Вакансии

Location: Poland; Georgia; Serbia; Bulgaria; Armenia We build cloud CPaaS/CCaaS infrastructure - the routing, messaging and real-time layer that contact centres run on. High traffic, event-driven services, and a UI that has to stay correct while thousands of live conversations move through it. We're hiring a senior engineer for a team where AI agents are part of the normal development loop, not a pilot. You'll own features end-to-end across a Go backend and a React/TypeScript frontend, and you'll be accountable for everything you ship — including the parts an agent wrote. This is not a prompt-engineering role. It's a senior engineering role where AI-assisted delivery is the default working method. Requirements What will you do at MMDSmart? Own features end-to-end across Go backend and React/TypeScript frontend; Design and develop solutions for high-load and distributed production systems; Use AI coding agents as an integral part of your everyday development workflow; Guide AI agents, review and verify their output, and take ownership of the final result; Build and evolve backend services, APIs, frontend functionality, and external integrations; Investigate complex production issues and drive them to resolution; Contribute to architecture decisions, technical discussions, and system improvements; Help improve our codebase and development practices to make AI-assisted engineering more effective. You are a perfect match if you have: 5+ years of professional software engineering experience and strong Senior-level engineering fundamentals; Strong hands-on production experience with Go - 4 years of experience; Practical experience with React and/or TypeScript; you don’t need to be a frontend expert, but you should be comfortable working with frontend code; Hands-on experience with high-load and distributed production systems; Experience designing, building, and debugging production services and APIs; Hands-on experience with AI coding tools such as Claude Code, Cursor, Windsurf, Copilot, or similar - beyond simple autocomplete; Ability to use AI to work effectively across different parts of the stack while critically reviewing and verifying its output; Strong engineering judgement, ownership, and ability to make technical decisions independently. Our Tech Stack: Backend: Go, microservices, REST APIs, GraphQL Frontend: React, TypeScript, Zustand / Redux Toolkit, WebSocket / SSE Event-driven: Kafka, NATS / JetStream, RabbitMQ, event-driven architecture Data: PostgreSQL, Redis, MongoDB Infrastructure: GCP, Kubernetes, Docker, CI/CD, Infrastructure as Code Observability & Performance: structured logging, metrics, tracing, profiling, high-load and concurrency tooling AI Development: Claude Code, Cursor, Windsurf, Copilot and other agentic development tools Domain: CPaaS / CCaaS, messaging, voice, real-time communication, external provider integrations Will be a plus: CCaaS / CPaaS / telecom background: contact-centre routing, ACD, omnichannel messaging. Voice stack: WebRTC, SIP, media servers, or CPaaS APIs API gateway and microservices integration; GraphQL federation. Kubernetes, Docker, CI/CD ownership, infrastructure-as-code. Polyglot persistence: Redis for caching and ephemeral state, PostgreSQL where a document model is the wrong fit; plus the judgement to tell the difference. MongoDB Atlas or self-managed cluster operations. Internal tooling, evals or automation built on LLM APIs. Open-source contributions, especially in Go. What you get: An AI-first engineering environment where AI is part of real production development; The opportunity to use AI to work across the full stack and expand beyond your primary expertise; Work on high-load communication products with real business impact; A team where Senior Engineers influence technical decisions and architecture; Remote work. Benefits Why do talents choose and stay at MMDSmart? Embrace the opportunity to work in a company that cares about: Your Wellness: Access to mental health programs, comprehensive medical insurance, and a sports card*. Your Happiness: Enjoy the company of cool teammates, a friendly atmosphere, a strong mentorship, and a variety of bonuses & corporate gifts. Your Development: Benefit from free educational events & courses, and English classes with native speakers. Your Career: Focus on your professional development in a supportive environment. Work-Life Balance: Choose your working format - remote, office-based, or hybrid and engage in team-building activities. Think this role's got your name on it? Go ahead and apply, we'd love to see what you've got! Equal-Opportunity Employment We are an equal opportunity employer committed to creating a diverse and inclusive work environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. *Medical Insurance and Sport Card perks are available for employees located in Bulgaria.

Location: San Francisco, CA; New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. About the Team The Infrastructure team builds and maintains the systems that power LangChain’s developer platform, including LangGraph Cloud and LangSmith. The team focuses on reliability, scalability, and developer productivity across the stack, working closely with backend, frontend, and platform engineers to ensure services are deployed, tested, and operated with confidence. About the Role We’re hiring a Software Engineer to join the Infrastructure team and own developer productivity across our LangGraph Cloud/Platform and LangSmith products. You’ll work closely with Infrastructure, Backend, and Frontend teams to ship with confidence across Kubernetes-based services, APIs, and UI flows. You’ll also help pioneer quality practices specific to LLM applications, such as prompt regression testing and evaluation suites. Location: In person 5 days/week in San Francisco, CA or New York, NY What You'll Do - Own test strategy end-to-end across APIs, services, UI, data, and infrastructure (Kubernetes, Terraform, Helm) - Stand up ephemeral test environments in Kubernetes for pull requests and release candidates; seed test data and run hermetic test suites - Shift quality earlier in CI/CD pipelines (GitHub Actions) through parallelization, caching, deterministic seeds, flake tracking, and quality gates - Build observability into testing workflows with rich failure artifacts such as logs, traces, and dashboards - Establish performance and reliability baselines for critical paths, including SLIs, SLOs, and regression detection - Partner on incident workflows by reproducing issues, adding targeted regression tests, and improving runbooks and postmortems - Write documentation including test plans, playbooks, and contributor guidelines for writing high-quality tests Example projects you might own - A pull-request ephemeral end-to-end testing harness that deploys a minimal LangSmith stack in CI and runs Playwright and API suites against seeded tenants - A k6 performance scenario that simulates multi-tenant traffic and surfaces p95/p99 latency regressions per release - A flake-budget system that automatically quarantines flaky tests, opens issues with artifacts, and tracks time-to-deflake What You'll Bring - 3+ years of experience as a software engineer or infrastructure engineer - Strong hands-on experience with Python and testing frameworks such as pytest - Experience working with CI/CD systems (GitHub Actions preferred) and improving pipeline performance and reliability - Solid understanding of API testing, mocking/stubbing, and data setup/teardown - Comfort defining quality standards, writing test plans, and driving cross-team execution Nice to Have - Experience with load and performance testing tools such as k6 - Familiarity with observability tooling such as Datadog or OpenTelemetry - Experience testing services running on Kubernetes and containerized environments - Basic infrastructure experience with Helm, Terraform, Kubernetes networking, or secrets management - SQL fluency for validating data (Postgres, ClickHouse, BigQuery) - Familiarity with Go, Node, or React for targeted white-box tests and improving system testability Compensation - Annual salary range: $165,000- $250,000 USD COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: San Francisco; New York City Perplexity Computer is one of the defining products of the new era of agentic AI. Millions of people use Perplexity to transform knowledge into action, and the Agent Capabilities team sits at the intersection of frontier AI research and product innovation, building the foundations that shape how users and agents solve increasingly complex tasks. As every major breakthrough in AI models creates new possibilities, the Agent Capabilities team is responsible for turning frontier AI breakthroughs into reusable product capabilities. We are often the first to evaluate emerging model capabilities, determine where they create real user value, and transform them into reliable, scalable, high quality experiences for both users and agents. This is a highly leveraged role with broad ownership at the intersection of frontier AI research, agent systems, platform engineering, and product innovation. Tech Stack: Python | Go | Rust | PostgreSQL | DynamoDB | AWS | TypeScript WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Evaluate frontier models against real user tasks, identify useful behaviors and failure modes, and turn the most promising advances into production agent systems. Own the lifecycle from rapid prototyping and evaluation through launch, monitoring, and iteration. - Improve agents’ ability to plan, use tools, manage context, recover from errors, and complete long-running tasks reliably. - Apply state of the art ML and LLM techniques to design scalable agent capabilities such as skills, plugins, artifact generation, tools integrate and use, auto-research, and multi-agent collaboration. Shape the architecture, abstractions, and product experiences that enable both users and agents to compose increasingly sophisticated solutions for real-world tasks. - Own agent behavior and capabilities end-to-end, from user-facing products and interfaces to backend services. Define offline and online evaluations for task completion, correctness, safety, latency, cost, and user satisfaction. Iteratively improve across models, prompts, harnesses, and products for different problem spaces. - Build secure, observable, and reliable agent systems, including permissions and safeguards for sensitive actions. Develop tracing, replay, and monitoring infrastructure that makes agent failures reproducible and actionable. - Collaborate closely with PM, Data Science, Research, to identify high-impact opportunities in understanding and validating emerging model capabilities, and turn complex agent behaviors into simple, reliable product experiences. - Apply relevant advances in models, inference, evaluation, and agent architecture when they produce measurable improvements in production performance. Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and technical leadership. QUALIFICATIONS - Typically 6+ years of professional software engineering experience, with a track record of building and owning robust AI-powered, large-scale, user-facing or data-intensive products. Exceptional candidates with less experience and an outstanding record of impact are encouraged to apply. - Strong software engineering fundamentals, with experience building and operating AI/ML products, backend services, or distributed systems at scale. - Experience owning the AI product lifecycle, including data analysis, rigorous evaluation, production monitoring, and iterative improvement. Able to define metrics and use production data and user feedback to guide decisions. - Practical experience in one or more relevant areas, such as agent harnesses, tool use, context engineering, model evaluation, browser automation, or long-running task execution. - Strong product judgment and execution: you can translate ambiguous user needs into applied AI or ML problems and ship durable solutions with measurable user impact. - Genuine interest in frontier AI capabilities, agent systems, and excitement for rapidly exploring, evaluating, and productizing new model behaviors. NICE TO HAVE - Experience with LLM context engineering or harness engineering, experience with subagents, coding assistants, long-running or autonomous task execution. - Deep familiarity with the strengths and limitations of current model families across reasoning, tool use, context management, and long-horizon tasks. - Experience building agent permissions, safeguards, evaluation infrastructure, or production observability systems. - Experience with mid-training, post-training, or reinforcement learning for frontier or open-source models, along with a strong understanding of model strengths and limitations across reasoning, tool use, context management, and long-horizon tasks. - AI/ML research experience demonstrated through publications, open-source contributions, or other meaningful research impact. - Time spent at a fast-growing startup or on a high-ownership engineering team.

Location: San Francisco; New York City Perplexity Computer is one of the defining products of the new era of agentic AI. Millions of people use Perplexity to transform knowledge into action, and the Agent Capabilities team sits at the intersection of frontier AI research and product innovation, building the foundations that shape how users and agents solve increasingly complex tasks. As every major breakthrough in AI models creates new possibilities, the Agent Capabilities team is responsible for turning frontier AI breakthroughs into reusable product capabilities. We are often the first to evaluate emerging model capabilities, determine where they create real user value, and transform them into reliable, scalable, high quality experiences for both users and agents. This is a highly leveraged role with broad ownership at the intersection of frontier AI research, agent systems, platform engineering, and product innovation. Tech Stack: Python | Go | Rust | PostgreSQL | DynamoDB | AWS | TypeScript WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Evaluate frontier models against real user tasks, identify useful behaviors and failure modes, and turn the most promising advances into production agent systems. Own the lifecycle from rapid prototyping and evaluation through launch, monitoring, and iteration. - Improve agents’ ability to plan, use tools, manage context, recover from errors, and complete long-running tasks reliably. - Apply state of the art ML and LLM techniques to design scalable agent capabilities such as skills, plugins, artifact generation, tools integrate and use, auto-research, and multi-agent collaboration. Shape the architecture, abstractions, and product experiences that enable both users and agents to compose increasingly sophisticated solutions for real-world tasks. - Own agent behavior and capabilities end-to-end, from user-facing products and interfaces to backend services. Define offline and online evaluations for task completion, correctness, safety, latency, cost, and user satisfaction. Iteratively improve across models, prompts, harnesses, and products for different problem spaces. - Build secure, observable, and reliable agent systems, including permissions and safeguards for sensitive actions. Develop tracing, replay, and monitoring infrastructure that makes agent failures reproducible and actionable. - Collaborate closely with PM, Data Science, Research, to identify high-impact opportunities in understanding and validating emerging model capabilities, and turn complex agent behaviors into simple, reliable product experiences. - Apply relevant advances in models, inference, evaluation, and agent architecture when they produce measurable improvements in production performance. Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and technical leadership. QUALIFICATIONS - Typically 6+ years of professional software engineering experience, with a track record of building and owning robust AI-powered, large-scale, user-facing or data-intensive products. Exceptional candidates with less experience and an outstanding record of impact are encouraged to apply. - Strong software engineering fundamentals, with experience building and operating AI/ML products, backend services, or distributed systems at scale. - Experience owning the AI product lifecycle, including data analysis, rigorous evaluation, production monitoring, and iterative improvement. Able to define metrics and use production data and user feedback to guide decisions. - Practical experience in one or more relevant areas, such as agent harnesses, tool use, context engineering, model evaluation, browser automation, or long-running task execution. - Strong product judgment and execution: you can translate ambiguous user needs into applied AI or ML problems and ship durable solutions with measurable user impact. - Genuine interest in frontier AI capabilities, agent systems, and excitement for rapidly exploring, evaluating, and productizing new model behaviors. NICE TO HAVE - Experience with LLM context engineering or harness engineering, experience with subagents, coding assistants, long-running or autonomous task execution. - Deep familiarity with the strengths and limitations of current model families across reasoning, tool use, context management, and long-horizon tasks. - Experience building agent permissions, safeguards, evaluation infrastructure, or production observability systems. - Experience with mid-training, post-training, or reinforcement learning for frontier or open-source models, along with a strong understanding of model strengths and limitations across reasoning, tool use, context management, and long-horizon tasks. - AI/ML research experience demonstrated through publications, open-source contributions, or other meaningful research impact. - Time spent at a fast-growing startup or on a high-ownership engineering team.

Задачи: — Сотрудничество с бизнес-стейкхолдерами для понимания их потребностей и требований — Анализ и документирование бизнес-процессов, рабочих процессов и функциональностей систем — Проектирование и предложение технических решений, соответствующих бизнес-целям и технологической стратегии FxPro — Разработка детальных системных спецификаций, диаграмм и блок-схем для руководства разработчиками — Тесное взаимодействие с командами разработки для контроля реализации системных решений — Обеспечение бесшовной интеграции новых систем с существующей инфраструктурой и платформами Требования: — Опыт работы системным аналитиком не менее 5 лет — Экспертиза в анализе и документировании требований для backend-сервисов — Опыт создания детальных системных спецификаций, wireframes, диаграмм и блок-схем — Владение созданием комплексной технической документации — Знание системной архитектуры — Опыт работы с RESTful APIs, GraphQL и интеграцией сторонних API — Знание отраслевых стандартов и требований регуляторов — Сильные навыки решения проблем и устранения неполадок — Отличные устные и письменные коммуникативные навыки — Способность к сотрудничеству и работе в команде — Аналитическое мышление — Адаптивность к изменяющимся бизнес-требованиям — Свободное владение английским и русским языками Желательно: — Глубокие знания торговых систем — Понимание принципов UX/UI дизайна Условия: — Отличный компенсационный пакет — Медицинская страховка — Пенсионный фонд — Собственный спортзал с персональным тренером — Бесплатное ежедневное питание, закуски и напитки — Корпоративная дисконтная карта на различные товары и услуги — 21 день ежегодного отпуска и 10 дней больничных в год — Трансфер из Лимассола — Подарок на день рождения — Бонус на релокацию и поддержка в оформлении визы/разрешения на работу

Задачи: - Разрабатывать и развивать frontend на React / Next.js, реализовывать интерфейсы по Figma с TailwindCSS - Строить мультидоменную и мультивитринную архитектуру, конфигурационный подход для storefront - Интегрировать frontend с backend на Django через REST API, работать с платёжными и subscription API, webhook-события - Реализовывать ключевые страницы: Landing, Pricing, Checkout, Login, My Account; GEO-зависимый контент - Оптимизировать Core Web Vitals, обеспечивать SEO и кроссбраузерность Требования: - От 3 лет коммерческого опыта с React, уверенное знание Next.js и TypeScript, опыт с TailwindCSS - Уверенная работа с REST API, опыт интеграции frontend с backend на Django - Опыт с SSR / SSG, понимание routing и middleware в Next.js - Понимание принципов multi-tenant / multi-domain архитектуры, feature flags - Будет плюсом: интеграция с платёжными системами, recurring payments, финтех Условия: - График: 5/2 с 10 до 18, отпуск 21 день, оплачиваемый больничный - Формат работы: удалённо

Location: Remote Who we are Our mission is to bring clarity and control to the world's most complex codebases. AI is accelerating code creation, but the infrastructure to understand, oversee, and evolve that code hasn't kept pace. Sourcegraph gives engineering organizations full visibility across their systems, precise context for their agents, and the ability to execute coordinated code changes at scale. As agentic development becomes the dominant engineering paradigm, we provide the context layer teams need to take control of their codebase. With Code Search, Deep Search, MCP, and Agentic Batch Changes, we deliver on that mission today - giving engineering teams and their AI tools the cross-repo context to navigate massive codebases with confidence, and the ability to make changes across hundreds of repositories at once. Companies like Stripe, Reddit, and Leidos rely on Sourcegraph to ship faster and with higher quality. We're backed by a16z, Sequoia, and Redpoint, and proud to operate as a globally distributed team that values high agency, direct communication, and customer love. If you want to build the infrastructure that lets every engineering team - and every agent they deploy - operate on their codebase with confidence, join us. Hours & location 🌎 While we hire almost anywhere in the world, we have a preference for someone to reside in the following locations for this role. However, if you feel qualified, we welcome you to apply regardless of location. No matter what, working hours must overlap with EST for at least 20 hours/week. Preferred locations: USA Why this job is exciting Sourcegraph is at the forefront of building AI tools to solve the biggest problems in the software industry, problems that only get bigger as codebases grow and as more of the work is done by agents. The Code Understanding team owns the surfaces where that intelligence meets the developer: Deep Search , our agentic, multi-step answer engine across an enterprise's entire lineup of codebases, Query Assist , turning natural language queries into Sourcegraph query syntax, Smart Hovers , concisely summarizing symbols right where devs need it, guided diff review, and the APIs that both humans and AI agents rely on every day. Most of what makes those surfaces tick is agent engineering : a blend of software engineering, machine learning, and statistics. Agent engineering tells us which model to use and when, how to retrieve and pack context, how to measure answer quality, where to fine-tune or distill a smaller model to cut costs and latency, and how to expand a single LLM call into a reliable multi-step agent. As the staff ML and agent engineer on Code Understanding , you'll be the technical owner of it: setting the tam’s direction for models, evaluations, and agentic systems, making our products measurably better, faster, and cheaper, and raising the team's fluency in building with models. This is a staff-level role : we're hiring a technical leader, not just a strong individual contributor. The primary need is a production ML and evaluation authority who also builds production agent systems. You'll own the hardest, most ambiguous problems in this space, set standards others follow, and influence direction beyond your immediate team. You'll get the exhilarating chance to drive the vision on how we can provide the best code understanding experience on the market by combining our deterministic, large-scale systems and AI into experiences never seen before. Concretely, you'll own work like: Agentic systems. You'll design and harden the multi-step, tool-using agent loops behind current and new agentic experiences, turning research and experiments into reliable, observable, and affordable products at enterprise scale. Pragmatic use of evaluations. Crafting agentic products means needing to tell when a change actually helped, which is hard when agents keep changing and the product keeps shifting. You'll bring judgment about where evaluations earn their keep, when to use targeted smoke tests and metrics, and how to avoid noise dressed up as rigor, so we can move fast with confidence. Models: selection, upgrading, and training. You'll decide which models we run where, drive upgrades, and fine-tune our own when that's the right call. Retrieval and context engineering. You'll push on how we ground models in a customer's code - retrieval, ranking, context windows, citations - to make answers more accurate and verifiable. Cost and latency. Every surface has a per-user economic budget. You'll treat cost and latency as product features, and profile, distill, cache, and right-size models so we can ship ambitious features sustainably. You'll do this on a small, senior-leaning team that ships quickly, owns a lot of product surface, and has streamlined product management: engineers here talk to customers, frame the problem, and own it end-to-end. You'll have real agency over technical direction and a direct line to the impact of your work. 📅 Within one month, you will… Get the Code Understanding products and their model/agent pipelines running end-to-end locally, and land your first improvements to a model, prompt, retrieval path, or eval. Build a clear picture of where the AI engineering pain is, and the product surfaces most constrained by them. Get to know the team and our customers, and start forming your own opinions about where our agentic products should go next. Join the team's on-call support rotation. 📅 Within three months, you will… Own a meaningful agentic slice of the product end-to-end, driving it from problem-framing through rollout and measurement. Establish how the team ships model and prompt changes responsibly: the evals, dashboards, and guardrails that make quality and cost regressions visible before customers feel them. Begin up-leveling teammates in building with models by pairing with them, reviewing their code, and modeling good agent engineering instincts. 📅 Within six months, you will… Be the recognized technical authority for agent engineering and agentic systems on Code Understanding. You will be the person teammates, and increasingly the wider department, defer to on model, eval, and agent-design decisions. Have measurably moved the products: better answer quality, lower cost/latency, or new agentic capabilities that weren't feasible before. Be setting the direction of the team's roadmap where it intersects agents, bringing conviction, backed by evidence, about which bets are worth making, and pulling other engineers up to execute on them. About you You are a staff engineer and technical leader with hard-won skills across production machine learning, evaluation, and agent systems . This high-leverage role relies on your ability to make sound model and evaluation decisions for a fast-moving product, build the production systems around them, steer technical direction, and be a force multiplier for a talented, product-minded team. You're equally comfortable reasoning about an eval harness, a fine-tuning run, a retrieval pipeline, and the multi-step agent loop that ties them together, and you make everyone around you better at all of it. You operate at staff scope: you own the most ambiguous, highest-risk problems in your domain, go into whatever codebase a problem requires, set standards and patterns others adopt, and translate fluidly between engineering goals and business objectives. You influence direction beyond your immediate team. You lead through technical excellence and mentorship. You have personally owned a production model lifecycle. You have trained or fine-tuned at least one model and taken it from dataset construction through evaluation, production rollout, and monitoring. You can explain how you chose between training or fine-tuning and prompting or retrieval, how you chose baselines and metrics, what error analysis revealed, and how production evidence affected the next version. You build agents, fluently and opinionatedly. You've designed multi-step agentic systems and made them reliable, observable, and cost-bounded. You have a point of view on where agents shine and where deterministic code or human judgment is required. You have strong evaluation judgment. You build representative datasets, meaningful baselines, useful error taxonomies, and release criteria that connect offline measurements to production behavior. You know where rigorous evaluations earn their keep, where lightweight smoke tests or qualitative review are enough, and where a precise-looking metric is misleading. You treat cost and latency as product constraints. You make measured quality, latency, and cost tradeoffs and use the appropriate combination of model selection, prompting, retrieval, caching, distillation, and fine-tuning rather than reaching reflexively for a more complex model. You operate autonomously on ambiguous problems. Given a rough product idea, a few customer quotes, and a Slack thread, you come back with a plan, a prototype, milestones, and a point of view on tradeoffs, without it being pre-scoped. You own high-technical-risk projects end-to-end. You contribute beyond your domain. As a senior IC, you go into whatever part of the codebase a problem requires, recognize issues beyond your immediate area, and translate between engineering goals and business objectives. You up-level the people around you. You mentor by pairing on hard problems, providing substantive design and code reviews, and spreading agent engineering literacy across the team. You see investing in your teammates' growth as part of the job. You're customer and product-driven. You're comfortable on customer calls and in feedback threads, you turn raw signals into requirements, scopes, and milestones, and you push back when feedback would lead the product astray. You're pragmatic, not a perfectionist. You ship the smallest correct thing, prefer robust solutions over complicated ones, and keep a high-quality bar with simplicity. On the engineering fundamentals: You're a strong software engineer who can ship production services. You're comfortable across our stack - Go on the backend, TypeScript on the frontend, GraphQL, Postgres, Docker - or you're clearly able and eager to get there. You're fluent with agentic coding tools, and you understand and own every line it submits. You're comfortable in an async-first, multi-service, fast-paced remote environment. Nice-to-haves: You've shipped an LLM-powered or agentic developer-facing product you can speak about opinionatedly: what worked, what didn't, what you'd do differently. You've fine-tuned, distilled, or trained models to meet cost, latency, or quality targets in production. Experience with retrieval, ranking, embeddings, or search relevance. Experience working directly with enterprise customers and translating their needs into a product. Experience mentoring or up-leveling engineers, especially raising a team's agent engineering fluency. Level 📊 This job is an IC4. You can read more about our job leveling philosophy in our Handbook. Compensation 💸 We pay above-market salaries because we want to hire exceptional people who can focus on building great products, not worrying about paying bills. As an open and transparent company, our compensation philosophy and pay bands are visible to every Sourcegraph teammate, and we strive to make our approach equitable, explainable, and competitive. Your base salary is determined by the IC4 pay band for your location zone (1-4). Our pay bands are informed by market data and designed to ensure competitive compensation wherever you live. During the recruiting process, we'll discuss the range applicable to you based on job level, relevant skills, experience, qualifications, and location zone. 💰 The starting salary for the IC4 pay band in each zone is: Zone 2: $176,000 USD Zone 3: $132,000 USD Zone 4: $88,000 USD 📈 In addition to competitive cash compensation, we offer meaningful equity (because when Sourcegraph succeeds, we want you to succeed, too) and generous perks & benefits . Interview process Below is the interview process you can expect for this role (you can read more about the types of interviews in our Handbook). It may look like a lot of steps, but rest assured that we move quickly and the steps are designed to help you get the information needed to determine if we’re the right fit for you… Interviewing is a two-way street, after all! We expect the interview process to take 5.5 hours in total. 👋 Introduction Stage - we have initial conversations to get to know you better… [30m] Recruiter Screen [30m] Hiring Manager Screen 🧑‍💻 Team Interview Stage - we then delve into your experience in more depth and introduce you to members of the team, including cross-functional partners… [60m] Resume Deep Dive [60m] System Design [60m] Harden a Code Research Agent Interview [60m] Cross-functional team collaboration / Values 🎉 Final Interview Stage - we move you to our final round, where you gain a better understanding of our business and values holistically… [30] Leadership We check references and conduct your background check Please note - you are welcome to request additional conversations with anyone you would like to meet, but didn’t get to meet during the interview process. Learn more about us You can learn more about what it is like to work at Sourcegraph by reading our handbook . We are an ambitious team who are collectively working hard to build the most influential company in the world. You can read more about our culture , competitive compensation and benefits here. Sourcegraph is an equal opportunity workplace; we welcome people from all backgrounds. Sourcegraph participates in E-Verify for U.S. Employees.

Location: Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; Madrid, Spain; Munich, Germany; Paphos, Cyprus; Prague, Czech Republic; Remote, Germany; Warsaw, Poland; Yerevan, Armenia If you want to build and own the systems that decide what JetBrains customers are entitled to use and bill them accurately for it, this is for you. You will focus on designing backend services, keeping complex commercial flows correct, and tackling hard distributed systems challenges on the critical path of every paid request. 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. What you’ll do At JetBrains, the Cloud Platform department builds the underlying infrastructure that powers authentication, paid capabilities, usage metering, and accounting. Within this department, the Licensing & Billing team sits right at the center of our commercial model, turning what a customer buys into what they are actually allowed to use, and accounting for that consumption accurately enough to bill on. The complexity of our entitlement, quota, and metering systems continues to grow. In this role, you will own the correctness and evolution of these backend services, take full ownership of end-to-end data flows, tackle distributed consistency across unreliable upstream systems, and ensure revenue-affecting data migrations happen cleanly without taking services offline. Day to day, you will: Design, build, and operate backend services that decide what a customer is entitled to and what their usage costs. Own flows end to end, from ingesting licensing and purchase data from upstream systems to enforcing quotas and recording consumption. Evolve our domain model to handle new commercial structures, combining seat-based plans and usage-based models. Design integrations with external systems, ensuring correctness through idempotency, ordering, reconciliation, and eventual consistency. Plan and execute live data migrations using feature flags, dual writes, backfills, and verification at every stage. Build observability into our systems by defining invariants, metrics, and alerts to catch silent divergence before customers do. Design internal APIs with explicit focus on versioning, backward compatibility, and developer experience for other JetBrains teams. Improve system performance and reliability under continuous production load while decommissioning legacy subsystems. Write integration tests against real dependencies and maintain reliable test infrastructure. Investigate production incidents, find root causes, and follow through on lasting fixes. What you’ll bring An engineer’s dedication to accuracy, especially in domains where system errors have direct financial impact. Pragmatic judgment when designing distributed systems where correctness under unreliable delivery is the main constraint. A habit of trusting metrics, traces, and logs to understand production behavior rather than relying on assumptions. Comfort navigating and simplifying large existing codebases containing legacy decisions. Clear, direct communication skills to agree on API contracts across teams with different priorities. A focus on testing as an essential design tool rather than an afterthought. What you’ll need A proven track record of building and operating backend services on the JVM platform using Kotlin or Java. A solid working knowledge of relational databases, including transactions, isolation levels, locking, indexing, and live schema migrations (PostgreSQL preferred). A deep understanding of distributed systems patterns, such as idempotency, retry strategies, eventual consistency, and data reconciliation. Practical experience making live data migrations or system changes without downtime using feature flags and staged rollouts. Experience designing versioned, backward-compatible APIs for other engineering teams. Hands-on experience with event-driven architectures and message brokers like Kafka. The ability to diagnose, debug, and resolve production incidents in complex environments. Proficiency in both written and spoken English. What success looks like Success in this role means building a bulletproof entitlement and metering foundation that product teams can trust without hesitation. You will have successfully migrated live commercial systems to support new billing models without downtime or data divergence. Silent errors will be caught automatically by system invariants before affecting users, and internal teams will integrate seamlessly with your clean, versioned APIs. Why join JetBrains? Strong base salary. We offer competitive pay that reflects your skills and experience. Flexible work location. Enjoy the freedom to work from home or from the office. Remote work. Spend up to 30 days per year working remotely from abroad. Extra time off. More days to relax, recharge, and do the things you love. Medical insurance allowance. Enjoy peace of mind for you and your family Learning and development opportunities. Access to conferences, courses, and language classes. Relocation support. We help make your move as smooth and stress-free as possible. (keep if relevant for the role) Language classes. Pick up the local language or sharpen your English skills. Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays. Mental health support. To help you feel your best, we provide easy access to professional mental health services. Sports benefit. Enjoy an on-site gym or sports club stipend. Internal events. Join company-wide celebrations and team gatherings. *Some benefits may vary depending on location. #LI-KT1 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.

Location: London, United Kingdom Workplace: fully About InvestEngine InvestEngine is a fast-growing fintech company based in London, on a mission to make ETF investing simple and accessible. Over 150,000 clients trust us with more than £3 billion in assets under management — and we’re just getting started. We’ve been featured in MoneyWeek, Finder, and Forbes, and we’re scaling quickly with ambitious plans for both our product and engineering organization. About the Role We’re looking for two Senior Engineering Managers to help build a stronger management layer in engineering and support multiple product teams across InvestEngine. This is a high-impact leadership role focused on engineering management, delivery, team performance, and organizational scaling. You’ll work closely with the CTO, CPO, and multiple Team Leads reporting to you to help teams operate effectively, deliver business impact, and scale sustainably as the company grows. One role will focus more on customer-facing product teams, while the second role will work more closely with infrastructure and operational teams, including Payments, Trading, Pension, and Back Office systems. While this role is less hands-on than a traditional Tech Lead position, a strong engineering background and technical judgment are still important. What You’ll Do Manage and support multiple engineering teams and Team Leads Improve delivery processes, team performance, and engineering effectiveness Help scale engineering processes and organizational structure Drive operational and process improvements across teams Support architectural discussions and long-term technical strategy Mentor engineers and engineering leaders Help improve planning, communication, and cross-team collaboration Contribute to engineering culture and organizational growth What We’re Looking For Strong engineering management experience leading multiple teams or Team Leads Previous software engineering background (backend or full-stack preferred) Experience working in product companies rather than pure outsourcing environments Experience scaling teams, processes, and engineering organizations Experience building engineering processes and delivery practices Strong communication and stakeholder management skills Ability to operate in ambiguity and drive initiatives independently Collaborative leadership style with strong mentoring mindset English level С1 Bonus if you have Experience in fintech or regulated industries Experience in high-growth product companies Experience working with metrics and operational improvements How We Work We’re a lean, collaborative engineering organization where managers and engineers have real influence on product direction, engineering culture, and technical decisions. We care about ownership, pragmatism, continuous improvement, and building scalable systems and teams — without unnecessary bureaucracy. What We Offer Direct impact on product and engineering growth Opportunity to shape a scaling engineering organization Remote-first and flexible working environment High level of ownership and autonomy Modern tech environment and experienced engineering teams Unlimited vacation policy Hiring Process Intro call with our Talent team Technical interview with the Backend team Gamified cognitive assessment to understand how you think and problem-solve Final conversation with our CTO

Location: Canada Workplace: Remote ABOUT THE TEAM The AI/ML Engineering team builds and operates ClickHouse's AI and machine learning products end-to-end. This includes the Agentic Data Stack, AI Functions, chDB, the in-Console copilot, and the AI/ML partnerships that distribute them — together with the shared components and expertise that let every other ClickHouse team ship AI in the surfaces they own. Our team is looking for highly skilled and experienced software engineers to join us, who will be responsible for designing, building, and operating the products that make ClickHouse the platform of choice for agents and data scientists. WHAT YOU WILL DO - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. - Oncall: Participate in the daytime oncall rotation along with the rest of the team. - UI/UX Implementation: Build responsive, intuitive user interfaces that make complex AI functionalities accessible and valuable to users of all technical backgrounds. WHAT YOU WILL BRING ALONG - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - A high level of ownership and can drive features from concept to production with minimal supervision - Ability to thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders - Strong frontend skills with TypeScript/JavaScript and React Nice to have - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus - Experience building data-oriented interfaces and visualizations PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: United States Workplace: Remote NOTE: This role is not office-based, and the final candidate can be in any EMEA country ClickHouse hires in (such as The Netherlands, Germany, Spain, Italy, UK, or Portugal). We are looking for a Senior Software Engineer to drive the development of AI/ML-powered features in ClickHouse Cloud. In this role, you will bridge the gap between a high-performance database technology like ClickHouse and AI capabilities, implementing AI/ML integrations and end-to-end solutions from the Inference API layer to the user interface that enhance how users interact with and extract value from their data. What will you do? - Feature Development: Design and implement AI-powered features across the full stack, from backend inference services to intuitive frontend interfaces within the ClickHouse Cloud platform. - API Architecture: Create robust, scalable APIs that connect ClickHouse's database capabilities with modern AI/ML inference systems and external/internal AI services. - UI/UX Implementation: Build responsive, intuitive user interfaces that make complex AI functionalities accessible and valuable to users of all technical backgrounds. - Ecosystem Integrations: Implement and maintain integrations with the broader AI/ML ecosystem and standards, ensuring that ClickHouse as a technology works seamlessly with popular frameworks and tools. - Technical Integration: Integrate models into production systems with proper monitoring, versioning, observability, and evaluation. What you bring along: - 5+ years of software engineering experience in production environments - Exposure to working directly with AI/ML technologies - Strong frontend skills with TypeScript/JavaScript and React - You have a high level of ownership and can drive features from concept to production with minimal supervision - You thrive in collaborative environments and can effectively communicate technical concepts to diverse stakeholders Nice to have - Experience building data-oriented interfaces and visualizations - Experience integrating and deploying AI/ML models in production systems, including working with inference APIs and vector databases - Familiarity with cloud technologies such as AWS, Azure, or GCP, particularly services related to AI/ML deployment - Understanding of database systems and data processing pipelines, with ClickHouse experience being a significant plus #LI-Remote PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Ищем hands-on DevSecOps / Security специалиста для проекта в сфере regulated crypto / fintech. Основная задача — разбирать результаты IT/Security-аудитов и технически закрывать выявленные vulnerabilities, security gaps и audit findings. Что важно: • DevSecOps / Application / Infrastructure / ICT Security; • DORA — обязательно; • MiCA, ISO 27001 или аналогичные стандарты; • опыт security/compliance-аудитов; • понимание regulated crypto / fintech; • умение самостоятельно делать remediation. Будет плюсом: Fireblocks, crypto custody, MPC, crypto exchanges, custodians, fintech/payment. Не рассматриваем чистых Compliance Officers, специалистов только по документации и Backend Developers без Security/DevSecOps опыта.

Location: Brazil; Argentina; Honduras Workplace: Remote ABOUT THE ROLE We’re splitting our Analytics & Reporting group into two focused teams: a Data Engineering team that owns data acquisition and the company-wide data platform, and an App team that owns everything our customers touch, including the data-serving APIs, the Analytics section of the Uberall platform, and the reports that turn location data into decisions. We’re hiring the lead for the App team. You’ll be a player-coach: you’ll manage and grow a team of six engineers (3 backend, 2 frontend, 1 QA), partner daily with two Product Managers, a Designer, and a UX Researcher, and stay meaningfully hands-on. Roughly 20–30% of your time is spent on architecture, code reviews, and code. You’ll work as a peer to the Lead Data Engineer, with a close, explicit contract between your team’s customer-facing products and the data platform that feeds them. This is a role for someone who has led before and still loves to build. WHAT YOU’LL OWN - Customer-facing data APIs: the public APIs enterprise customers use to access their data, and the microservices behind them. - The Analytics product: the Analytics section of the Uberall platform, including its frontend, filtering experience, and the APIs powering custom reports. - Customer reporting: the QuickSight reports our customers rely on, and the gold-layer datasets that feed them. Your team owns its data models end-to-end, built on the self-serve platform the Data Engineering team provides. - Production: you build it, you run it. Your team deploys and operates its own services (Kubernetes on AWS), owns its observability and SLOs, and runs its own on-call rotation. You lead the incident process. - The team: hiring, growth, 1:1s, delivery, and the engineering culture of a newly formed team. With one QA engineer among six, you’ll make quality everyone’s job. WHAT YOU’LL DO IN YOUR FIRST YEAR - Stand up the App team as a healthy, autonomous unit: clear ownership, sustainable delivery cadence, and strong working relationships with Product, Design, and the Data Engineering team. - Co-own, from the application side, the in-flight migration of data pipelines out of our monolith and into the Data Engineering stack. Your backend engineers keep those pipelines running and hand them over cleanly, so your team can focus fully on APIs and product. - Drive the modernization of our backend estate: the stack is consolidating on Kotlin, and legacy Groovy and Scala services need a pragmatic path forward. - Shape the next chapter of Analytics: AI-assisted insights in the product, and exposing your team’s data and APIs for consumption by AI agents through the company’s data gateways. WHAT WE’RE LOOKING FOR - 7+ years of software engineering experience, with deep backend expertise on the JVM (Kotlin strongly preferred; our stack: Kotlin, Spring Boot, Postgres). - 2+ years leading an engineering team with genuine people responsibility (hiring, 1:1s, performance, and delivery) while staying hands-on. - Experience designing, operating, and evolving microservices in production: Kubernetes, AWS, observability, SLOs, and incident management. You’ve run an on-call rotation, not just been on one. - Strong SQL and analytical data modeling skills. Your team owns the datasets behind customer reports, and you can reason about them credibly. - Experience with RESTful, service-oriented architectures serving external customers at scale. - Enough frontend fluency (React, TypeScript) to lead frontend engineers well. You review their thinking, not their semicolons. - Experience navigating legacy systems and migrations. You can modernize without stopping the world. - Professional working English (read, write, speak) and comfort collaborating across a remote, distributed organization. NICE TO HAVE - Experience with Groovy, Scala, or Python - the languages of our existing services. - Experience with BI tooling (Amazon QuickSight or similar) and data warehouse platforms (Databricks, Snowflake, Redshift). - Experience building LLM-powered product features or exposing data/APIs to AI agents.

Location: Batumi, Georgia; Berlin, Germany; Munich, Germany; Lisbon, Portugal; Warsaw, Poland; Barcelona, Spain The Vault by Tría Finance is a Swiss and EU-regulated fintech group delivering institutional-grade digital asset infrastructure and services. Bringing together a software vendor and a licensed Crypto Asset Service Provider (CASP), The Vault combines deep domain expertise with a strong foundation of transparency, security, and regulatory compliance. We develop and operate a comprehensive suite of crypto-native solutions, powered by proprietary technology, enabling institutions to execute digital asset strategies across both custodial and non-custodial models. We're building a security-first platform for digital asset operations. Our product is API-driven, highly auditable, and engineered for reliability. We're looking for a Senior Full-Stack Engineer who can own features end-to-end — from clean domain modeling in Go or Node.js to a polished, crisp React UI. Responsibilities: Build end-to-end product features across Go and Node.js/Express backends and React frontend AI-assisted development: use Cursor/Copilot/ClaudeCode (or similar) daily to accelerate delivery, refactoring, and test generation—while verifying outputs and keeping code clean Design backend services using DDD patterns (bounded contexts, aggregates, domain events), clean layering, and pragmatic architecture Implement data models and migrations across PostgreSQL and MongoDB, using GORM, Mongoose, or raw queries where appropriate Build and maintain REST APIs (and webhooks/event-driven workflows where needed) in both Go and Node.js/Express Implement frontend flows in React (TypeScript): dashboards, admin workflows, status lifecycles, audit views Ensure correctness and observability: structured logging, metrics, tracing, and production-ready error handling Contribute to security fundamentals: RBAC, least-privilege access, safe secrets handling, and audit trails Own quality: unit/integration tests, contract tests, and CI pipelines Requirements Must-have 7+ years building production systems with Go and/or the MERN stack (MongoDB, Express, React, Node.js), plus solid React experience Strong backend fundamentals: concurrency, APIs, reliability, debugging Hands-on with DDD (not just buzzwords): can model domains and keep boundaries clean Strong database skills across PostgreSQL and MongoDB: schema/collection design, indexing, query tuning, migrations Experience with GORM and/or Mongoose (or similar ORMs/ODMs) plus comfort dropping to raw SQL or aggregation pipelines when needed Frontend proficiency in React (TypeScript preferred), including state management and form-heavy admin UIs Good testing discipline (Go testing, Jest/Vitest, integration tests; frontend testing basics) REQUIRED: confident daily use of AI coding tools (Cursor/Copilot/etc.) with disciplined verification and secure practices Nice to have Event-driven patterns: outbox, retries, idempotency, background jobs Experience with RBAC/policy engines, audit logs, fintech/compliance workflows Docker/Kubernetes familiarity CI/CD ownership (GitHub Actions/GitLab CI), release workflows Experience with high-security systems (custody, payments, identity) Soft skills Ownership mindset: deliver features end-to-end with high quality Clear communication and ability to work across teams Pragmatic: balances long-term design with shipping Comfortable in ambiguity and fast iteration Benefits Competitive salary; Annual performance bonus; Fully remote position — work from anywhere in the world (team operates on CET); Paid time off, including vacation, sick leave, and public holidays; Multiple projects within the company — the opportunity to discuss different projects during the interview and choose the one that's the best fit for you.

Задачи: — Развёртывание и эксплуатация продуктовых систем компании во всех средах: prod, stage, test, qa, demo. — Настройка, развитие и сопровождение CI/CD-пайплайнов для backend-сервисов (.NET), web-frontend, Node.js-сервисов и мобильных приложений (iOS/Android), включая подпись и публикацию в магазины приложений. — Сопровождение self-hosted GitLab, GitLab Runner и Container Registry: обновления, бэкапы, восстановление, производительность, права доступа. — Эксплуатация контейнерной платформы на Docker Swarm: деплой сервисов, конфигурации и секреты, сетевой слой, обратный прокси (Traefik/nginx), TLS-сертификаты. — Обеспечение воспроизводимости и единообразия окружений, контроль отличий между средами. — Автоматизация инфраструктуры как кода (Ansible, Terraform или аналоги), отказ от ручных правок на серверах. — Построение и сопровождение мониторинга, логирования и алертинга (Grafana, Prometheus, Loki, Alertmanager): SLO/SLI для продуктовых систем, дашборды, дежурные уведомления. — Организация резервного копирования и регулярной проверки восстановления для PostgreSQL, MinIO, GitLab и конфигураций. — Эксплуатация инфраструктурных компонентов платформы: PostgreSQL, Kafka, RabbitMQ, MinIO, Keycloak, Redis, включая обновления и миграции. — Работа с облачной инфраструктурой (Yandex Cloud: Cloud Functions, API Gateway, Object Storage, DNS) и GitHub Actions для облачных сервисов. — Внедрение практик безопасности в поставку: SAST/SCA, secret scanning, сканирование образов, управление секретами, ротация ключей, минимизация привилегий. — Подготовка и сопровождение runbook по каждой системе: перезапуск, откат, диагностика, восстановление после сбоя; участие в разборе инцидентов и постмортемах. — Участие в проектировании архитектуры новых цифровых сервисов с точки зрения деплоя, отказоустойчивости, наблюдаемости и стоимости эксплуатации. — Совместная с разработчиками настройка quality gates в CI/CD и стандартов ветвления, релизов и версионирования. Требования: — Высшее образование в области информационных технологий, прикладной математики, программной инженерии, автоматизации, вычислительной техники или смежных технических направлений. — Опыт работы не менее 5 лет в ИТ-инфраструктуре или разработке, из них не менее 3 лет в роли DevOps/SRE-инженера с ответственностью за production. — Дополнительное профильное обучение по разработке ПО, архитектуре, DevOps, cloud, тестированию или ИБ будет преимуществом. — Опыт построения DevOps-практик с нуля в небольшой команде: стандарты, пайплайны, мониторинг, runbook, а не только поддержка готового. — Опыт работы с распределённой по нескольким площадкам инфраструктурой (несколько хостинг-провайдеров плюс публичное облако). — Опыт организации дежурства и реагирования на инциденты, проведения постмортемов. — Опыт проверенного восстановления из бэкапов, а не только их настройки. — Опыт эксплуатации .NET-сервисов в Linux-контейнерах: диагностика производительности, память, health checks, graceful shutdown. — Готовность работать в компактной команде рядом с разработчиками, участвовать в проектировании и code review инфраструктурной части. — Умение документировать системы понятно для коллег и аргументировать технические решения. — Будет преимуществом опыт работы в корпоративной среде с повышенными требованиями к ИБ, traceability и релизному контролю. Условия: — Субсидирование ипотечного кредитования. — Льготные путевки в собственный санаторий. — Ежегодная индексация. — Расширенная ДМС (после испытательного срока). — Корпоративная программа пенсионного обеспечения. — Дополнительные выплаты: поддержка многодетных родителей, выплата при рождении ребенка. — Офис в пешей доступности от станции Сколково. — Корпоративный транспорт от м. Тропарево и от м. Новопеределкино. — График работы: с 8:30 до 17:00, пятница до 16:00.

Требования: — Опыт работы в тестировании ПО (Web, Backend); — Опыт в автоматизации тестирования с использованием Java, Selenide, RestAssured (можно до года); — Опыт тестирования систем на микросервисной архитектуре; — Опыт работы с базами данных; — Опыт тестирования REST API (ручное и автоматизированное); — Опыт работы с системой версионного контроля GIT (бранчи, пулл-реквесты и тд.); — Опыт работы с системами CI; — Умение использовать тестовые инструменты (Swagger, Postman, Fiddler/Charles, DevTools). Задачи: — Проведение ручного и автоматизированного тестирования мобильных и веб приложений; — Автоматизация тестирования с использованием Java, Selenide, RestAssured, Appium; — Тестирование API и микросервисов; — Проведение функционального и нефункционального тестирования мобильных и веб приложений, включая анализ и тестирование требований; — Написание тестовой документации, подготовка тестовых сценариев для ручного и автоматизированного тестирования; — Разработка фреймворка для тестирования; — Выявление/приоритезация ошибок и сообщение о них в системе отслеживания ошибок, выполнение RCA; — Проведение регрессионного, интеграционного тестирования. Условия: — Возможность поработать на проектах крупного Бигтеха; — Белая зарплата, трудоустройство по ТК РФ; — 31 день оплачиваемого отпуска в год; — Активная корпоративная культура с Online и Offline мероприятиями; — Добровольный ДМС (50% оплата от компании); — Корпоративные внутренние курсы: автоматизация тестирования на Java, нагрузочное тестирование; — Частичная компенсация пройденных курсов на различных платформах; — Добровольная международная сертификация ISTQB с компенсацией от компании; — Корпоративные занятия английским языком; — Оборудование от компании; — Реферальная программа "Приведи друга";

Задачи: Разработка и поддержка веб-приложений на React; Участие в проектировании архитектуры frontend-части; Интеграция с REST API / GraphQL; Оптимизация производительности интерфейсов; Работа с адаптивной и кроссбраузерной версткой; Написание чистого, поддерживаемого и тестируемого кода; Участие в code review и командной разработке; Взаимодействие с backend-разработчиками, дизайнерами и QA. Требования: Уверенное знание JavaScript (ES6+) / TypeScript; Опыт разработки на React; Понимание жизненного цикла React и React Hooks; Опыт работы с Redux / Zustand / MobX или другими state managers; Знание HTML5, CSS3, SCSS/SASS; Опыт адаптивной и кроссбраузерной верстки; Опыт работы с REST API; Понимание принципов UI/UX; Навыки работы с Git; Опыт работы с webpack / Vite; Базовое понимание CI/CD процессов; Умение работать в Agile/Scrum-команде; Коммерческий опыт Frontend-разработки от 2–3 лет. Будет плюсом: Опыт написания unit/integration тестов (Jest, React Testing Library); Знание GraphQL; Опыт работы с Docker; Понимание SSR/SSG; Опыт работы с Figma; Английский язык на уровне чтения технической документации. Условия: Формат работы — гибридный. Удалённый формат работы не рассматриваем. Гибридный формат доступен после прохождения испытательного срока. Конкурентная заработная плата — 800 000 ₸ на руки.

Location: New York Workplace: Hybrid WHY HARVEY At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. ROLE OVERVIEW As a Staff or Senior Staff Software Engineer on the Product Engineering team at Harvey, you will own and lead engineering projects that span multiple Product Engineering teams and product lines. You'll work closely with our AI, Legal, and GTM teams to build secure systems that deliver value to our customers.   Product Engineering covers a lot of ground, and we're looking for engineers across multiple domains — backend, full stack, and AI. We want people who have built great products across consumer, enterprise, and everything in between, and who are excited about building the future of application layer and genAI products. You'll build both the surfaces where lawyers meet Harvey — web, mobile, and embedded experiences in Word, Outlook, and Slack — and the agentic capabilities that power them.   This role can be based in New York City or San Francisco, with a hybrid schedule of three days a week in office.   WHAT YOU'LL DO - Bring AI to where our customers already work: build Harvey across every surface — web, desktop, mobile, and embedded experiences (Google Docs, MS Word, Outlook, and Slack), and API. - Lead large, high-priority projects that span multiple teams, and define the technical bets we make over the next several quarters. - Find the problems that are business critical, prioritize ruthlessly, and make the big tradeoff calls without slowing anyone down. - Build AI-platform and AI-native capabilities — the agent harness, agent building (custom agents and workflows), tool calling, retrieval, memory and context management, personalization and tone, the thread experience, and the evals that turn model quality into product quality. - Ship the systems that make Harvey work: retrieval over petabyte-scale document corpora, ingestion growing 10x every six months, data collection across 50+ jurisdictions, and government-level security for the world's most sensitive matters. - Ship across the stack — React and TypeScript alongside Python and Postgres — architecting intuitive UX and robust APIs for streaming results, long-running processes, and complex tool-calling workflows. - Mentor senior and staff engineers, and raise the bar for how the whole org builds.   WHAT YOU HAVE - 10+ YoE (post-BS/MS) in a product-focused software engineering role, operating at Staff level or above. - Depth in full stack, backend, or agents/AI — and enough range to be useful outside it. - Experience building scalable, extensible systems that support multiple product lines. - Track record of shipping highly intuitive products in fast-growing SaaS, strong attention to detail. - Experience with React, TypeScript, CSS (we use TailwindCSS), Python, or related. For agents/AI, proficiency in Python plus hands-on work building and shipping agentic systems — agent harnesses/loops, tool use, memory, and evals — not just calling LLM APIs. - You embrace AI in how you build: AI coding tools (Claude Code, Cursor, Codex, or similar) are a core part of how you ship, and you have sharp instincts for where they accelerate work and where they fall short. - A history of influencing and aligning engineers and leaders well outside your direct scope. - Strong programming skills and general Computer Science knowledge. - Grit — experience working at early-stage startups is a plus.   COMPENSATION $231,000 – $340,000 USD   DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.   #LI-PM1 Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai