Вакансии

-адаптировать процесс разработки под продукт, используемые технологии и команду, предлагать и внедрять улучшения в процесс разработки: правила code review, тестирования, CI/CD, релизов, документирования и контроля качества. -спокойно относиться к конструктивной критике и уметь давать её коллегам.

Разрабатывать и исследовать ML-модели для генерации изображений и визуализации интерьерных/строительных решений на основе товаров Лемана ПРО. Проектировать и реализовывать end-to-end пайплайны для PoC: от сбора и подготовки данных до обучения, оценки и демонстрации результатов.

Задачи: — Участвовать в архитектурных решениях, проектировании, развитии и эксплуатации PaaS-платформы на базе Kubernetes, включая компоненты ClickHouse и Redis/Valkey. — Автоматизировать жизненный цикл Data Services: развертывание, масштабирование, миграции, обновления, резервное копирование, репликацию и восстановление. — Создавать и развивать решения самообслуживания для команд разработки. — Стандартизировать и развивать платформенные практики: Service Catalog, SLO/SLA, GitOps и IaC. — Участвовать в устранении инцидентов, анализировать стабильность и производительность платформы. — В первую очередь развивать платформенные компоненты для ClickHouse и Redis/Valkey, формировать стандартные сценарии их предоставления и эксплуатации в Kubernetes. Требования: — Понимание Kubernetes как платформы: архитектуры control plane и data plane, жизненного цикла объектов, примитивов нагрузки Deployments, StatefulSets и DaemonSets, механизмов контроля и reconciliation. — Уверенное знание Kubernetes storage stack: StorageClass, PVC/PV, особенности stateful-нагрузок, репликация и отказоустойчивость. — Практический опыт эксплуатации и тюнинга ClickHouse от 3х лет: репликация, шардирование, ClickHouse Keeper, оптимизация запросов и хранения, резервное копирование и восстановление. — Практический опыт эксплуатации Redis или Valkey: репликация, Sentinel или Cluster, механизмы персистентности, переключение при отказах, оптимизация памяти и задержек. — Опыт развертывания и эксплуатации stateful-операторов Kubernetes для ClickHouse и Redis/Valkey или участие в разработке и кастомизации собственных операторов. — Опыт работы с Terraform и понимание принципов IaC. — Опыт построения CI/CD pipelines для инфраструктурных компонентов. — Практическое владение GitOps-подходом, например Argo CD или Flux, и умение проектировать процессы развертывания платформенных компонентов. — Понимание процессов Software Development. Дополнительно приветствуется: — Опыт решения эксплуатационных задач, связанных с кластеризацией, высокой доступностью, backup/restore и производительностью других Data Services в Kubernetes. — Опыт разработки Kubernetes-операторов и контроллеров на Go или Python. — Опыт работы с multi-tenancy в Kubernetes. — Знание принципов распределенных систем: CAP, Raft, quorum и consensus. — Опыт участия в архитектурных обсуждениях и принятии решений при построении PaaS/DBaaS. — Опыт работы с policy-as-code: OPA, Gatekeeper или Kyverno. — Экспертиза в observability-стеке: Prometheus, Grafana, VictoriaMetrics и Jaeger, умение строить метрики и алерты для Kubernetes и Data Services. — Умение находить корневые причины инцидентов, связанных с latency, IO bottlenecks, сетью и потреблением памяти. — Опыт работы с Helm и проектирования production-чартов. Условия: — Полный рабочий день. — Возможна удалённая работа из любого города России. — Официальное трудоустройство, полностью белая зарплата. — Медицинское страхование (ДМС) и возможность онлайн-консультаций с врачами. — Возможность выступать на конференциях и писать статьи. — Собственный учебный центр с курсами, тренингами и книгами для повышения квалификации. — Офисы в Москве, Санкт-Петербурге и Новосибирске для гибридного формата работы.

Проектировать, разрабатывать и оптимизировать высокопроизводительные серверные приложения. Реализовывать примитивы синхронизации (мьютексы, условные переменные, lock-free структуры) и алгоритмы с жесткими требованиями к latency и throughput.

Разрабатывать сценарии на Locust нагрузочного тестирования, поддержка актуальности, подготовка отчетов; Анализировать требования;

Location: San Francisco, CA or Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ Docker AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance—so developers can focus on building incredible AI agents, not gluing together infrastructure. The Gateway sits at the center of modern AI applications, offering: - A model and tool routing layer with built-in security and cost optimization - A familiar OpenAI-compatible interface and MCP server - Unified observability and policy enforcement - Auto-RAG, tool injection, session summarization, and more We’re just getting started—and we need exceptional engineers to help us build the backbone of the future of agent-based development. WHAT YOU’LL DO - Design and implement core systems powering the AI Gateway, including the model router, MCP gateway, and control plane - Build infrastructure that supports dynamic model selection/routing, auto-failover, cost-based routing, and policy enforcement - Own critical capabilities such as secure credential storage, session summarization, caching, and rate limiting - Develop APIs for developers building with OpenAI-compatible interfaces and the Model Context Protocol - Build the underlying infrastructure to support evaluation, telemetry, replay, and backtesting for agents and LLM workflows - Lead architectural decisions and mentor engineers as the team scales - Performance tuning - caching, session summarization, and rate limiting that keep the gateway fast under real production load - Contribute to roadmap planning, technical strategy, and cross-functional alignment KEY PROBLEMS YOU’LL HELP SOLVE - Building a unified abstraction over fundamentally different model and tool providers without leaking their differences into the developer experience - Making credential and identity handling for tool access both airtight and fast - Giving developers real-time and historical visibility into what their agents are doing, with policy enforcement that can't be bypassed - Keeping latency low and reliability high as traffic scales from early adopters to production fleets WHO YOU ARE Required Qualifications: - 6+ years of backend engineering experience with production-grade systems - Deep knowledge of distributed and highly scalable systems, cloud-native infrastructure, and API design - Experience building secure, high-throughput services (e.g., gateways, proxies, load balancers, policy engines) - Fluency in Go, and/or Rust (both preferred) - Familiarity with AI/ML platforms or model serving infrastructure - A strong product mindset—you're excited about building developer-facing tools - Ownership mentality with a bias for shipping, learning, and iterating - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience Bonus Qualifications: - Prior experience with OpenAI, Anthropic, or similar LLM APIs - Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI) - Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways - Understanding of OAuth2.1, secret management, and cloud IAM systems - Experience with Kubernetes, Docker, and microservices architecture WHY JOIN US? - Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software. - Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications. - Impact at scale: Your work will touch tens of thousands of developers building AI-first applications. - Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking. - Remote-first culture: Work from anywhere with a team that trusts and empowers you. Docker considers visa sponsorship on a case-by-case basis based on business needs.   Compensation & Equity United States: $160,900 – $260,700 + equity ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: New York Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. ABOUT THE ROLE: We’re looking for a Head of IT to build and own the systems that enable everyone at Modal to work effectively and securely. You’ll own our employee technology environment end-to-end, including identity and access, devices, internal systems, SaaS applications, and day-to-day IT operations. You’ll work closely with Security and Engineering to build an environment that is secure by default, easy to operate, and scales with the company. This is initially a hands-on role. You’ll build systems, automate workflows, and solve problems directly. As Modal grows, you’ll define how the IT function should scale and eventually build a team around it. WHAT YOU’LL WORK ON: Identity & Access - Own employee identity and access across internal systems and SaaS applications - Build scalable onboarding, offboarding, and access lifecycle workflows - Improve SSO, MFA, least privilege, and access management in partnership with Security Devices & Endpoints - Own the lifecycle and security of employee devices - Build and maintain device management, configuration, patching, and endpoint security - Automate provisioning and make onboarding as close to zero-touch as possible Internal Systems & Automation - Own and improve the SaaS applications and internal systems we depend on - Build integrations and automate workflows across identity, HR, finance, and other business systems - Evaluate and deploy new internal capabilities, including AI tools and integrations - Use APIs, scripting, and internal tooling to solve problems that don’t fit neatly into off-the-shelf products IT Operations - Own employee support, hardware, asset management, procurement, and relevant vendor relationships - Build reliable, maintainable processes rather than scale through manual work - Identify recurring problems and solve them at the system level Build the IT Function - Define the technical direction and operating model for IT at Modal - Establish the systems and processes we’ll need as the company grows - Determine when and where additional IT capacity is needed, and build the team over time YOU MAY BE A FIT IF: - You’ve owned IT or corporate technology in a fast-growing technology company - You have a strong understanding of identity, device management, SaaS administration, and endpoint security - You have strong technical skills and are comfortable working with APIs, scripting, automation, and system integrations - You’ve designed and automated employee lifecycle and access-management workflows - You have good security judgment and experience working closely with Security and Engineering - You can independently identify problems, make pragmatic technical decisions, and drive them through implementation - You’re comfortable being hands-on today while building the systems and team needed as the company grows

Un(e) Développeur(-euse) Expérience IA est responsable du cycle de vie complet des parcours que nos clients vivent avec l'agent IA d'Upgrade par clavardage, par téléphone et par courriel : création, optimisation, gestion des cas particuliers et augmentation du taux de résolution autonome. Création de parcours :

Key Requirements: — 3+ years of commercial experience in a relevant role. — Strong expertise in Asterisk (versions 13 and above). — Hands-on experience building and maintaining VoIP solutions for contact centers or fintech environments. — In-depth understanding of SIP and RTP protocols, including NAT and QoS. — Experience configuring and managing SIP trunks. — Experience configuring IVR workflows, agent queues, and skill-based routing, including fallback and overflow logic. — Experience with call recording, CDR, and CEL. — Strong Linux administration skills (Ubuntu/Debian) in production environments. — Practical experience securing VoIP infrastructure, including protection against brute-force attacks, Fail2Ban, firewall configuration, ACLs, and rate limiting. — Experience integrating Asterisk with external systems, including CRM, billing, antifraud solutions, and APIs. — Experience using AMI / ARI to integrate Asterisk with backend systems. — Understanding of financial systems requirements, including reliability, auditability, and logging. — Ability to quickly understand and troubleshoot complex or legacy systems. Responsibilities: — Maintain and continuously improve the company’s telephony platform. — Ensure the stable operation of support, collections, and sales communication channels. — Configure and maintain IVR menus, call queues, and routing logic in line with business processes. — Integrate the telephony platform with internal services, including CRM, backend systems, and billing. — Ensure high availability and minimize system downtime. — Monitor call quality and key performance metrics, including SLA, ASR, and ACD. — Identify and resolve latency and call-quality issues. — Optimize system performance and support infrastructure scaling. — Upgrade and improve the existing VoIP infrastructure. — Create and maintain technical documentation covering call flows, routing, and integrations. — Collaborate with cross-functional teams, including backend, support, and security.

Задачи — полный цикл НТ: разработка средств, целевые запуски, сбор и анализ метрик, фиксация ошибок и отчётность. Опыт в нагрузочном тестировании от 1 года.

Location: Stockholm ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you’ll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You’ll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You’ll own durability and cost at petabyte scale, from streaming and batch replication between origins to garbage collection over billions of objects. You’ll work across the stack, from local disk and page cache to distributed blob storage and garbage collection, and you’ll help shape what storage becomes next as we push storage closer to workloads. WHAT YOU’LL WORK ON: - Build P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicate data across multiple blob storage providers - Automate garbage collection across hundreds of petabytes of data - Deploy colocated storage clusters to datacenters to accelerate high-throughput customer workloads YOU MAY BE A FIT IF: - You have 5+ years of experience writing high-quality production code - You’ve built high-performance distributed storage or caching systems at a large scale (the more challenges you’ve worked through, the better) - You have strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - You’re willing to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVE: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte scale - Prior experience with Rust

Location: United Kingdom; Brazil; Ireland; Peru; Costa Rica; Latvia; Argentina; Romania; Cyprus; Portugal; Slovenia; South Africa; Czech Republic; Panama; Estonia; Canada; Hungary; Mexico; Poland; Spain; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The AI Infrastructure team builds and operates the production systems that power intelligent agents at scale. This team sits at the foundation of the agent platform, ensuring that model inference, orchestration, and execution layers are reliable, observable, and performant under real-world load. Working closely with the Agent Systems team and broader infrastructure partners, this group owns the core primitives that enable agents to safely operate across internal systems. The environment is high-scale and high-stakes — systems serve millions of users and must meet strict reliability, latency, and correctness standards. This is a deeply production-oriented team. Engineers here combine strong systems thinking with applied ML infrastructure experience, building in Rust and operating services where performance and failure modes matter.   THE OPPORTUNITY - Design and build the infrastructure layer powering AI agent systems in production - Develop high-performance Rust services that handle model inference, orchestration, and execution - Architect scalable systems capable of supporting millions of users and high request throughput - Build reliable ML infrastructure and MLOps patterns for model deployment, evaluation, and monitoring - Define guardrails, observability, and failure handling for agent-driven workflows - Optimize latency, throughput, and cost across inference and orchestration layers - Partner closely with the Agent Systems team to translate experimental prototypes into hardened production systems - Contribute to foundational infrastructure decisions in a high-scale, high-impact environment   WHAT YOU BRING - 5+ years of experience building and operating high-scale production systems - Strong proficiency in Rust and systems-level programming - Deep understanding of distributed systems, reliability engineering, and performance optimization - Experience operating services serving millions of users or high-throughput workloads - Familiarity with ML infrastructure, model serving, or MLOps in production environments - Experience designing observability, monitoring, and failure recovery systems - Strong collaboration skills working across infrastructure and applied engineering teams - High ownership mindset in high-stakes production environment   NICE TO HAVES - Experience building infrastructure for agent-based or LLM-powered systems - Background in high-performance networking, async systems, or low-latency architectures - Experience with container orchestration and cloud-native infrastructure - Familiarity with evaluation frameworks and model performance monitoring at scale - Experience working in fast-moving 0→1 or platform-building teams Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: United States (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote position. We are seeking candidates in US and Canada. The Opportunity: We build Tempo , the open-source distributed tracing backend behind Grafana Cloud Traces and Grafana Enterprise Traces (GET). Tempo makes it easy to search traces, generate metrics from spans, and connect tracing data with logs, metrics, and profiles across the Grafana stack. 2026 is an inflection point for Tempo. After a major architectural upgrade and the launch of TraceQL metrics, we are shifting from foundational work to product and operational excellence, and evolving Tempo from a SaaS database into a platform that powers Grafana’s next generation of observability products (App Observability, Asserts, Traces Drilldown, and AI-driven assistants). Over the next year, you will help us: Make Grafana Cloud Traces “just work” for customers by eliminating rough edges, confusing limits, and hidden failure modes. Achieve operational excellence at scale as we grow from close to 50 cells today into triple digits this year, with autoscaling, parameterized rollouts, and aggressive toil reduction. Evolve Tempo into a platform enabler: higher-density APIs, trace aggregation, TraceQL metrics math, and machine/LLM-friendly interfaces that downstream products and agents can build on. Push performance further: faster query latency at hundreds of MB/s ingestion and performant 30-day query ranges to match competitors. Prepare Tempo for an agent-driven world: larger, burstier, higher-cardinality workloads, and new categories of AI-powered workflows, such as assistant-driven triage and “why is this slow?”- style investigations. What You’ll Be Doing: As a Senior Engineer on Tempo, you will own technical direction on the hardest problems in our roadmap and raise the bar across the team. Deliver significant technical projects. Take well-scoped, multi-month initiatives from problem framing through rollout, e.g., trace aggregation APIs, Limitless Tempo, autoscaling cells and customer limits, or query engine improvements. Partner with Staff engineers and the tech lead on broader, cross-team direction. Own major components of Tempo. Contribute to and own parts of ingestion, storage, query, and metrics generation. Write and present design docs, participate in design reviews, make sound trade-offs on performance, cost, and complexity, and document the “why” for the team. Build APIs for humans and agents. Help shape the next generation of Tempo’s interfaces (structured, deterministic, discoverable) so that Act 3 products, LLM-driven assistants, and external integrators can build on Tempo reliably. Contribute to operational excellence. Own outcomes for the areas you build against concrete SLOs (P99 write latency, incident recurrence, TCO per ingested GB), and help move the team toward Zero Ops through automation, parameterized rollouts, and actionable alerts. Collaborate with Product and sibling teams. Work with PMs and with App Observability, Asserts, Drilldown, and Grafana Assistant teams to understand how Tempo gets consumed and to ship what unblocks them. Mentor and support engineers. Raise the bar through thorough code review, constructive design feedback, and pairing, especially with junior and mid-level engineers. Participate in on-call for the services you help build, and contribute to incident response and post-incident learning. Contribute to open source. Tempo is OSS. You will engage the community, review external contributions, and contribute to the project in the open. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always with strong code review and quality standards. You'll also have access to the latest frontier models from OpenAI, Anthropic, and Google. Example problems you could work on These are the kinds of projects landing in 2026: Trace aggregation and higher-density APIs: extend TraceQL metrics, design LLM-friendly response types, and make Tempo a first-class data source for Grafana’s AI assistant. Autoscaling end-to-end: customer limits and Tempo cells, with hysteresis, predictive scaling for spikes, and safe scale-down. Agent-scale ingestion and query: guardrails for bursty, high-cardinality, agent-generated workloads. Query performance: new data formats, smarter query pipelines, targeted optimizations for common Drilldown and Traces workflows, and 30-day query ranges. Rollouts and multi-cell operations: parameterized rollouts, push-button deploys, and the tooling to grow safely into triple-digit cell counts without a proportional increase in alert noise. Limits and self-service: drive customer-facing configuration and observability so escalations trend toward zero. What Makes You a Great Fit: Technical ownership. A track record of delivering complex, multi-month projects that spanned design, delivery, and operations, and of helping the teammates around you grow. Solid systems experience. Significant hands-on experience building and operating distributed data systems in production: ingestion pipelines, storage engines, query execution, or similar. Strong software craftsmanship. You write clean, robust, performant software that others can maintain, and you know when to optimize vs. when to ship. Strong Go, or a path to it. We write Tempo in Go. Solid experience in other systems languages (Rust, C, C++) translates well. Operational mindset. You’ve owned production services, carried a pager, reduced toil, and treated SLOs as a product feature, not a chore. Customer focus and pragmatism. You break complex problems into short feedback loops: analyze, design, deliver an MVP, learn, iterate. Collaboration and clear writing. You contribute through design docs, reviews, and shipped code, and you communicate clearly in a fully remote, asynchronous environment. Bonus Points For: Experience with tracing, OpenTelemetry, or large-scale observability systems. Experience designing query languages, SQL/TraceQL-like engines, or APIs intended to be consumed programmatically (by services or agents). Experience with columnar storage formats (e.g., Parquet) or purpose-built on-disk formats for analytical workloads. Experience operating multi-tenant, multi-cell SaaS infrastructure at scale on Kubernetes. Experience building for AI/LLM consumers: structured APIs, metadata/discovery endpoints, deterministic outputs, evaluation harnesses. Open-source contribution or maintainership, and comfort engaging a community in the open. Experience as an on-call user of Grafana, Prometheus, Loki, or Tempo in a previous role (or on a homelab). Experience in a fully remote, globally distributed team. How we work We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our senior engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. In US, the OTE (On-Target Earnings)/Base compensation range for this role is USD $154,445 - $185.334. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Canada (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote position. We are seeking candidates in US and Canada. The Opportunity: We build Tempo , the open-source distributed tracing backend behind Grafana Cloud Traces and Grafana Enterprise Traces (GET). Tempo makes it easy to search traces, generate metrics from spans, and connect tracing data with logs, metrics, and profiles across the Grafana stack. 2026 is an inflection point for Tempo. After a major architectural upgrade and the launch of TraceQL metrics, we are shifting from foundational work to product and operational excellence, and evolving Tempo from a SaaS database into a platform that powers Grafana’s next generation of observability products (App Observability, Asserts, Traces Drilldown, and AI-driven assistants). Over the next year, you will help us: Make Grafana Cloud Traces “just work” for customers by eliminating rough edges, confusing limits, and hidden failure modes. Achieve operational excellence at scale as we grow from close to 50 cells today into triple digits this year, with autoscaling, parameterized rollouts, and aggressive toil reduction. Evolve Tempo into a platform enabler: higher-density APIs, trace aggregation, TraceQL metrics math, and machine/LLM-friendly interfaces that downstream products and agents can build on. Push performance further: faster query latency at hundreds of MB/s ingestion and performant 30-day query ranges to match competitors. Prepare Tempo for an agent-driven world: larger, burstier, higher-cardinality workloads, and new categories of AI-powered workflows, such as assistant-driven triage and “why is this slow?”- style investigations. What You’ll Be Doing: As a Senior Engineer on Tempo, you will own technical direction on the hardest problems in our roadmap and raise the bar across the team. Deliver significant technical projects. Take well-scoped, multi-month initiatives from problem framing through rollout, e.g., trace aggregation APIs, Limitless Tempo, autoscaling cells and customer limits, or query engine improvements. Partner with Staff engineers and the tech lead on broader, cross-team direction. Own major components of Tempo. Contribute to and own parts of ingestion, storage, query, and metrics generation. Write and present design docs, participate in design reviews, make sound trade-offs on performance, cost, and complexity, and document the “why” for the team. Build APIs for humans and agents. Help shape the next generation of Tempo’s interfaces (structured, deterministic, discoverable) so that Act 3 products, LLM-driven assistants, and external integrators can build on Tempo reliably. Contribute to operational excellence. Own outcomes for the areas you build against concrete SLOs (P99 write latency, incident recurrence, TCO per ingested GB), and help move the team toward Zero Ops through automation, parameterized rollouts, and actionable alerts. Collaborate with Product and sibling teams. Work with PMs and with App Observability, Asserts, Drilldown, and Grafana Assistant teams to understand how Tempo gets consumed and to ship what unblocks them. Mentor and support engineers. Raise the bar through thorough code review, constructive design feedback, and pairing, especially with junior and mid-level engineers. Participate in on-call for the services you help build, and contribute to incident response and post-incident learning. Contribute to open source. Tempo is OSS. You will engage the community, review external contributions, and contribute to the project in the open. We invest heavily in developer productivity. You can use modern AI coding assistants as part of your daily workflow (your choice of tools, within security guidelines), backed by a company-funded usage budget so you can iterate quickly without unnecessary friction. We encourage pragmatic AI-assisted development: faster prototyping, test generation, refactors, documentation, and incident follow-ups—always with strong code review and quality standards. You'll also have access to the latest frontier models from OpenAI, Anthropic, and Google. Example problems you could work on These are the kinds of projects landing in 2026: Trace aggregation and higher-density APIs: extend TraceQL metrics, design LLM-friendly response types, and make Tempo a first-class data source for Grafana’s AI assistant. Autoscaling end-to-end: customer limits and Tempo cells, with hysteresis, predictive scaling for spikes, and safe scale-down. Agent-scale ingestion and query: guardrails for bursty, high-cardinality, agent-generated workloads. Query performance: new data formats, smarter query pipelines, targeted optimizations for common Drilldown and Traces workflows, and 30-day query ranges. Rollouts and multi-cell operations: parameterized rollouts, push-button deploys, and the tooling to grow safely into triple-digit cell counts without a proportional increase in alert noise. Limits and self-service: drive customer-facing configuration and observability so escalations trend toward zero. What Makes You a Great Fit: Technical ownership. A track record of delivering complex, multi-month projects that spanned design, delivery, and operations, and of helping the teammates around you grow. Solid systems experience. Significant hands-on experience building and operating distributed data systems in production: ingestion pipelines, storage engines, query execution, or similar. Strong software craftsmanship. You write clean, robust, performant software that others can maintain, and you know when to optimize vs. when to ship. Strong Go, or a path to it. We write Tempo in Go. Solid experience in other systems languages (Rust, C, C++) translates well. Operational mindset. You’ve owned production services, carried a pager, reduced toil, and treated SLOs as a product feature, not a chore. Customer focus and pragmatism. You break complex problems into short feedback loops: analyze, design, deliver an MVP, learn, iterate. Collaboration and clear writing. You contribute through design docs, reviews, and shipped code, and you communicate clearly in a fully remote, asynchronous environment. Bonus Points For: Experience with tracing, OpenTelemetry, or large-scale observability systems. Experience designing query languages, SQL/TraceQL-like engines, or APIs intended to be consumed programmatically (by services or agents). Experience with columnar storage formats (e.g., Parquet) or purpose-built on-disk formats for analytical workloads. Experience operating multi-tenant, multi-cell SaaS infrastructure at scale on Kubernetes. Experience building for AI/LLM consumers: structured APIs, metadata/discovery endpoints, deterministic outputs, evaluation harnesses. Open-source contribution or maintainership, and comfort engaging a community in the open. Experience as an on-call user of Grafana, Prometheus, Loki, or Tempo in a previous role (or on a homelab). Experience in a fully remote, globally distributed team. How we work We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our senior engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. In Canada, the OTE (On-Target Earnings)/Base compensation range for this role is CAD $164,490 - $197,389. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Remote - Canada What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote About the problem space AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working." Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering. Little more about the team: You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place. What you'll do You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first. Ship automated workflows end to end Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't. Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work." Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring. Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing. Build the shared substrate as you go Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance. Build on the Data team's existing infrastructure rather than standing up parallel systems. Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively. Make the company fluent Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns. Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating. Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows. Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked. Keep it safe and governable Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment. Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines. What you'll bring Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily. Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable. The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work. A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making. Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk. Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are. Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does. Nice to have SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling). Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases. Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis. Change management experience across a distributed, multi-function company. Interest in external evangelism — writing, speaking, podcasts, peer groups. Base Salary based on level of experience $310,000 — $360,000 CAD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Location: Remote - United States What We’re Building Honeycomb is a service for the near and present future, defining observability and raising expectations of what developer tools can do! We’re working with well known companies like HelloFresh, Slack, LaunchDarkly, and Vanguard and more across a range of industries. This is an exciting time in our trajectory, we’ve closed Series D funding, scaled past the 200-person mark, and were named to Forbes’ America’s Best Startups of 2022 and 2023! If you want to see what we’ve been up to, please check out these blog posts and Honeycomb.io press releases . Who We Are We come for the impact, and stay for the culture! We’re a talented, opinionated, passionate, fiercely inclusive, and responsible group of bees. We have conviction and we strive to live our values every day. We want our people to do what they truly love amongst a team of highly talented (but humble) peers. How We Work We are a fully distributed company, which means we believe it is not where you sit, but how you deliver that matters most. We invest in our people and care about how you orient to our culture and processes. At the same time we imbue a lot of trust, autonomy, and accountability from Day 1. #LI-Remote About the problem space AI has changed what's possible in go-to-market, support, and business operations. The constraint is no longer "can we build it" — it's "can we deploy it into a real workflow, prove it made things better, and keep it working." Most companies are stuck at the demo stage: a lot of clever prompting, very little that runs reliably on Tuesday morning without someone watching it. This role exists to get us past that, everywhere outside of engineering. Little more about the team: You'll sit on the Data team, which is where this work belongs. Our team already operates at the seam between the business and its systems — we partner daily with RevOps, Customer Success, Sales, and Product, and we own the data infrastructure these workflows depend on. AI-in-the-business is a data problem with a model attached, and you'll have the pipelines, the warehouse, and the domain relationships already in place. What you'll do You are a senior individual contributor. Your job is to take business workflows that are slow, manual, or inconsistent, and make them fast, automated, and measurably better — then do it again, and leave behind enough shared scaffolding that the third one is easier than the first. Ship automated workflows end to end Partner with department leaders to identify the highest-leverage workflows in their orgs, and go deep enough on how the work actually happens to know where a model helps and where it doesn't. Define success before you build: cycle time, quality, cost, risk. Instrument it. Report on it honestly, including when the answer is "this didn't work." Deliver working systems, not prototypes, with evaluation harnesses, human-in-the-loop review where the stakes call for it, and ongoing monitoring. Iterate on adoption the way a product manager would: user research, documentation, and a real plan for getting people to use the thing. Build the shared substrate as you go Establish patterns for model access, orchestration and agents, prompt and tool management, evaluation, logging, and cost control — derived from what real workflows needed, not designed in advance. Build on the Data team's existing infrastructure rather than standing up parallel systems. Co-own shared components with your counterpart in Engineering; identify dependencies early and bring them into partner roadmaps collaboratively. Make the company fluent Create templates, playbooks, and golden paths: prompt patterns, agent patterns, safety checklists, evaluation patterns. Run office hours, demos, and community-of-practice sessions that make adoption feel accessible rather than intimidating. Develop enablement material for distinct audiences — GTM, operations, leadership — from fundamentals through advanced workflows. Help people build judgment about AI: when to use it, when not to, and how to tell whether it worked. Keep it safe and governable Partner with Security, IT, and Legal on access control, data handling, vendor risk, and policy — so that employees have a clear, fast, safe path to experiment. Work with the Data team to apply our data classification standards to AI use cases: what data can be used for retrieval and context, and what audit trails are required when sensitive data flows through LLM pipelines. What you'll bring Deep experience shipping systems into real business workflows — you've owned something end to end, in production, that non-technical people depended on daily. Hands-on fluency with modern AI stacks: LLMs, retrieval, tool use and agents, evaluation, guardrails — plus the pragmatism to keep things shippable. The ability to learn someone else's job well enough to improve it. This role lives or dies on understanding how support, sales, or finance actually work. A track record of leading cross-functional initiatives without formal authority, bringing clarity, momentum, and crisp decision-making. Comfort navigating security, privacy, and compliance tradeoffs in real organizations: data classification, retention, access controls, vendor risk. Strong teaching instincts — you explain complex things simply, write clear docs, and meet people where they are. Demonstrated ability to stay current as the landscape shifts, and to change your mind in public when the evidence does. Nice to have SQL fluency and comfort in a modern data stack (dbt, a cloud warehouse, BI tooling). Experience with workflow automation or enterprise systems: case management, ticketing, CRM, knowledge bases. Familiarity with observability practices for AI systems: monitoring, quality signals, evaluation pipelines, cost and latency analysis. Change management experience across a distributed, multi-function company. Interest in external evangelism — writing, speaking, podcasts, peer groups. Base Salary based on level of experience $225,000 — $265,000 USD What you'll get when you join the Hive: A stake in our success - generous equity with employee-friendly stock program It’s not about how strong of a negotiator you are - our pay is based on transparent levels relative to experience Time to recharge with unlimited PTO A distributed-first mindset and culture (really!) Home office, co-working, and internet stipend Full benefits coverage for employees, with additional coverage available for dependents Up to 16 weeks of paid parental leave, regardless of path to parenthood Annual development allowance And much more... Please note we cannot currently sponsor or support visa transfers at this time. Additionally, in compliance with applicable law, all persons hired will be required to verify identity and eligibility to work. Phishing and Recruitment Scam Warning: We take your security seriously. Please be aware that recruitment scams are increasingly common and scammers may create email addresses or websites to impersonate Honeycomb employees. To help protect you: All communications will come from an @honeycomb.io email address We occasionally work with external recruiting agencies. These partners will use legitimate business email addresses— never personal accounts like Gmail or Yahoo . Our recruiting process will never ask you to provide financial or sensitive personal information, including but not limited to: Social security or tax identification numbers Credit card numbers Bank account information Diversity & Accommodations: We're committed to building a diverse, inclusive, and equitable workplace—where people of all backgrounds, identities, experiences, and abilities are welcomed, valued, and supported. We recognize that there is no single path to success and embrace nontraditional career journeys and diverse perspectives as key to building stronger, more innovative teams. We strive to ensure an inclusive experience throughout every stage of our hiring process and are happy to provide reasonable accommodations as needed. If you require accommodations or accessible formats at any point during our hiring process, please let your recruiter know. As an equal opportunity employer our hiring process is designed to put you at ease and help you show your best work. If there’s anything we can do to improve your experience, we’re always open to feedback. Privacy Notice: If you apply for a job at Honeycomb and your application is unsuccessful (or you withdraw from the process or decline our offer), Honeycomb will retain your information after your application for a period of time in accordance with local laws. We retain this information for various reasons, including in case we face a legal challenge in respect of a recruitment decision, to consider you for other current or future jobs at Honeycomb, and to help us better understand, analyze and improve our recruitment processes. For more information regarding our privacy practices please see the Honeycomb Privacy Notice . If you do not want us to retain your information, or want us to update it, please contact privacy@honeycomb.io . Please note, however, that we may retain some information if required by law or as necessary to protect ourselves from legal claims.

Location: New York; San Francisco Workplace: OnSite ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. ABOUT GTM ENGINEERING: GTM Engineering is responsible for the data, business logic, workflows, and agents that enable our Marketing and Sales teams to help customers get the most out of Modal. Like the infrastructure beneath the Magic Kingdom https://en.wikipedia.org/wiki/Disney_utilidor_system, much of our work happens behind the scenes. We build systems that anticipate and deliver what customers need to grow on Modal. We bring a product management, growth engineering, and data science approach to GTM, from centralizing our data platform https://deepline.com/blog/gtm-ai-nyc-chris-modal to building agents for account research https://parallel.ai/blog/case-study-modal. THE ROLE: We’re looking for a GTM Engineer to own our GTM data platform. This role combines analytics engineering with revenue operations: you’ll build the org map, people graph, and data systems that help us discover future customers and support our GTM workflows, partnering closely with our Data team on the shared foundation. WHAT YOU’LL WORK ON: - Build and maintain an org map and people graph connecting companies, labs, teams, and individuals to identify researchers, engineers, and early-stage startups, including people beyond our existing users and CRM - Own identity resolution, enrichment, and CRM schemas so affiliations, roles, and relationships stay accurate, current, and traceable to their sources - Build GTM data models in Snowflake and dbt connecting people, companies, workspaces, workloads, usage, and revenue, giving reps and agents a shared foundation for customer context - Partner with RevOps and Marketing to define and implement metrics, data models, and business rules for routing, territory assignments, compensation, pipeline reporting, and attribution - Partner with Data on usage forecasts and account signals; build reproducible reporting that reconciles actuals, forecasts, human adjustments, and credited attainment - Build reverse ETL pipelines for ad audiences, lifecycle campaigns, CRM enrichment, outbound, and event outreach, preserving engagement history and campaign eligibility - Own data quality and system health, from graph coverage and stale enrichment to failed syncs and historical reporting accuracy - Build the tooling that helps GTM Engineering ship reliably, from development environments, automated tests, and deployments to backups and shared AI agents and skills YOU MAY BE A FIT IF: - You’re fluent in SQL and proficient in Python - You already use AI coding tools and agents to build, debug, and automate your work, and help teammates do the same - You’ve built data models and production pipelines with tools like Snowflake, dbt, Modal, or Hex - You have hands-on experience with CRM architecture, integrations, and revenue or marketing operations - You understand how leads, accounts, opportunities, and revenue move through a business - You have high attention to detail and a habit of testing, documenting, and monitoring the systems you build NICE-TO-HAVE: - Experience with usage-based businesses

Location: Brazil; Peru; Sweden; Colombia; Argentina; Romania; Cyprus; Slovenia; Lithuania; South Africa; Czech Republic; Hungary; Mexico; Chile; Poland; Slovakia; Bulgaria Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. The team Founded in 2011, Kraken is one of the world’s longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The Pro team is responsible for everything to do with the trading backend services such as the matching engine, market data gateways, internal and external APIs, and various other trading services. The team is located globally and responsibilities are split into sub-teams, working with various tech stacks. Our teams code in Rust and C++ and work agile around the globe. The Opportunity - Design and implement robust Rust and C++ services and libraries that power trading, payments, and crypto experiences with a focus on reliability, performance, and user impact. - Write reusable, testable, and highly efficient code that scales across teams and supports revenue-critical systems without compromising safety or security. - Collaborate on large-scale distributed systems architecture, translating evolving product requirements into resilient, low-latency solutions. - Work alongside hundreds of experienced Rust and C++ engineers, contributing to a high-performance, product-driven engineering culture. What You Bring - 3+ years of software engineering experience - Experience building financial trading focused products - Proficient in writing network services or asynchronous code in Rust - Experience with modern C++, including performance-sensitive, low-latency systems - Have a security-first mindset during system design to ensure robustness - Demonstrate the ability to autonomously debug issues across the stack (OS, network, application) - Apply a solid understanding of distributed systems and technologies, including RPC protocols, Kafka, and Event-Driven Systems, to design scalable solutions - Collaborate effectively with product teams to gather requirements and constraints for designing appropriate systems - Take complete end-to-end ownership of systems and libraries Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice