration of AI Agents, AI Coding, knowledge capabilities, and engineering platform systems. The goal is to build an intelligent product system covering requirement analysis, solution design, development collaboration, testing validation, environment orchestration, and knowledge accumulation.This role serves complex engineering processes and multi-role collaboration scenarios. You are expected to design AI product capabilities that can be embedded into workflows, measured for impact, and continuously evolved in real enterprise environments, enabling the product to scale from pilot adoption to broad organizational rollout. What You’ll Be Doing Lead the product planning, requirement analysis, and solution design of the AI Native engineering platform, and drive continuous product evolution and adoption. Develop a deep understanding of the end-to-end engineering lifecycle, and translate the core scenarios and collaboration patterns of product, design, engineering, QA, and operations teams into structured product solutions. Design AI Agent capabilities for engineering scenarios , including requirement analysis, solution generation, coding collaboration, test generation, environment orchestration, and knowledge accumulation. Drive the integration of AI capabilities with code repositories, CI/CD pipelines, testing platforms, deployment environments, and knowledge platforms to deliver a unified end-to-end product experience. Establish mechanisms for product effectiveness evaluation, user feedback, and continuous optimization , and support the product’s scale-up from pilot validation to broad adoption. What We Look For In You Bachelor’s degree or above , preferably in Computer Science, Software Engineering, Artificial Intelligence, or related fields. 8+ years of experience in ToB products, platform products, or intelligent product solutions. Must have an engineering background , such as software development, test development, architecture, or technical product roles, with the ability to work effectively with engineering teams. Strong understanding of DevOps , engineering productivity, software delivery processes, and quality systems , with the ability to abstract and productize complex workflows. Solid understanding of AI Agent product design , with the ability to design for task execution, workflow orchestration, result validation, and delivery closure. Familiarity with mainstream AI coding products, with strong hands-on experience or product understanding of Claude Code , Codex, Cursor , and Copilot , as well as context engineering, knowledge input, tool integration, human-in-the-loop collaboration, and governance considerations. Strong structured thinking, cross-functional collaboration, and execution skills; experience with engineering platforms, DevOps platforms, platform products, or intelligent products is a plus. Nice to Haves Experience with products related to AI Agents, RAG, knowledge graphs, Copilot, or intelligent workflows . Experience building engineering platforms, DevOps platforms, or platform products from 0 to 1 or from 1 to N. Hybrid background of engineering-to-product transition , or contributions to open source, communities, or public thought leadership in AI or engineering productivity. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependents. More that we love to tell you along the process! Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong. Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: United Kingdom; Brazil; Ireland; Peru; Costa Rica; Latvia; Argentina; Romania; Cyprus; Portugal; Slovenia; Lithuania; South Africa; Czech Republic; Panama; Estonia; Canada; Hungary; Mexico; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. Kraken is building a dedicated AI Compute and Infrastructure team to power the next generation of model training, inference, evaluation, and experimentation across the exchange. This team sits within engineering leadership and owns the infrastructure layer that lets Kraken run AI workloads with control, speed, reliability, and cost discipline. The team is responsible for GPU and accelerator infrastructure, cluster operations, scheduling, model serving, observability, capacity planning, and cost-efficient compute at scale. This is the backbone that allows Kraken to train, serve, evaluate, and iterate on AI systems in-house where it matters for privacy, latency, reliability, cost, or product differentiation. You will join a small, senior, high-impact team working directly with AI/ML researchers, platform engineers, security teams, and product teams. The mandate is simple: make Kraken's AI ambitions real by building compute infrastructure that is fast, dependable, efficient, and production-grade.   THE OPPORTUNITY - Own and operate GPU and accelerator clusters used for training, inference, evaluation, and experimentation, including drivers, runtimes, kernels, device plugins, node configuration, scheduling primitives, and workload isolation. - Design infrastructure that enables Kraken teams to run models locally on GPUs where it is strategically and economically preferable, reducing unnecessary dependency on external providers and containing compute costs. - Build and improve scheduling, orchestration, placement, quota management, and utilization systems across heterogeneous accelerator environments. - Optimize inference pipelines for latency, throughput, reliability, memory efficiency, and cost using frameworks such as vLLM, Triton Inference Server, TensorRT, or equivalent serving stacks. - Partner with ML engineers and researchers to remove bottlenecks in training, evaluation, batch inference, online inference, deployment, and production debugging workflows. - Build observability for GPU utilization, memory pressure, queue depth, saturation, token throughput, request latency, failed workloads, capacity pressure, and spend. - Drive reliability, incident response, alerting, runbooks, and post-incident improvements for always-on AI compute infrastructure. - Evaluate and integrate new hardware, cloud instance families, specialized accelerators, runtimes, schedulers, and serving frameworks as the AI infrastructure landscape evolves. - Build tooling that makes GPU usage visible, accountable, and easier for internal teams to consume without needing to become infrastructure experts. - Contribute to long-term architecture decisions that balance performance, cost efficiency, scalability, operational simplicity, and production safety.   WHAT YOU BRING - 5+ years of infrastructure engineering experience, with significant time spent on GPU compute, ML infrastructure, distributed systems, high-performance computing, or large-scale production platforms. - Hands-on experience operating GPU clusters or accelerator-backed infrastructure in production or production-like environments, including scheduling, orchestration, utilization monitoring, and cost optimization. - Strong systems engineering fundamentals across Linux, networking, storage, containers, Kubernetes, distributed runtimes, and production debugging. - Experience with ML serving frameworks such as vLLM, Triton Inference Server, TensorRT, TorchServe, KServe, Ray Serve, or equivalent systems. - Proficiency in Python for infrastructure automation, tooling, debugging, integration, and operational workflows. - Practical understanding of performance tradeoffs across batching, concurrency, memory usage, GPU utilization, model size, latency, throughput, availability, and cost. - Track record of optimizing compute costs while maintaining clear performance, reliability, and availability expectations. - Experience building observable systems with useful metrics, logs, traces, dashboards, alerts, and incident workflows. - Comfortable working in high-stakes, always-on environments where uptime, throughput, correctness, and operational discipline are critical. - Clear communicator who can translate infrastructure tradeoffs for researchers, product teams, platform engineers, security stakeholders, and engineering leadership.   NICE TO HAVES - Experience at a frontier AI lab, hyperscaler, high-frequency trading firm, research platform, or high-scale ML organization. - Familiarity with custom silicon or specialized accelerators such as TPUs, AWS Trainium, Gaudi, or similar platforms. - Background in capacity planning, procurement input, reserved capacity strategy, cloud accelerator economics, or GPU fleet cost management. - Experience with distributed training frameworks such as DeepSpeed, Megatron-LM, FSDP, Ray, or equivalent systems. - Experience debugging CUDA, NCCL, kernel, driver, runtime, memory, networking, or low-level performance issues. - Experience with Rust, C++, Go, CUDA, or other systems languages used for performance-critical infrastructure. - Crypto, financial services, trading infrastructure, or security-sensitive production infrastructure experience. Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: New York, NY; Austin, TX; San Francisco, CA Workplace: Hybrid ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the Role: We are looking for an GTM Engineer where you won’t just be using our tools—you’ll be the "First Customer," building the AI-native systems that power our technical support, onboarding, and customer success engines. You will own the technical roadmap for how LangChain supports its users. Your goal is to drive massive case deflection and a premium onboarding experience by building autonomous agents that solve complex technical problems before a human ever needs to step in. This is a role for a builder-operator who can identify a friction point in the customer journey and ship a production-grade agentic solution to fix it. YOU WILL: - Architect Customer Agents: Design and deploy production-grade agents (using LangGraph and LangSmith) that handle technical support queries, troubleshoot integrations, and guide users through complex onboarding flows. - Drive Case Deflection: Analyze customer friction points and build self-service AI systems that significantly reduce support volume while improving the quality of the customer experience. - Own the Domain: Act as the product owner and the technical muscle proactively identifying opportunities for improvement, propose architectures, and own the full lifecycle of the systems you build. - Dogfood the Stack: Be a key member of the feedback loop for our product team. As you build complex systems for our customers, you’ll identify gaps in our frameworks and contribute back to the LangChain and LangGraph open-source ecosystem. - Build Onboarding Workflows: Develop "AI-native onboarding" experiences that help enterprise customers move from prototypes to production faster by automating documentation retrieval and code generation. WHAT WE ARE LOOKING FOR: - AI-Native Developer: You have a deep understanding of the LLM stack: prompting, retrieval (RAG), cognitive architectures, and agentic loops. You have likely already built with LangChain or LangGraph. - Engineering Foundation: You are a strong software engineer (typically 3+ years) with at least 1 year of experience specifically shipping LLM systems in production. - Self-Directed "Founder" Mentality: You don't need a ticket to tell you what to fix. You are comfortable navigating ambiguity, identifying high-impact problems, and driving them to completion autonomously. - Full-Stack Capability: Strong coding skills in Python or TypeScript (ideally both) and the ability to build end-to-end applications. - Customer-Centric: You enjoy the intersection of high-level engineering and direct customer impact. You can translate a customer's technical pain point into a scalable system architecture. Nice to Haves: - Expertise with LangSmith for evaluation and monitoring. - Experience building or maintaining open-source projects. - A background in technical consulting, solutions engineering, or high-growth GTM teams. Compensation: - We offer competitive compensation that includes base salary, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. - Salary: $160K - $180K Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Задачи: — Создание и улучшение моделей компьютерного зрения для производственных задач. — Разработка конвейеров обработки изображений для промышленных сред. — Работа с камерами, освещением и системами сбора данных. — Разработка решений для обнаружения дефектов и контроля качества. — Развертывание и оптимизация моделей ИИ реального времени для периферийных/производственных сред. — Сотрудничество с командами по продуктам и инженерии. Требования: — Опыт работы в компьютерном зрении: классификация, обнаружение аномалий, обнаружение/сегментация объектов. — Уверенное владение Python + PyTorch / TensorFlow. — Опыт работы с промышленными системами зрения (камеры, освещение, конвейеры изображений). — Опыт обнаружения дефектов в производственных средах является большим плюсом. — Опыт развертывания высокоточных моделей реального времени (edge / production) с акцентом на точность и надежность. Условия: — Удаленная работа из любой страны. — Быстрорастущая компания с возможностями карьерного роста. — Прямое влияние на продукт. — Опционы компании в случае успешного сотрудничества.

Location: Georgia Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are seeking a dynamic and motivated Senior AI NodeJS Engineer with a strong focus on developing AI Agents. If you have an understanding of AI technologies and thrive on applying diverse tech stacks to build innovative solutions, we want to hear from you. This role involves not only technical expertise but also collaboration with clients to understand and refine project requirements. 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. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Location: Paris, France Workplace: OnSite 🤖 WHO WE ARE We’re building Mo — a health companion for everyone. We’re a small team within Alan, on a mission to redefine the future of care by democratizing access to medical expertise. We are building Mo, an intelligent, empathetic, multimodal LLM-based conversational AI assistant able to prescribe, triage, and proactively follow up on care. Imagine giving every person in the world instant, 24/7 access to personalised medical expertise - through chat, voice, or video. That’s what we are building 🤖. We kicked off the project in 2023, and we have launched Mo to all our french members (1M) in Q1 2026, making it the first safe AI health companion live at scale in Europe. 🚀 WHAT KEEPS US UP AT NIGHT We’re building a medical agent that works — reliably, safely, and at scale. You’ll work at the intersection of product engineering, ML engineering, and medical expertise. Our mission is to build the most accurate and reliable medical agent in the world, while delivering an outstanding conversational experience. Things we’re working on: - 💬 Deliver the most memorable chatting experience — You’ll work on making Mo the obvious choice when it comes to asking a health question. It means having a world-class snappy and delightful chatting experience, blazing fast time to answer, and rich content shared. - 🧱 Integrate Mo with Alan services and our healthcare system — You’ll work on integrating Mo with our other services (digital chat with HP, map of physical location of HPs, tailored prevention programs, …) to help members get from words to actions. - ➕ Extend our architecture to support the next chapters of Mo — You’ll work on our architecture, and agentic framework, to support Mo’s next needs (get more context, use new skills, be accessible in other countries we operate in) If you’re excited by the idea of building the future of healthcare, this is the team for you - we're at the start of the journey. If you’re curious, here https://arxiv.org/abs/2411.12808 is a paper we published recently. 🎯 IS IT YOU WE’RE LOOKING FOR? We’re looking for Product engineers with 3+ years of experience who get excited about building state-of-the-art AI systems and applying them to real-world, high-stakes problems in healthcare. - You’ll work at the frontier of LLMs, multi-agent architectures, and human-in-the-loop learning — and see your work deployed in production, helping real people. - You’ll implement new capabilities for Mo, working across engineering, data, and medical expertise - You'll have deep product ownership over the use cases supported in Mo, making sure we actually help our members get and stay better. - You’ll have significant influence on system architecture and code quality - You’ll mentor engineers, contribute to our product & engineering culture, and help build the team (including participating in hiring, shaping our interview loops, etc.). You would be a good fit in Mo if most of this sounds like you: - Applied background in software engineering and systems architecture - Experience with traditional ML, or LLMs, or ML dev ops is a big plus. - Product-minded: you want your solutions to be used, and impactful - Self-directed, pragmatic, driven, hard working - Humble and still willing to grow (no matter your seniority!) - Collaborative, enthusiastic about teamwork, learning, and teaching - Fluent in English (no need to speak French!) - Ex-founders are typically great fit in our team But above all, we are looking for high potential and curiosity: make sure to show us this when you apply! Everything else is a bonus. 🤘 HOW WE DO IT ? We benefit from Alan’s platform, infrastructure, distribution, and health expertise — but operate with the speed and focus of a startup. If you’re curious about Alan’s broader vision, our https://www.notion.so/alaninsuranceShareholder Letters https://alan.com/en/blog/discover-alan/a/alan-2025-q3-letter-to-shareholders are worth a read. People joining Alan are often surprised and delighted by our innovative working method. We have a set of cultural values https://alan.com/about/company-culture that guide our approach to work, such as: HOW WE WORK: OUR LEADERSHIP PRINCIPLES - Mission is the Boss — We think long-term and are methodical optimists who take risks, seeking our mission's success above all else. - Distributed Ownership — Accountable enlightened despots: everyone owns their decisions and results. - Radical Transparency — All information is accessible and written-first, so everyone can make the best decisions asynchronously. - Always Growing — Direct, positive, and caring feedback, combined with self-growth ownership. 🙌 PERKS & BENEFITS https://alan.com/en/careers/a/salary-equity At Alan, we believe that being in good health is a basic need, and it starts with our employees. This is why Alaners are provided with a stimulating environment and perks ensuring they are happy, efficient and spend only high-quality time with co-workers. Therefore, we offer: - Fair rewards. Generous equity packages complement your base salary. - Flexible Office. Amazing office space at our HQ, sponsored co-working hubs or a full-remote experience with home office equipment sponsorship, we want you to live where you’re the happiest. - All the tools you need. Top of the range equipment: Macbook Pro, keyboard, laptop stand, monitor, and noise-canceling headphones. - Flexible vacation policy and flexible working hours. Organize your time as you wish. - Delightful healthcare insurance: Extremely comprehensive health insurance - 100% for you and your children, 90-100% for partners depending on your country (permanent contracts only). - Transport. Country-specific commuter benefits. - Learning & Training opportunities. A highly flexible Training policy free books and budget to attend and speak at conferences if the opportunity arises. - Personal growth through coaching: At Alan, coaching isn't just a perk - it's core to who we are. Every Alaner is paired with a dedicated coach from day one, who helps maximize their impact, nurture engagement, and navigate Alan's values to develop their full potential. Learn more about our coaching culture https://alan.com/en/blog/discover-alan/a/alan-culture-excellence-through-coaching. - Parental leave. Extended parental leave for all new parents. IMPORTANT NOTE: WE HIRE PEOPLE, NOT ROLES. If you're excited about this opportunity but don't check every box, we'd love to hear from you. Everyone, no matter how underrepresented, should feel free to apply as it can only bring learnings or success. If you identify yourself as a woman: Did you know that research shows women often apply only when meeting 100% of requirements? Remember, this is just a guide, not a checklist. We'll be thrilled to receive your application! 🔖 Check out our About Alan https://alan.com/about and Career https://alan.com/careers pages, as well as our Medium https://medium.com/alan, blog https://blog.alan.com/ and Glassdoor page https://www.glassdoor.com/Overview/Working-at-Alan-EI_IE1696043.11,15.htm for more info. #LI-DNP

Location: Raleigh, NC Workplace: Remote ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $150,000–$250,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Charlotte, NC Workplace: Remote ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $150,000–$250,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Singapore, Singapore OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa. Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the Opportunity You will be responsible for the core architecture design and technical delivery of an enterprise-grade AI Native engineering platform, driving the deep integration of large language models, AI Agents, knowledge capabilities, and the software development lifecycle. The platform will support intelligent capabilities across requirement analysis, solution generation, coding collaboration, test automation, and environment orchestration.This role focuses on engineering-grade AI implementation in complex R&D scenarios. You are expected to turn model capabilities into reusable, scalable, and governable platform capabilities, and continuously drive the evolution of the engineering platform toward an AI Native architecture. What You’ll Be Doing Lead the overall architecture design and core capability development of the AI Agent platform, including task orchestration, tool invocation, context management, memory mechanisms, and multi-agent collaboration. Drive the implementation of AI Native capabilities in engineering workflows , including AI coding, technical solution generation, test case generation, test report generation, and automated environment deployment. Build the knowledge augmentation layer for the platform, including the design, integration, and application of RAG, GraphRAG, and knowledge graph capabilities. Establish the runtime and governance framework for AI Agents, including execution isolation, permission control, auditability, evaluation, stability, and cost governance. Collaborate with product, engineering, QA, and operations teams to standardize, productionize, and scale platform capabilities, continuously improving engineering efficiency and delivery quality. What We Look For In You Bachelor’s degree or above , preferably in Computer Science, Software Engineering, Artificial Intelligence, or related fields. 6+ years of experience in backend engineering, platform engineering, or infrastructure engineering, with strong system design and delivery capabilities. Proficient in Java / Python , with solid coding skills, architectural thinking, and experience building complex systems. Strong understanding of LLM and AI Agent architectures , including task decomposition, tool use, context management, memory, execution loops, and exception handling. Hands-on experience with LangChain and LangGraph , and strong familiarity with mainstream AI coding tools or frameworks such as Claude Code , Codex, Cursor , and Copilot . Experience in designing or developing RAG / GraphRAG / knowledge graph solutions for enterprise knowledge augmentation and engineering use cases. Good understanding of DevOps , CI/CD , Kubernetes , and cloud-native technologies , with strong cross-functional collaboration and execution skills. Nice to Haves Experience contributing to open-source projects related to AI Agents, AI Coding, RAG, or knowledge graphs. Experience building enterprise engineering platforms, DevOps platforms, or AI platforms . Familiarity with open-source Agent projects such as openclaw, openhands/openharness, or Hermes . Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .