Вакансии

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We’re looking for a Senior Staff Machine Learning Engineer to lead Reddit’s next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform. This role requires deep expertise in mainstream ML user modeling approaches (e.g., large-scale embeddings, user interest modeling, affinities, behavioral signals) and the ability to reimagine these systems in the GenAI era—leveraging LLMs and foundation models to unlock step-change improvements in fidelity, adaptability, and expressiveness. You will set the technical direction for this space, leading the design and implementation of Reddit’s core user representation layer—spanning embeddings, interest modeling, and key user attributes. You’ll ensure this foundation is scalable, reliable, and widely adopted across Feeds, Search, Notifications, and Ads, partnering closely with product, infrastructure, and downstream ML teams to drive measurable impact. This is a high-impact role. The systems you build will shape how hundreds of millions of people experience Reddit every day—what they see, what they discover, and the communities they connect with. Your work will directly advance personalization and relevance at global scale, strengthening Reddit as a platform for meaningful connection and belonging. What you'll do: Design User Understanding Strategy: Define a unified user understanding framework and strategy: how users are represented (embeddings, tags, attributes, LLM-based user profile), how they are computed, stored, and exposed. Provide thought leadership in user understanding and user modeling by setting a long-term technical vision and advancing the state-of-the-art in the field. Build Foundational User Models: Lead design and implementation of advanced user models, e.g. large-scale user representation learning (sequence-based, multi-interest, multi-task) that share representations across surfaces to improve personalization experience across key Reddit products e.g. Feeds, Notification, Search and Ads, balancing latency, cost, and performance. Reimagine user understanding with LLM/Gen-AI: Evolve user modeling beyond traditional representations by leveraging LLMs to build richer user understanding (e.g., dynamic user profiles, intent inference, semantic reasoning over user behavior). Explore how LLMs can augment or unify embeddings, attributes, and taxonomies to enable more adaptive, interpretable, and context-aware personalization. Ship Large Scale User Understanding as a System: Partner with platform teams to design and build core components for large-scale learning and serving: storage/retrieval for embeddings, feature pipelines, and APIs. Collaborate with ML/Ranking infra to ensure low-latency serving, high availability, and integration with MLOps systems. Drive Cross-Team Integration & Impact: Partner with Feeds, Notification, Search and Ads teams to drive experimentation and adoption of new user understanding models with product teams across Reddit, ensuring measurable end-to-end impact on key metrics. Set Technical Bar & Mentor: Mentor senior to staff engineers, lead design reviews, steward technical decisions across the user understanding domain, and champion and drive engineering processes and best practices Who you might be: You have at least 10 years experience building and scaling production-grade ML systems, particularly in user modeling, large-scale representation learning, or recommender systems. You have a track record of driving ambiguous, high-impact initiatives from concept to production, shaping both technical direction and execution. You are product- and impact-oriented: you care deeply about how your work moves real metrics (e.g., engagement, retention, revenue), not just model quality. You bring strong fundamentals in mainstream user understanding ML approaches (e.g., representation learning, behavioral modeling, user clustering), and understand their trade-offs in real-world systems. You are excited about the GenAI shift and have experience (or strong intuition) applying LLMs or foundation models to evolve existing systems,  going beyond incremental improvements. You think in systems, not just models: you consider data, training, evaluation, serving, and adoption as a cohesive whole, and design with end-to-end impact in mind. You influence beyond your immediate team: partnering effectively with product, infra, and other ML teams, and driving alignment across multiple stakeholders. You raise the technical bar: mentoring senior engineers, leading design reviews, and establishing best practices for building reliable, scalable ML systems. You are comfortable navigating trade-offs across quality, latency, cost, and safety, especially in large-scale, user-facing systems. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave #LI-remote, #LI-JS5 Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $266,000 — $372,400 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Задачи: — Разработка и развитие production LLM/AI-систем и AI-агентов. — Построение многошаговых agentic workflows: routing, tool calling, state management. — Работа с prompt- и context-engineering, управление памятью и состоянием диалога. — Реализация structured output и function/tool calling. — Создание RAG-пайплайнов: chunking, embeddings, retrieval, reranking. — Интеграция LLM с API, базами данных и внутренними сервисами. — Разработка backend на Go и AI-компонентов на Python. Требования: — Умение собирать LLM-систему целиком — от prompt/context logic и агентов до backend, интеграций и запуска в production. — Основной стек — Go для production-backend и высоконагруженной логики, Python для AI-инфраструктуры и прототипирования. — Опыт построения agentic workflows, управления состоянием диалога и памяти. — Понимание RAG, embeddings, retrieval и reranking. — Навыки тестирования и оценки качества: evals, regression tests, golden datasets, LLM-as-a-judge. — Умение выбирать модели с учётом качества, latency и стоимости. — Анализ логов и трасс для повышения стабильности.

Location: Hybrid About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Location:  Austin, Dallas or Houston TX Senior Customer Engineer SLED *This is a work-from-home 100% remote role, but you should reside in Texas." What you’ll do as a Senior Customer Engineer SLED About the Role At Cloudflare , we are on a mission to help build a better Internet. As the architectural complexity of enterprise solutions scales, we are evolving how we partner with our customers. The Customer Engineer (CE) represents the core driver of our technical go-to-market strategy: a trusted advisor who owns the technical relationship from the initial discovery phase through to long-term adoption and ongoing account expansion. Sitting within the GTM organization and reporting to the Regional Customer Engineering Leader, this specialized role will focus heavily on our SLED (State, Local, and Education) and Local Government sectors. You will not hand off your customers once an initial agreement is reached. Instead, you will operate as a quota-carrying technologist, utilizing AI-augmented workflows to eliminate administrative toil so you can focus on high-value architectural design and driving measurable business outcomes across the entire public sector customer journey. Key Responsibilities Technical Validation : Partner closely with Account Executives to lead technical discovery, build bespoke architectures, and deliver compelling product demonstrations and Proof of Concepts (PoCs) across Cloudflare’s portfolio (Security, Networking, and Developer Platforms) tailored to public sector procurement and compliance standards . Customer Adoption & Value Realization : Lead and/or provide oversight to technical onboarding and implementation, serving as the primary executive and engineering contact for the customer. You will partner with Account Executives to own discovery, demos, onboarding, technical health, risk, and expansion strategy. You will proactively monitor dynamic customer health scores and telemetry to ensure rapid time-to-value and resolve integration bottlenecks common in municipal and educational IT infrastructures . Commercial Accountability & Expansion : Carry a variable quota tied directly to new business acquisition and/or ongoing account growth. You will be commercially accountable for ensuring deep platform adoption, retaining revenue, and identifying strategic cross-sell and up-sell opportunities based on product usage data. Lead technical Quarterly Business Reviews (QBRs) to translate platform capabilities into return on investment for C-level executives. Trusted Advisory : Act as a trusted technical advisor throughout the entire customer lifecycle, maintaining a continuous, deep relationship with key stakeholders from initial onboarding through maturity, renewal, and expansion. AI Orchestration & Workflow Automation : Act as an "AI-Augmented" engineer. Leverage AI agents and internal platforms to automate routine tasks such as RFP/Security Questionnaire responses, sandbox provisioning, and basic telemetry monitoring, reclaiming your time for strategic customer advisory. Minimum Qualifications Public Sector Expertise : Proven experience working with or selling into SLED, Local Government, State or Municipal agencies , with a deep understanding of public sector buying cycles, compliance requirements, and unique government IT constraints. Experience : Experience in a customer-facing technical role, such as Solutions Engineering, Customer Engineering, Sales Engineering, or as a Forward Deployed Engineer (years of experience required will vary based on Associate, Senior, Staff, or Principal leveling). Technical Acumen : Broad technical expertise spanning web security, networking (routing, DNS, DDoS mitigation), cloud infrastructure, and enterprise architecture. Commercial Mindset : Proven track record of operating in a quota-carrying or revenue-aligned environment, with a strong understanding of SaaS metrics, business value translation, and public sector/enterprise sales cycles. Communication : Exceptional presentation and stakeholder management skills, capable of bridging the gap between deep technical implementation details and high-level government C-suite/elected official business strategy. Strongly Preferred Qualifications (The "Good-to-Haves") Cloudflare AI Stack Experience : Hands-on experience building, deploying, or architecting solutions using Cloudflare's developer platform and AI ecosystem, specifically Workers AI, AI Gateway, and Vectorize. Applied AI Knowledge : Experience with prompt engineering, Large Language Model (LLM) orchestration, or Retrieval-Augmented Generation (RAG) architectures. Coding/Scripting : Proficiency in Python, JavaScript, or similar languages to write custom integration scripts, API connectors, and edge computing functions. Compensation Compensation may be adjusted depending on work location. For Texas based hires: Estimated annual salary of $231,000-$275,000+ OTE, Base + Commissions Equity This role is eligible to participate in Cloudflare’s equity plan. Benefits Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S. Health & Welfare Benefits Medical/Rx Insurance Dental Insurance Vision Insurance Flexible Spending Accounts Commuter Spending Accounts Fertility & Family Forming Benefits On-demand mental health support and Employee Assistance Program Global Travel Medical Insurance Financial Benefits Short and Long Term Disability Insurance Life & Accident Insurance 401(k) Retirement Savings Plan Employee Stock Participation Plan Time Off Flexible paid time off covering vacation and sick leave Leave programs, including parental, pregnancy health, medical, and bereavement leave What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

Location: Yerevan, Armenia Problem Space Logistics operations today are still largely: manual reactive fragmented across tools running on incomplete or late data full of conflicting constraints under real-time decision pressure driven by evolving business rules a mix of legacy and new systems Much of this is unstructured: emails, documents, free-text updates, exceptions nobody modelled. That is where AI changes the game. We’re building a system that: ingests real-time operational data, structured and unstructured supports planning and execution decisions, with AI agents that act where it’s safe and hand over to humans where it isn’t adapts to constantly changing constraints What You’ll Work On AI in production. Building LLM- and agent-powered features into production .NET services: tool calling, structured outputs, retrieval over operational data, document and message understanding. The seams. Designing the boundaries between deterministic business logic and probabilistic AI: validation, fallbacks, human-in-the-loop. Trust. Making AI measurable and trustworthy: evals, test sets, observability, guardrails and cost/latency budgets. Ownership. Owning features end to end, from problem framing with product to running them in production. Design Principles keep things simple before scalable prefer explicit logic over magic abstractions, and that includes AI: deterministic where you can, model where you must optimize for change, not perfection (models, prompts and providers will change) measure AI behaviour, don’t trust vibes avoid “framework-driven architecture” accept that some parts will be ugly, temporarily Tech Stack .NET · Vue.js · service-oriented architecture · relational + operational data storage · cloud-based infrastructure · LLM APIs and agent tooling (e.g. Semantic Kernel / Microsoft.Extensions.AI, MCP) · vector/semantic search · eval and tracing tools How We Build AI-native development is the default. You use coding agents (e.g. Claude Code, Copilot) every day. You own what you ship, whoever typed it: you review AI-generated code critically, test it and understand it. What We Expect Strong, senior-level .NET engineering Ability to navigate uncertainty and work in ambiguity Willingness to challenge decisions Focus on outcomes, not just code Understanding of trade-offs and complex systems, including when not to use AI Preferring ownership over comfort Strong Plus Having shipped LLM/AI features to production and kept them running Experience with evals, prompt/version management or AI observability Python for prototyping and data work Logistics or other real-time operations domain experience What You Won’t Find Here over-engineering everything upfront unnecessary microservices “clean architecture” for the sake of it process-heavy development AI demos that never reach production wrapping a chatbot around a problem and calling it solved

Location: Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. About the Role We are at an inflection point where AI is fundamentally reshaping what products can do and how users experience them. We're not just looking for a product manager — we're looking for a hybrid product builder who truly understands AI capabilities and can translate technical potential into real user value. You will lead end-to-end product design for LLM / Agent-powered applications — from zero to one — across domains including intelligent customer service, personalized recommendations, AI assistants, and automated workflows. You are the critical connector between user insights, AI technical capabilities, and business objectives: someone who can discuss RAG retrieval strategies and multi-agent orchestration with ML engineers, while clearly articulating product value and delivery roadmaps to business stakeholders. If you have genuine passion for AI-native products and the ability to define clear product direction amid ambiguity and rapid change, we'd love to build the next generation of AI applications together. Key Responsibilities End-to-End AI Product Lifecycle Management Own the full product lifecycle of AI applications — including intelligent chatbots, AI assistants, recommendation systems, and automated workflows — from requirements definition and product design through to launch and delivery. Produce high-quality PRDs, interaction flow diagrams, and acceptance criteria while driving cross-functional teams to execute efficiently. LLM / Agent Capability Productization Deeply engage in Agent product design, including task planning workflows, tool-calling strategies (Function Calling / MCP), context management mechanisms, multi-agent orchestration logic, and graceful failure/fallback handling. Translate underlying model capabilities into meaningful, perceivable user value. AI Evaluation Framework & Quality Standards Build Harness evaluation frameworks for AI products — designing test scenario sets, evaluation metric systems (accuracy, hallucination rate, task completion rate, etc.), and regression test case libraries. Independently assess AI capability boundaries and drive continuous model iteration and product quality improvement. Conversational Product Design & Knowledge Engineering Lead platform architecture planning for intelligent customer service and conversational assistant products, covering knowledge base structure design, dialogue flow and SOP design, corpus annotation and training strategy, intelligent reply generation, and case summarization. Leverage large-scale data analysis to continuously optimize conversation quality and issue resolution rates. Personalization Engines & Generative UI Products Collaborate deeply with ML and data teams to design recommendation strategies that deliver truly personalized, individualized user experiences. Define generative UI product requirements and drive growth in core business metrics including CTR, conversion rate, and user retention. Establish comprehensive attribution analysis frameworks for recommendation effectiveness. AI Capability Integration with Business Scenarios Develop a thorough understanding of business goals and user pain points. Proactively identify opportunities to apply AI technologies — including RAG, Prompt Engineering, and multimodal capabilities — to concrete use cases. Define clear product evolution roadmaps that balance technical feasibility, user experience, and commercial value. Cross-Functional Collaboration & AI-Native Product Culture Act as the product Owner in close collaboration with algorithm, engineering, data, design, operations, and business teams. Maintain a strong sense of ownership in a fast-moving AI-native environment, continuously track industry developments, and rapidly translate emerging AI capabilities into product innovation opportunities. Requirements Product Experience : 3+ years of product management experience, with at least 1 year of direct hands-on experience delivering AI application products, AIGC products, or Agent products. Must have fully shipped at least one AI-related feature module or standalone product. AI Technical Understanding : Deep understanding of the productization of mainstream AI technologies, including but not limited to: LLM Prompt Engineering, RAG (Retrieval-Augmented Generation) architecture, Agent fundamentals (tool calling / task planning / context window management), and conversational system design. Ability to independently evaluate the product feasibility of technical proposals. Evaluation & Data Capabilities : Proven ability to design AI product evaluation frameworks — independently defining evaluation metrics, building test case sets, and tracking product performance through data analysis. Familiarity with A/B experiment design and a strong data-driven decision-making mindset. Documentation & Communication Skills : Ability to write structured, logically rigorous PRDs, technical requirement documents, and flow diagrams. Excellent cross-functional communication skills with the ability to accurately bridge information between technical and business teams, eliminating information gaps. User Insight & Product Thinking : Sharp ability to translate ambiguous user needs into clearly defined product requirements. Skilled at finding the right product balance between AI capability boundaries and user expectations — avoiding both overpromising and underutilizing model capabilities. Learning Agility & Ownership Mindset : Sustained enthusiasm and capacity for continuous learning in a rapidly evolving AI landscape. Strong sense of ownership — able to proactively define problems, drive decisions, and take accountability for outcomes in highly ambiguous environments. Nice to Have Familiarity with cutting-edge AI engineering practices including MCP ( Model Context Protocol ), Function Calling, and multi-agent orchestration frameworks (e.g., LangChain / AutoGen / CrewAI), enabling deep technical dialogue with engineering teams. Experience with AI Harness / Eval / Benchmark platform product design or usage, with involvement in establishing and maintaining LLM evaluation systems. Background in Fintech / e-commerce / SaaS industries, with an understanding of the unique product design requirements for AI in high-concurrency, compliance-sensitive environments. Bilingual fluency in Chinese and English (spoken and written), with the ability to independently drive product collaboration and cross-cultural communication within international teams. Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

Задачи: — Проектировать и развивать LLM/AI-системы и AI-агентов; — Строить многошаговые agentic workflows: routing, tool calling, state management; — Работать с Prompt Engineering и Context Engineering; — Управлять контекстом, памятью и состоянием диалога; — Реализовывать structured output и function/tool calling; — Строить RAG-пайплайны: chunking, embeddings, retrieval, reranking; — Интегрировать LLM с API, базами данных и внутренними сервисами; — Разрабатывать backend-сервисы на Go и AI-компоненты на Python; — Исследовать новые модели и подходы, быстро проверять гипотезы; — Выбирать модели с учетом качества, latency и стоимости; — Строить систему оценки качества: evals, regression tests, golden datasets, LLM-as-a-judge; — Анализировать логи и traces, улучшать качество и стабильность агентов; — Реализовывать retries, fallbacks, timeouts и обработку ошибок; — Доводить решения от прототипа до стабильного production. Требования: Go: — production-сервисы; — REST/gRPC API; — concurrency; — работа с БД; — микросервисная архитектура. Python: — AI-сервисы и backend; — async; — API; — обработка данных; — быстрое прототипирование. Также важно: — Практический опыт разработки production-приложений с LLM; — Понимание архитектуры современных AI-систем: prompt → context → tools → agent → state → evaluation; — Опыт Prompt Engineering: system prompts, few-shot, prompt chaining, structured output; — Опыт Context Engineering: memory, summarization, динамическая сборка контекста; — Опыт создания AI-агентов и agentic workflows; — Работа с LLM API и понимание особенностей разных моделей; — Понимание RAG: embeddings, vector search, retrieval, reranking, hybrid search; — Понимание evals, regression testing и анализа production-логов; — Опыт с PostgreSQL, MongoDB, Redis, Docker, Git, CI/CD; — Понимание production-подходов: observability, scalability, latency, retries, fallbacks и контроль стоимости. Будет плюсом: — Multi-agent системы; — LangGraph; — MCP; — Langfuse / LangSmith; — Elasticsearch / OpenSearch; — Open-source LLM: Qwen, Llama, DeepSeek и др.; — vLLM / Ollama; — Kafka / RabbitMQ; — Kubernetes; — Оптимизация token usage, latency и стоимости LLM; — Guardrails и защита от prompt injection; — Highload-системы. Ищем инженера, который воспринимает LLM не как простой API, а как компонент большой production-системы. Важно уметь проектировать всю логику вокруг модели: какие данные передать в контекст, какого агента или инструмент вызвать, как проверить результат, обработать ошибку и определить следующий шаг. Ищем software engineer с сильной AI/LLM-экспертизой, который умеет не только написать хороший промпт, но и довести всю систему до стабильного production-решения.

Задачи: — Проектировать и развивать LLM/AI-системы и AI-агентов; — Строить многошаговые agentic workflows: routing, tool calling, state management; — Работать с Prompt Engineering и Context Engineering; — Управлять контекстом, памятью и состоянием диалога; — Реализовывать structured output и function/tool calling; — Строить RAG-пайплайны: chunking, embeddings, retrieval, reranking; — Интегрировать LLM с API, базами данных и внутренними сервисами; — Разрабатывать backend-сервисы на Go и AI-компоненты на Python; — Исследовать новые модели и подходы, быстро проверять гипотезы; — Выбирать модели с учетом качества, latency и стоимости; — Строить систему оценки качества: evals, regression tests, golden datasets, LLM-as-a-judge; — Анализировать логи и traces, улучшать качество и стабильность агентов; — Реализовывать retries, fallbacks, timeouts и обработку ошибок; — Доводить решения от прототипа до стабильного production. Требования: Go: — production-сервисы; — REST/gRPC API; — concurrency; — работа с БД; — микросервисная архитектура. Python: — AI-сервисы и backend; — async; — API; — обработка данных; — быстрое прототипирование. Также важно: — Практический опыт разработки production-приложений с LLM; — Понимание архитектуры современных AI-систем: prompt → context → tools → agent → state → evaluation; — Опыт Prompt Engineering: system prompts, few-shot, prompt chaining, structured output; — Опыт Context Engineering: memory, summarization, динамическая сборка контекста; — Опыт создания AI-агентов и agentic workflows; — Работа с LLM API и понимание особенностей разных моделей; — Понимание RAG: embeddings, vector search, retrieval, reranking, hybrid search; — Понимание evals, regression testing и анализа production-логов; — Опыт с PostgreSQL, MongoDB, Redis, Docker, Git, CI/CD; — Понимание production-подходов: observability, scalability, latency, retries, fallbacks и контроль стоимости.

Задачи: — Решать технические проблемы клиентов от начала до конца (Helpdesk + Slack) в рамках SLA — Проводить анализ корневых причин с использованием Grafana и Datadog (логи, метрики, трассировки) — Создавать дашборды мониторинга и проактивные оповещения — Писать скрипты на Python для автоматизации и массовых операций — Активно использовать AI-инструменты (Claude, Cursor, ChatGPT) для ускорения устранения проблем Требования: — Опыт ежедневной работы с LLM и prompt engineering — Практические навыки работы с Grafana и Datadog (создание дашбордов и оповещений) — Скриптинг на Python и хорошее понимание распределённых систем — Опыт 2+ года в TechOps/технической поддержке (приветствуется опыт в FinTech/Forex/Crypto) — Отличное владение английским языком (C1+) Условия: — Удалённая работа (предпочтительно в часовом поясе GMT+5 - GMT+8) — Командный язык — английский

Location: United States Workplace: Remote At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 We're looking for a Senior Technical Account Manager - Customer Success to act as a strategic partner and trusted advisor to our customers, blending strong relationship management with a deep understanding of ClickUp’s platform and capabilities. This role sits at the intersection of customer success, solution strategy, and technical enablement, supporting long-term growth, adoption, and measurable business outcomes.   Senior Technical Account Manager - Customer Success at ClickUp lead with a customer-first mindset, developing success plans, guiding onboarding and adoption, and ensuring stakeholders see continuous value throughout their lifecycle. While you’ll support technical initiatives like process optimization, workflow design, and AI enablement, you’ll also own the overall health, engagement, and strategic direction of your accounts. You’ll work cross-functionally with Sales, Product, and Support to align efforts and ensure each customer’s success story is long-term, scalable, and impactful.   Senior Technical Account Manager - Customer Success at ClickUp are responsible for delivering measurable value and driving meaningful business outcomes across their customer portfolio by focusing on: - Customer Enablement & Onboarding: Guiding new teams through implementation, onboarding, and training to ensure a smooth start and foundational success. - Account Health & Engagement: Proactively managing user adoption, stakeholder alignment, and account health to promote long-term success, retention, and growth opportunities. - Process Optimization & Solution Design: Collaborating with customers to identify critical business processes, map them to scalable solutions, and drive efficiency through ongoing refinement and performance insights. - Innovation Adoption & Workflow Automation: Empowering customers to leverage emerging features and technologies, including AI and automation, to enhance productivity, streamline operations, and deliver real-world impact. CORE RESPONSIBILITIES Senior Technical Account Manager - Customer Success at ClickUp act as the strategic and technical owner of the customer relationship, ensuring every customer achieves measurable success through ClickUp product and AI feature set.   - New Customer Onboarding - Lead or support the end-to-end onboarding and implementation of ClickUp, from discovery and solution design to training and go-live support. - Translate functional and technical requirements into scalable ClickUp solutions, including workflows, templates, hierarchies, and automations. - Guide customers through foundational setup, integration, and enablement, while promoting best-practices and system governance and change management. - Account Health Management - Monitor seat utilization, adoption trends, and Champion/Stakeholder engagement. - Build and execute adoption plans and account reviews to maintain or improve health. - Identify risks early and build recovery plans in partnership with the account team. - Deliver ongoing change management and enablement, ensuring customers continue to evolve and mature with the platform. - Workflow Mapping (IER Framework) - Conduct Intake → Execution → Reporting (IER) cycles for key workflows. - Lead discovery sessions to map current-state vs. future-state processes. - Recommend optimizations and create workflow templates to scale across teams. - AI Enablement & Agent Deployment - Drive adoption of ClickUp AI and build custom workflow Agents tied to customer use cases. - Partner with customers to define and deliver new AI automations that align with business KPIs. - Provide technical training and consultation on AI and automation best practices, including prompt design, agent architecture, and scaling use cases across teams. - Track and report AI usage and credit consumption against plan. - Customer Success & Expansion - Serve as the technical partner to assigned accounts, connecting adoption to business value. - Generate qualified leads through data-driven insights and AI usage analysis. - Drive cross-functional alignment to position renewals, expansions, and AI upsells. - Cross-Functional Collaboration - Act as the voice of the customer, translating business objectives and pain points into actionable insights for Product, Engineering, and Support. - Partner with account teams to maintain alignment between delivery and success.   CORE SKILLS & COMPETENCIES - Technical Acumen: Deep understanding of ClickUp platform capabilities, automation logic, integrations, and AI Agent functionality. Able to translate business needs into technical solutions. - AI Expertise: Familiar with generative AI concepts, prompt design, and automation frameworks. Skilled at identifying and scoping AI use cases and consumption plans. - Consultative Discovery: Exceptional at workflow analysis, process design, and identifying friction points. Uses structured discovery to map customer needs into ClickUp. - Project and Program Management: Ability to manage complex customer programs with multiple stakeholders, deadlines, and outcomes. Skilled at running structured account plans. - Data and Reporting: Comfortable using dashboards and metrics to communicate health, adoption, and ROI. Interprets usage data to drive recommendations. - Customer Engagement: Executive presence and strong communication skills. Builds trust at both ATL and BTL levels through credibility and clarity. - Account Ownership: Full accountability for assigned book of business: proactive, organized, and driven to achieve measurable outcomes. - Collaboration and Influence: Works cross-functionally with account team, Product, and Sales to align on outcomes. Influences without authority through insight and results. #LI-NMR #LI-Remote Equal Opportunity Employer ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. Privacy Notice ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice. https://clickup.com/careers-terms/candidate-privacy-notice If you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice https://t333.s.clickup-attachments-stg.com/t333/d9a53ce2-6d2c-48cd-84b1-ed4e525f9613/Philippine%20Data%20Privacy%20Notice_2024.pdf?view=open for further details. Visa Sponsorship Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions. Fraud Alert ClickUp Talent Acquisition will only initiate contact via an @clickup.com http://clickup.com email or through our official careers portal on clickup.com http://clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to support@clickup.com. AI Processing Notice ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates' employment applications against role-related criteria. These tools support, but do not replace, human decision‑making. If you have questions or need an accommodation in the recruitment process, please contact us at AskPeople@ClickUp.com.

Location: Bengaluru, India We are looking for a Senior AI Quality Engineer (L3+) with strong Python skills and hands-on experience testing AI and ML systems. You will analyze requirements, define evaluation strategies, build automated checks, validate models and outputs, test APIs and data pipelines, verify defects through resolution, and contribute to release readiness for your assigned product area. You will both evaluate AI systems and design, build, and operate QE agents for the software testing life cycle. AI-assisted work is part of everyday QE practice on this engagement, with Ragas, DeepEval, promptfoo, Cursor, and other AI and ML tools used for evaluation, scripting, test generation, analysis, and maintenance. You will also build golden datasets, calibrate LLM-as-judge methods, test agentic workflows and RAG systems, implement self-healing and intelligent test approaches, and diagnose quality, safety, performance, and cost failures across distributed AI services. This position is intended for Hyderabad-based candidates who are available to work from the office. The client delivers AI agents, retrieval systems, models, and data pipelines across a broad technology landscape. Quality is part of delivery through evaluation gates, automated regression, model and data validation, security and privacy checks, and evidence that a release is ready. Python is the primary language for AI evaluation, model validation, API testing, data-pipeline quality, and QE agent design. The role combines deterministic automation with probabilistic evaluation to assess AI behavior across models, data, retrieval, tools, and integration surfaces, and designs and operates agents that support the software testing life cycle. Analyze requirements and define evaluation strategies, golden datasets, regression benchmarks, baselines, thresholds, and blocking metrics with domain-expert review. Design, build, and orchestrate AI agents, persona-based workflows, and reusable skills for the STLC using LangChain, LangGraph, or Semantic Kernel. Build automated evaluations and benchmarks for LLMs, agents, RAG, retrieval, tool trajectories, and contracts using Ragas, DeepEval, and promptfoo. Calibrate LLM-as-judge against human grading, manage non-determinism through repeated runs, and detect regression and drift. Write and maintain Python and pytest automation for AI, ML, API, data, and integration workflows. Use Cursor and agentic tools to analyze requirements, generate and review tests, and maintain evaluation suites. Validate deep-learning, reinforcement-learning, and predictive models using LangChain. Build AI-assisted STLC workflows for requirements analysis, test design, script generation, execution, self-healing, failure analysis, and defect triage, plus intelligent test selection and defect prediction. Integrate LLMs, APIs, embeddings, vector databases, retrieval pipelines, and enterprise data sources into QE frameworks using Python. Test REST and streaming APIs, agent tools, and RAG and MCP integrations, including authentication, errors, retries, and recovery. Test data and retrieval pipelines for schema integrity, lineage, idempotency, fallback, promotion gates, and rollback. Integrate evaluations, benchmarks, and agent workflows into QE frameworks and CI/CD on GitHub Actions, review Allure results, and keep TestRail aligned with automated coverage. Test prompt injection, jailbreaks, unsafe tool use, data exfiltration, access control, PII controls, and guardrails. Measure accuracy, relevance, groundedness, hallucination, retrieval quality, agent reliability, latency, throughput, token use, and cost, and diagnose distributed failures. Implement tracing, monitoring, and production evaluation using Langfuse, LangSmith, or a comparable AI observability platform. Deploy and operate QE agents on Amazon Bedrock AgentCore or a comparable agent platform, with governance and human oversight. Deploy and validate AI and ML solutions on AWS or Azure, including secrets, database services, and cloud-native test infrastructure. Report, track, and verify defects in Jira, and work with domain experts, product, and engineering on traceable coverage and untested scope. Contribute to release readiness for the assigned product area without owning sign-off for the whole team. Strong Python proficiency with pytest for test and evaluation automation. Hands-on experience building and orchestrating AI agents and agentic workflows with LangChain, LangGraph, Semantic Kernel, or comparable frameworks. Hands-on experience building AI evaluations and benchmarks with Ragas, DeepEval, promptfoo, or equivalent tools. Hands-on use of Cursor or agentic development tools for test generation and maintenance. Experience defining AI evaluation strategies, golden datasets, regression benchmarks, and LLM-as-judge calibration, including non-determinism and drift. Experience validating deep-learning, reinforcement-learning, and predictive models with LangChain. Experience building AI-assisted STLC workflows for requirements analysis, test design, script generation, execution, self-healing, failure analysis, defect triage, intelligent test selection, and defect prediction. Experience integrating LLMs, APIs, embeddings, vector databases, and retrieval pipelines with automation frameworks in Python. Experience testing REST and streaming APIs, agent tools, RAG workflows, and MCP integrations. Experience testing data and retrieval pipelines for correctness, lineage, and safe promotion. Experience integrating AI evaluation and agent workflows with automation frameworks and CI/CD using GitHub Actions, Allure, TestRail, or equivalent tools. Experience testing AI security, privacy, access control, and guardrails. Experience measuring accuracy, relevance, groundedness, hallucination, retrieval quality, agent reliability, latency, throughput, token use, and cost, and diagnosing distributed failures. Experience with AI tracing, monitoring, and production evaluation using Langfuse, LangSmith, or comparable tools. Familiarity with AWS, Azure, or GCP cloud AI services and agent platforms for deploying and validating AI and ML solutions. Experience deploying and operating agents on Amazon Bedrock AgentCore or a comparable agent platform, with governance and human oversight. Experience managing defects through resolution in Jira or an equivalent tool. Ability to work with domain experts, product, and engineering on ground truth and coverage gaps. Experience contributing to release readiness for an assigned product area. Playwright and TypeScript experience for UI and API automation. Real-device and cross-browser execution using LambdaTest, Sauce Labs, or an equivalent platform. Knowledge of AI-driven test optimization and coverage analytics using SeaLights or an equivalent platform. Experience contributing reusable components to shared automation frameworks and reviewing automation code through Git and GitHub workflows. Experience managing test data and troubleshooting test environments needed for reliable execution. Experience triaging security findings and validating operational readiness, monitoring, rollback, and recovery controls. Experience producing audit-ready evaluation reports and improving shared evaluation patterns, automation libraries, and datasets.

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Ads powers Reddit’s mission to bring community, belonging, and empowerment to everyone in the world. The Advertiser Platform organization owns ads.reddit.com, Reddit’s core advertiser-facing product. We’re looking for a mid-level frontend engineer to join our Ads Manager team. Our team includes frontend and backend engineers who build tools that help advertisers create and manage campaigns at scale. We make complex advertising workflows easier to use, with a focus on performance and reliability. In this role, you’ll own medium-sized frontend projects. You’ll help clarify requirements, propose technical solutions, and carry your work through implementation and release. You’ll make progress independently, collaborate with teammates on tradeoffs, and ask for input when you need it. Responsibilities Build intuitive, accessible interfaces that help advertisers create and manage campaigns. Partner with product managers, designers, and backend engineers to turn advertiser needs into scoped projects. Own technical design, implementation, testing, and release for medium-sized frontend projects. Communicate progress, dependencies, and risks early so partners can plan around them. Review code and document technical decisions to help the team maintain and extend its work. Improve frontend performance and reliability, address bugs, and contribute reusable components and patterns. Requirements 3+ years of software engineering experience, including 2+ years in frontend engineering. Experience building and maintaining production web applications. Ability to break down a project, evaluate technical tradeoffs, and deliver a solution independently. Clear communication and a collaborative approach to problem-solving. Experience writing maintainable code, testing your work, and participating in code reviews. Preferred qualifications Experience building advertising products, creative tools, or design systems. Experience partnering directly with product managers and designers. Benefits: Comprehensive Healthcare Benefits and Income Replacement Programs 401k Match Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Reddit Global Days Off Generous paid Parental Leave Paid Volunteer time off #li-remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $164,200 — $229,900 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: Colombia, Huila, Colombia; São Paulo, Brazil About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Engineering Manager, (Technical Team Lead) Location: Remote, Brazil, Colombia, Argentina Status: Full-time Role Overview As a Engineering Manager (Technical Team Lead) at Turing, you will be a pivotal part of our engineering leadership for AI initiatives. This is not a pure people management role. You will be expected to be hands on: able to operate on the data, organize the stack, set up infrastructure, and personally deliver a project if no one else is available. You will lead a team through a rapid iteration, startup paced environment with high expectations and short timelines, while also driving the technical vision and execution of complex projects. The ideal candidate is someone who takes ownership beyond what their role technically requires, has a track record of delivering under pressure, and is excited by the intensity of a startup environment rather than looking for a more comfortable, longer timescale management track. Key Responsibilities Hands On Technical Ownership: Operate directly on data, organize the technical stack, and set up infrastructure as needed. Be the technical fallback who can personally deliver a project if no one else is online to do it. Guide the team in architecture, design, and implementation of scalable, maintainable codebases. Build and use AI agents, and review the team's agent based work, since this role requires evaluating agent output directly rather than only reviewing human written code. Prompt Generation and Innovation: Lead innovation efforts in product features and processes. Manage idea and prompt collection and prioritization. Drive experimentation and iteration for optimal outcomes. Work Stream Assignment Across Pods: Allocate projects based on skills and performance. Prioritize tasks to meet business goals. Coordinate with cross functional teams for project alignment. Team Throughput and Task Completion: Monitor progress using metrics like velocity and cycle time. Optimize development processes for efficiency. Ensure tasks meet quality standards before deployment. Spot Reviews on Tasks: Perform quality control through task reviews. Provide actionable feedback to maintain high standards. Identify risks early and adjust processes accordingly. Identifying High and Low Performers: Conduct performance analysis through reviews and metrics. Provide mentorship, feedback, and talent management. Identify high performers for advanced roles and support development for others. People and Project Leadership Under Pressure: Lead teams through urgent, high pressure delivery schedules, not just steady state work. Push delivery timelines in a rapid iteration startup context while maintaining quality. Take direct ownership of outcomes, including being responsive when urgent needs arise. Technical Skills Expert level, hands on experience in Node.js, with React and NestJS specifically, including a deep understanding of their ecosystems, libraries, and best practices. Experience with Infrastructure as Code (IaC) and GCP, including setting up and operating cloud infrastructure directly. Ability to build and use AI agents, with enough fluency to review and evaluate a team's agent built work. Experience leading projects that leverage Python for data analysis, backend development, or AI and ML applications, as well as JavaScript and TypeScript for front end and full stack development. Proficiency in data analysis techniques, including statistical analysis, data visualization, and data manipulation using tools like Pandas, NumPy, and SQL. Strong focus on data quality, including data validation, cleansing, and enrichment. Qualifications Bachelor's or Master's degree in Computer Science, AI, Data Science, Data Engineering, or a related field. Electrical engineering backgrounds are acceptable. AI or data science background is a meaningful plus (helps significantly) but not a dealbreaker if diligence and ownership are evident elsewhere. 5+ years of experience in software development. At least 2 years in a leadership role is the bar for an Engineering Manager managing teams of 3 to 6. For this Senior Engineering Manager (Technical Team Lead) role, candidates should have experience managing meaningfully larger teams than that, not just the 5 to 6 person threshold. Proven track record of leading teams through urgent, complicated technical work, ideally in a startup setting, and delivering on time or ahead of time. Demonstrated ownership that exceeds role expectations: a history of taking on more than the job required, high personal output, and strong initiative. Strong problem solving skills, with a focus on delivering results in a fast paced, dynamic environment. Excellent communication and interpersonal skills, with the ability to collaborate effectively across cross functional teams. What Success Looks Like You are the kind of leader who is excited to do this work. You know it will be intense, that you'll manage a lot of people, process, and technology at once, and you welcome it. You have taken on something genuinely hard, led people through it, and can clearly explain what made it difficult and how you delivered — a truly hard technical milestone, reached in a leadership setting, that you're proud of. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: London, England, United Kingdom About Smartcat Smartcat is building the future of work, where human expertise meets digital teammates to drive 10x to 1000x productivity gains for the world’s leading enterprises. We’re on the frontier of an entirely new category: Agentic AI. We enable enterprises to build high-performing hybrid workforces made up of both humans and AI agents. These AI agents aren’t generic copilots. They’re fully trained digital teammates that learn from your best people, your content, and your business strategy—ready to get to work from day one. Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. Whether you're launching a product globally, onboarding new hires, translating learning content, or aligning legal teams across regions, Smartcat turns knowledge into action and action into scale. Over 1,000 companies, including 20% of the Fortune 500, rely on Smartcat to bring their business to the world—instantly, accurately, and in every language. As a Series C company with consistently high year-over-year growth, we’re scaling fast and investing in people who want to shape the future of work with us. Join us in unlocking global potential, one human and agent team at a time. THE ROLE You’ll build and deploy customer translation and localization workflows, lead technical discovery and demos, guide onboarding, and support renewals by demonstrating value and resolving technical blockers. This is a hands-on engineering role with substantial customer-facing responsibility. You’ll focus on enterprise workflows in learning and development (L&D), websites, and marketing. WHAT YOU’LL DO Scope customer needs into technical plans with clear dependencies, acceptance criteria, and measurable outcomes. Build AI workflows using prompts, glossaries, translation memories, and human review to meet customer terminology, brand, and quality requirements. Write and deploy integrations with CMS, DAM, PIM, LMS, and commerce systems, preserving content structure, metadata, and context. Own production readiness: secure data access, testing, error handling, monitoring, quality evaluation, and review routing. Document the solution and agree ongoing ownership. Support customer enablement and adoption with Account teams, measure results against the baseline, and identify valuable follow-on workflows. Turn customer work into reusable connectors, evaluation suites, and deployment patterns, and inform Product and Engineering priorities. EXAMPLE PROJECTS L&D workflows: automate localization of courses, training materials, and learning content, from source files through review and delivery into the customer’s LMS. Website workflows: connect the CMS to translation, review, and publishing so new and updated pages stay current across languages. Marketing workflows: localize campaign assets, emails, and product content, applying brand voice and terminology with market-specific review and approval. Across these workflows, build quality checks and human review routing that meet customer requirements. WHAT YOU BRING A record of shipping software, integrations, or automation for enterprise customers; demonstrated ability matters more than a specific degree or years of experience. Hands-on coding skills across APIs, authentication, webhooks, data transformation, version control, testing, and debugging. Experience building AI workflows and evaluating quality, reliability, latency, and cost, including failure handling and human review. Clear communication with technical and business stakeholders, and the judgment to scope ambiguous requests, explain tradeoffs, and manage expectations. Ownership through deployment, documentation, customer enablement, and adoption. Practical use of AI in your own engineering work. Localization or translation technology experience is valuable; curiosity about the domain is essential. Willingness to travel up to 40% Why joining Smartcat might be your best move so far A global, connected team We’re a team of 200+ people across 30+ countries, working together through a hub-and-spoke model anchored in eight key locations: New York, London, Lisbon, Costa Rica, Serbia, Armenia, Georgia, and Spain.  Most of our roles are remote-friendly, giving you the flexibility to do your best work from where you thrive. For customer-facing teams, we prioritize proximity to our customers, ensuring we stay deeply connected to their needs and deliver an exceptional experience.  No matter where you’re based, you’ll be part of a highly collaborative, globally-distributed team that values ownership, speed, and meaningful impact. Be part of an AI Native Organization We are highly innovative, using AI across all areas of the organization to accelerate decision-making and free people to focus on strategy and high-impact work. We embrace new ideas and encourage all Smartcaters, regardless of level or department, to manage their own AI Agents. At Smartcat you’ll shape how AI transforms the workplace and play an integral role in ensuring Smartcat remains a leader in AI innovation. Innovating a $100 Billion industry Smartcat is reshaping the $100B multilingual content industry with an AI-powered platform that makes it easy for companies to create, translate, and localize global content at scale. Our platform enables enterprise teams to move away from slow,  traditional outsourcing methods, and achieve fast, high-quality results, at a fraction of the cost. Join the rocketship to scale-up 10x and beyond together We are looking for someone to become an integral part of our team and play a crucial role in the most exciting part of our journey: transitioning from a post-Series C startup to a company exceeding $100M in ARR and $1B in valuation. Our journey isn’t for the faint of heart. We are growing at 130% YoY, thanks to our strong product-market fit and high-performing team, and plan to accelerate from here. Smartcat Culture Code : Where Diversity Meets High Performance At Smartcat, we are committed to building a culture that highlights respect and appreciation for each individual's unique background and perspective, while maintaining a strong focus on results and engagement. We believe in welcoming everyone and fostering an inclusive environment where team members can be their authentic selves at work. Our commitment to inclusion is steadfast, and we stand firmly against discrimination and harassment.

Location: London, United Kingdom Workplace: hybrid About us At Xelix, we work with some of the world’s largest companies to automate and strengthen their financial controls. Our AI solutions redefine how Accounts Payable teams operate – moving from manual processes to automated, intelligent workflows. Xelix is a fast-paced scale-up – things move fast and expectations are high. We raised our Series B with Insight Partners in June 2025 and are expanding aggressively. We have a team 150 talented people pulling together to achieve our goals. Everyone is trusted to take ownership, move fast and have a meaningful impact. We prioritise personal and professional growth, keep things fun, and love to celebrate a milestone together. In this role you’ll grow, be challenged and help shape the future of Xelix. If you’re excited about building something special with us, we’d love to hear from you. About the role We are hiring an AI Engineer to join our growing AI Engineering team. You’ll design and build production AI systems — combining machine learning, large language models, and strong engineering — to solve real problems across documents, email, and financial data. We focus on building systems that work reliably in production, not just prototypes. We use modern AI tools extensively in our workflow, enabling engineers to operate at a higher level — focusing on system design, product thinking, and solving complex problems. What you'll be doing AI Systems & Agents: design and build production AI systems — including agent-based workflows, tool use, and multi-step reasoning. Model Development & Adaptation: develop and improve models across text, vision, and structured data, including fine-tuning and hybrid ML + LLM approaches. LLM Platform Work: work with hosted and self-hosted models, contributing to decisions around model selection, performance, and cost. Production Engineering: write clean, maintainable Python and contribute to scalable, observable systems. Evaluation & Iteration: design evals, measure performance rigorously, and improve systems using real-world feedback. AI-Assisted Development: use modern AI coding tools to move faster while maintaining high standards. Collaboration: work closely with product and engineering teams to deliver high-impact features. What you’ll bring Experience: 2–5 years building and shipping ML or AI-powered systems into production. Strong Engineering Skills: clean, testable Python; solid software design; experience working in production environments. AI/ML Breadth: experience with either traditional ML (e.g. gradient boosting) and/or LLM systems (prompting, tool use, evals, agents). Systems Thinking: ability to reason about trade-offs (accuracy, latency, cost, reliability) and design accordingly. Data Skills: SQL, pandas, and experience working with messy real-world data. AI-Native Workflow: comfortable using AI-assisted coding tools effectively. Curiosity & Ownership: proactive in exploring new approaches and improving existing systems. Collaboration: strong cross-functional working style. What we offer in return 💰 Competitive salary of £65,000 to £75,000 depending on experience 🏝️ 27 days of annual leave (including 3 days Christmas closing) which increases up to 3 days based on tenure, with the option to roll over, buy or sell up to 3 days 🏡 Hybrid working with two days a week from our dog-friendly Hoxton office 💪 On-site gym and cycle to work scheme 🛍️ Employee discount at over 100 retailers 🏥 Comprehensive private medical & dental cover with Vitality 🍼 Enhanced parental leave pay 📚 Learning & development culture – £1,000 personal annual budget 🌍 We’re carbon-neutral and are working towards ambitious carbon reduction goals 🎯 Lots of team socials & activities ☀️ Annual team retreat Want to learn more? About us Xelix blog Xelix news Xelix glassdoor We believe that people from diverse backgrounds, with different identities and experiences make our company and product better. No matter your background, we'd love to hear from you! And if you have a disability, please let us know if there's any way we can make the interview process better for you - we're happy to accommodate! If you're a recruiting agency - we have an existing list of agencies we work with if required and we are not currently planning on expanding the list. Neither the Talent team nor hiring managers or the Support team will respond to cold outreach. This is a full-time position, with standard working hours from 9:00 AM to 6:00 PM, Monday through Friday. Interview Process While the exact process may vary slightly depending on the role, our typical interview stages are: Introductory Call – A short Teams conversation with a Talent Partner to discuss your background and the opportunity. Hiring Manager Interview – A 30–45 minute Teams meeting to explore your experience and fit for the team. Technical Task or Presentation – A role-relevant exercise to demonstrate your skills and approach. Final On-site Interview – An in-person meeting with our senior leadership team and co-founders at our office. We strive to make the process clear, efficient, and respectful of your time. We welcome the responsible use of AI for research and interview preparation, but ask that it isn't used to generate answers during live interviews. We also believe in being transparent - we use Metaview's AI note-taker during interviews so our interviewers can stay fully present. If you'd prefer us not to use it, just let your interviewer know. While you may need to answer eligibility questions as part of your application, we do not use AI to review or make decisions on applications - every application is reviewed fairly by a member of our Talent team.

Location: Russia; Moscow; Perm Workplace: remote About Xsolla Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. About the Role We are hiring a Staff Software Engineer to own the smart wallet and account abstraction layer of XsollaZK, Xsolla's Web3 platform on a zkSync-based L2. This is an individual contributor role with a large technical scope. You are the technical anchor for how millions of players get an on-chain account they never have to think about. The product. Every player who signs in with Xsolla ID receives a deterministic, non-custodial smart account. The account is derived from their identity claim, is identical on every device, and its private keys never leave the client. It is not a separate wallet screen: it is the player's inventory. It backs: minting and gifting; trading on our Bazaar marketplace; Merkle-based reward airdrops; gas sponsorship; an in-app dApp browser that exposes the same signer to third-party applications through an EIP-1193 provider. Responsibilities The technical strategy and architecture of the smart wallet platform: account model, signing, session management and gas abstraction at scale The smart account and permissioning model, evolved to meet both product and compliance needs The security model where our signer meets third-party applications: what a player is actually approving, and proof that the UI shows it The custody and recovery roadmap, from today's interim mechanisms (including raw key export) to MPC -based custody Cross-team technical decisions on account architecture, SDK contracts, data modeling and platform reliability, with buy-in from the wallet, marketplace, SDK, mobile and security teams Engineering standards in the Web3 domain Production escalations in the wallet and account abstraction domain WHAT YOU WILL DO Design and evolve the ERC -4337 user operation lifecycle (prepare → sign → submit → confirm), EIP -7702 delegation, deterministic address derivation from identity, and the session-key and permission primitives (including origin-bound Smart Sessions) that let players act without a prompt on every transaction Set the paymaster and gas-sponsorship strategy: what we sponsor, how we meter and cap it, how we defend it from abuse, and how it degrades when sponsorship is unavailable Define EIP -1193 / EIP -6963 provider behavior, origin-bound and policy-versioned sessions, trust tiers, and the transaction and signature confirmation flow Design recovery paths (passkeys, guardians, social recovery) that a non-crypto-native player can complete without losing assets Identify systemic risks (key management, signature phishing, reorgs and indexer staleness, bundler and RPC dependencies, contract upgrade paths) and lead initiatives that resolve them before they become incidents Write RFCs and design docs; review critical code, contracts and designs Work with product, security, legal and infra teams to align on the roadmap and turn business and regulatory needs into well-scoped technical plans Create leverage for the engineering org through documentation, tooling and mentorship Serve as the escalation point for complex production issues: a stuck user operation, a drained paymaster, a signing prompt a player didn't understand Set up and maintain AI tooling in the repositories (Claude Code, Codex, Cursor: rules, context, harness) so the team uses it effectively REQUIRED Experience 8+ years of engineering in the Ethereum ecosystem working with crypto wallets and smart wallets Designing or operating a production smart wallet or account abstraction system serving real users and real value Shipping and operating systems where a bug meant lost funds. You can talk concretely about the guardrails, reviews and rollback paths you put in place Account abstraction and smart wallets ERC -4337 in depth: EntryPoint (v0.6 through v0.8), the UserOperation lifecycle, bundler and paymaster roles, validation rules ( ERC -7562), gas estimation and its failure modes, counterfactual deployment, signature validation for undeployed accounts ( ERC -6492) EIP -7702 and the post-Pectra landscape: EOA delegation, its interaction with EntryPoint v0.8, and the risks it introduces (residual key authority, delegation phishing, storage collisions) Building on or extending production smart account implementations; modular account standards ( ERC -7579 / ERC -6900) Session keys and delegated permissions: scoped, time-limited, policy-bound authority; TTLs and contract allowlists, origin binding, permission revocation; ERC -7710 / ERC -7715 Signature schemes and wallet interfaces: EIP -712 typed data, ERC -1271 contract signatures, WebAuthn / passkey (P-256) signers; EIP -1193, EIP -6963, EIP -5792 batched calls, ERC -7677 paymaster interfaces Smart contracts and EVM Solidity and the EVM : reading, reviewing and writing account, paymaster and module contracts; gas-aware design; upgradeability and migration patterns; working effectively with external auditors L2 specifics and their effect on wallet design: native account abstraction on zkSync-family chains, transaction and fee models, finality and reorg behavior, RPC and indexer semantics Backend Go: idiomatic code, concurrency patterns, performance profiling TypeScript and SDK design: client-side SDK surfaces that internal and external teams build on Distributed systems and their trade-offs (consistency, availability, failure modes); reconciling off-chain state against an authoritative on-chain result Data and infrastructure PostgreSQL: schema design, query optimization, migrations at scale Kubernetes: deploying, operating and debugging services Asynchronous messaging and event-driven design (Kafka or NATS ): consumer groups, at-least-once delivery Git, CI/CD Security Key management in production: platform secure storage (Keychain / Keystore), HSMs, MPC or threshold signing, and the operational discipline around each Wallet threat modeling: signature and delegation phishing, malicious dApp origins, replay and cross-chain replay, token approval abuse, paymaster griefing and DoS Leadership Leading multi-quarter technical initiatives across teams Influencing architecture and standards beyond your immediate team RFCs and design docs that stand on their own and are actionable without you in the room AI-assisted engineering Daily hands-on use of AI coding tools (Claude Code, Codex, Cursor) for development and review, including configuring them for a repository English English at C1 level Nice to Have Hands-on experience with ZK Stack and zk -rollups Hands-on experience with embedded and ecosystem wallet and AA infrastructure technologies (thirdweb, Privy, Dynamic, Turnkey, Pimlico, Alchemy, Biconomy, ZeroDev, Safe{Core}), with clear views on build versus buy MPC / threshold custody, social recovery or guardian-based recovery in a consumer product NFT and token infrastructure at scale: ERC -721 / ERC -1155 / ERC -20 mechanics, marketplace contracts, Merkle-based airdrop and claim distribution, chain indexing services Contributions to open-source wallet, security or identity projects, including authoring or reviewing ERC / EIP standards Compliance requirements for crypto consumer products: KYC / AML , geofencing, MiCA , SOC 2, ISO 27001, GDPR data minimization, audit logging Identity and auth integration for wallet derivation: OAuth 2.0 / OIDC , JWT verification, token scoping Platform or infrastructure engineering: building systems other engineers build on Owning a mobile wallet surface: React Native / Expo, WebView provider injection, native signing UI Gaming industry experience: platforms for game developers, publishers or players How We Work Decisions in writing. Significant technical decisions are written up as an RFC or ADR that lays out the options and trade-offs. We work across time zones, so a design has to stand on its own. AI is part of everyday engineering. We use AI coding tools for development and review, and we treat configuring them for a codebase as real engineering work. HOW WE HIRE Intro call. Your background, your motivation and the role. Technical interview. Built directly on the What you will own and Required sections above. We won't ask about anything this posting doesn't promise. System design. You design part of a wallet or account abstraction platform end to end and walk us through the trade-offs. Bar raiser. An engineer from outside the hiring team checks that you raise the overall engineering bar. Benefits We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we're not just building a business; we're cultivating a community that values creativity, collaboration, and the transformative power of play. EMPLOYMENT DETAILS Location: Remote  Employment Type: Full-time Schedule: 10:00–19:00 (flexible)

Location: Warsaw, Mazowieckie, Poland; Sofia City, Bulgaria; Limassol, Cyprus Workplace: hybrid Capital.com's Product Security team protects our web and mobile applications, infrastructure, and external perimeter in a highly regulated environment. As Senior/Staff Application Security Engineer, you will raise the bar for application security across the organisation. This role is measured by leverage: how well you design, automate, and scale security processes so that many engineering teams can build securely by default. You will lead security architecture reviews and threat modelling, increasingly with the help of AI tooling, and turn one-off security work into repeatable, self-service capabilities. The role combines deep hands-on offensive and defensive security expertise with the engineering mindset needed to automate at scale. You will work closely with development, QA, DevOps, and platform teams. Responsibilities: Security Architecture & Threat Modelling: Lead security architecture reviews and threat modelling for new and existing systems, using AI tools to make reviews faster, more consistent, and scalable across teams Act as a security force multiplier by influencing the standards, patterns, and guardrails that let teams move fast and stay secure Security Automation & Tooling: Design, build, and automate scalable security processes that engineering teams can self-serve, covering secure design review, threat modelling, testing, and remediation workflows Integrate and automate security checks across the SDLC and CI/CD pipelines (SAST, DAST, SCA, secrets, and IaC scanning), tuned for strong signal and low friction Own and evolve security tooling such as DefectDojo and SAST, DAST, and SCA platforms, maximising automation, coverage, and integration Apply AI and LLM-based tooling to architecture review, threat modelling, code review, and vulnerability triage, and help define how the team adopts these tools safely Security Testing & Vulnerability Management: Conduct and oversee security assessments of web and mobile applications, APIs, and cloud infrastructure, including manual testing and PoC development Run vulnerability scans across internal infrastructure and the external perimeter, then analyse findings, define remediation, and track issues to closure Support and triage the Bug Bounty Program and external vulnerability reports, automating triage where possible Participate in and help lead red teaming and offensive security exercises Enablement: Drive knowledge sharing on secure development, mentor engineers, and deliver training for development and QA teams Requirements: Experience: 5+ years in application or product security, or equivalent depth, with a track record of senior or staff-level impact Demonstrable experience leading security architecture reviews and threat modelling (e.g. STRIDE, attack trees, data-flow analysis) across multiple teams or products Proven ability to automate and scale security processes by building tooling, integrations, and self-service workflows that reduce manual effort Technical: Strong hands-on security testing skills, including code review and web, mobile, and API application security assessments, as well as the ability to triage and validate external vulnerability reports and bug bounty submissions Strong software engineering ability in at least one language (e.g. Python, Go, JavaScript), with the ability to build automation, not just scripts Deep understanding of the OWASP Top Ten, secure design, and secure coding best practices Experience with SAST, DAST, SCA, and vulnerability management platforms, and integrating them into CI/CD Strong understanding of modern application architectures: REST APIs, microservices, cloud-based systems, and containers Practical experience applying AI and LLM tooling to security work, or clear enthusiasm and aptitude to do so Collaboration: Excellent communication and influencing skills: you can explain security concepts to technical and non-technical stakeholders and drive change without direct authority A self-starter who enjoys solving complex problems, building leverage through automation, mentoring others, and strengthening security culture Nice to have: Experience securing the AI harness: hardening LLM and agent pipelines, prompts, tool and MCP integrations, and model endpoints against prompt injection, data leakage, and insecure agent actions Experience securing Kubernetes, including cluster hardening, RBAC, network policies, admission control, workload isolation, and image and supply-chain security Experience securing AWS infrastructure, including IAM, network and account architecture, key and secret management, and CSPM Experience building AI-assisted security tooling or internal self-service security platforms Experience mentoring or technically leading a security team Offensive or advanced security certifications such as OSAI, OSEP, OSCP, or OSWE What you'll get in return: You will join the company, that cares about work and life balance Annual Bonus based on the performance review cycle Generous Annual Leave Policy Medical Insurance and Pension fund, with additional benefit packages based on the location Hybrid working model (3 days from our modern office and 2 days fully remotely) Comprehensive Workation Policy with 30 more remote days available. Possibility of taking two additional days of paid leave per year to dedicate to volunteering efforts.

Мы в AnySense создаем AI-систему для автоматизацию административных процессов в американском healthcare секторе (с фокусом на автоматизацию работы страховых на US рынке). Задачи: — Разработка и оптимизация Python-бэкенда — Архитектура микросервисов и API (LLM, OCR/CV, клиент и админки) — Создание пайплайнов для LLM-агентов — Интеграция и поддержка OCR и CV-модулей — Тюнинг LLM, работа с датасетами и метриками в проде — Автоматизация процессов через RPA — Поддержка CI/CD и DevOps-процессов Требования: — Понимание архитектуры, системного дизайна и API — Уверенный опыт с Python (4+ лет) — Опыт с LLM-агентами, OCR/CV или похожими AI-модулями — Prompt engineering, тюнинг LLM и датасеты — Понимание / применение RPA — Опыт с CI/CD, Docker, продакшен-развёрткой Бонус: опыт в healthcare и AI-комплаенсе Условия: — USD 6000-10000 / мес — Remote (timezone +-2-3 часа от CET) — Офлайн-встречи несколько раз в год (EU, другие локации) — Работа в core team c founder’ом и СTO.

Location: Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Paphos, Cyprus; Remote, Germany; Warsaw, Poland Founding Tech Lead (GrowthBricks) Are you a hands-on engineer who loves zero-to-one challenges? Do you want to build systems with real context and memory that do more than reason, use tools, and drive actual business outcomes? About JetBrains We create intelligent software development tools for developers and teams. More than 15 million users, over 300,000 companies, and 88 of the Fortune Global Top 100 rely on our products to solve real, complex problems. Our mission is simple: make development teams more productive and AI adoptable at scale. GrowthBricks is a new project at JetMinds, backed by JetBrains, designed to give GTM teams and AI agents a shared business brain. Business context usually gets fragmented across CRMs, documents, dashboards, and people's heads. GrowthBricks brings that context together so agents and people can make decisions and execute effectively across the sales, marketing, and product stack. About GrowthBricks GrowthBricks is a shared business brain for GTM teams and AI agents. It brings together the context that usually lives across CRM, docs, dashboards, tools, and people’s heads: who we sell to, why customers buy, what matters now, what we tried, and what worked. Agents and people use that context to decide what to do next and execute across the GTM stack. GrowthBricks is a new project at JetMinds, backed by JetBrains. About the role We’re looking for a hands-on Founding Tech Lead to build GrowthBricks from zero. You’ll work directly with the product founder and own the technical side of the product: architecture, core systems, integrations, and the agent layer. The core challenge is turning fragmented, changing business context into reliable memory and agent actions across tools and measuring whether those actions actually drive business outcomes. You’ll write a lot of the early code yourself, make the key technical decisions, and shape the product as we learn what works. What you’ll work on Design the core architecture: business context, agents, tools, integrations, and feedback loops. Build agentic workflows that can reason over company context and act across CRM, sales, marketing, and product systems. Build context extractors from GTM team artifacts like sales calls, emails, internal documents, CRM state, marketing campaigns, etc. Work on prompting, context management, memory, tool use, and orchestration. Connect GrowthBricks to the existing GTM stack rather than rebuilding everything around it. Decide where to use MCP, APIs, frameworks, or third-party tools and where a custom solution is worth it. Prototype fast, discard weak ideas, and turn the useful ones into product primitives. We expect that you Are a strong hands-on engineer who enjoys zero-to-one work. Have built with LLMs, agents, or agentic workflows used by real people, and improved them based on failures, evaluations, and user feedback. Understand how context, prompting, tools, and agent behavior fit together. Can design backend systems, APIs, data models, and integrations. Are comfortable making decisions before all the answers are known. Prefer simple, pragmatic solutions over unnecessary complexity. We’re especially interested if you Have worked in solution engineering, sales engineering, pre-sales, or built software for GTM teams. Understand the modern GTM stack: CRM, enrichment, outbound, automation, and product signals. Have automated sales or marketing workflows, ideally with agents or LLMs. Have owned a technical product from a blank repo to something people actually used. GTM experience is not mandatory, but if you already understand how sales and marketing teams work, that is a strong advantage. What we offer A competitive salary and strong benefits package. The runway and resources of an established company, with startup-level autonomy. A founding role with direct influence over both product and architecture. Real users and real workflows from day one. Freedom to choose the stack, tools, and technical approach. A chance to help define what an agent-native GTM product should look like. #LI-IM We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. We process the data provided in your job application in accordance with the Recruitment Privacy Policy.