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Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: We are looking for experienced software engineers to join our Platform organization. We build the foundational primitives that accelerate product development across Anthropic, and own infrastructure and systems that teams depend on to ship reliably and at scale - either internally or by hundreds of thousands of external global users and companies at all stages. You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You'll partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day. We have multiple teams that are currently hiring. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers with the backend product efforts where they'll have the greatest impact and growth potential. You might be a good fit if you: Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent distributed systems, cloud-native products, developer tools, or external developer facing products Have strong fundamentals in service-oriented architectures, networking, and systems design, ideally having owned both the technical vision and execution of a foundational platform system end to end Are proficient in Python, Go, Rust, or similar systems languages Have experience with cloud infrastructure (GCP, AWS, or Azure), container orchestration (Kubernetes), and/or multi-cloud networking Take full ownership of your work—from design through deployment and operations Can navigate ambiguity and make sound technical decisions independently, and have ideally operated in 0 to 1 and more mature team or company settings Take a product-focused approach to platform work and care about building solutions that are robust, scalable, and easy to use Care about building systems that other engineers love to use Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote, Global Workplace: Remote ABOUT SUPABASE Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. ABOUT THE ROLE Auth https://supabase.com/auth, written in Go https://github.com/supabase/auth (server) and with client libraries for TypeScript https://github.com/supabase/supabase-js, SSR https://github.com/supabase/ssr and for other frameworks and technologies, is one of the most popular products in the Supabase stack. We are seeking someone to help us build new and maintain existing Auth features. WHAT YOU’LL BE RESPONSIBLE FOR - Designing and implementing secure, scalable authentication features in Go and TypeScript. - Working across the stack: from server-side protocols to client-side libraries for frameworks like Next.js. - Owning the performance, reliability, and scalability of the Auth server across Supabase's infrastructure. - Contributing to the evolution of our Auth architecture, including support for OAuth, OIDC, SAML, and other protocols. - Planning and executing safe database migrations across a large fleet of Postgres instances. - Building and improving observability: metrics, tracing, alerting, and dashboards to keep the system healthy at scale. - Writing and reviewing RFCs as part of our product development process. - Collaborating with engineers across Supabase to ensure a seamless experience for developers using our tools. - Supporting the community and responding to developer feedback on GitHub, Discord, and other channels. YOU MIGHT BE A GOOD FIT IF YOU - (Required) Have 4+ years of professional experience writing and shipping Go in production. - (Required) Have 2+ years of professional experience working on an authentication system (implementing protocol support, maintenance at scale). - (Required) Have strong relational database experience (Postgres or MySQL); Postgres experience is a bonus. - Have strong knowledge of TypeScript in addition to Go (languages used daily). - Have strong knowledge of web technology fundamentals (cookies, sessions, JWT, HTTP, browser APIs). - Have good knowledge of and deep interest in authentication security (passwords, protocols such as OAuth, OIDC or SAML, cryptography fundamentals such as hash functions, signatures and ciphers). - Have experience working with multiple web frameworks like Next.js (or other SSR alternative in the JavaScript space) and traditional web frameworks like Ruby on Rails, Django, Laravel or equivalent (in any language). - Have good technical writing skills (RFC process is an important part of making changes to the Auth product). - Have hands-on experience building and operating services at significant scale. - Have deep understanding of systems-level concerns: memory management, concurrency patterns, and compute resource optimization in Go. - Have experience with Kubernetes and AWS (or comparable cloud platform) in a production setting. - Have solid grasp of observability practices — metrics, distributed tracing, structured logging, and alerting (e.g., Prometheus, Grafana, OpenTelemetry). - Have experience managing database schema migrations safely at scale. WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

Location: Europe Workplace: Remote Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. We’re looking for a Principal Engineer to join the ML Platform team at Synthesia. Our team builds and operates the systems that allow researchers and product teams to train, serve, and deploy generative models reliably and efficiently. This includes research infrastructure, production serving systems, internal tooling, and the platform interfaces that connect them. A growing part of our mission is making these systems more automation-friendly and agent-oriented, so that workflows can increasingly be operated through reliable tooling rather than manual effort. We’re looking for a strong generalist with a systems mindset: - someone who is comfortable working across infrastructure, backend systems, and tooling, and who has seen ML systems in practice. - this is not a pure ML Engineer role. We’re especially interested in people who think deeply about reliability, scalability, performance, and resource efficiency in complex production environments. This is a hands-on IC role with significant ownership. You’ll help shape how our ML platform evolves as we scale the number of models, workloads, tools and teams relying on it. WHAT YOU’LL DO - Design and improve the platform systems that support model training, evaluation, and production serving. - Build infrastructure and tooling that make ML workloads more reliable, scalable, and cost-efficient. - Develop internal tools and workflows that are easy to operate both by humans and by agents. - Work on the architecture behind how models are deployed, served, and operated across research and product environments. - Improve how we schedule, monitor, and debug workloads running on GPUs and cloud infrastructure. - Develop internal tools and abstractions and agentic systems that reduce operational overhead for researchers and engineers. - Drive improvements across observability, automation, reliability, and developer experience. - Collaborate closely with researchers and product engineers to understand pain points and turn them into robust platform capabilities. - Contribute to technical direction and make pragmatic architectural tradeoffs as the platform grows. YOU’LL THRIVE IN THIS ROLE IF YOU HAVE - Strong experience building or operating production systems with a focus on reliability, scalability, and maintainability. - A systems mindset: you naturally think in terms of bottlenecks, failure modes, interfaces, resource usage, and long-term operability. - Solid hands-on experience with cloud infrastructure, Linux, and infrastructure automation. - Experience with Kubernetes and operating distributed workloads in production. - Strong coding skills, ideally in Python or similar languages used for backend systems and tooling. - Strong judgment around where automation adds leverage, and where human control and reliability matter most. - Experience building internal platforms, developer tooling, or infrastructure abstractions used by other engineers. - Comfort working in ambiguous environments and taking ownership of open-ended technical problems. - A pragmatic approach: you care about solving the right problem well, not over-engineering. PARTICULARLY RELEVANT EXPERIENCE - Operating ML infrastructure or model serving systems in production. - Supporting research or data-intensive workloads. - Working with GPU-based systems or other performance-sensitive infrastructure. - Experience with observability and debugging in distributed systems. - Familiarity with Terraform, Datadog, GitHub Actions, or similar tools. BONUS POINTS FOR - Experience building agentic or LLM-powered internal tools. - Experience with workflow orchestration systems such as Temporal. - Experience working at the boundary between research and production engineering. - Familiarity with performance optimization, scheduling, or resource allocation problems. - Experience building lightweight product or developer-facing tools.

Задачи: — Разрабатывать iOS-приложение с нуля (greenfield) — Участвовать в проектировании архитектуры — Интегрироваться с backend (REST API) — Писать чистый, поддерживаемый код — Делать code review и unit-тесты — Работать над производительностью и UX Требования к кандидату: — Имеешь 2+ года коммерческого опыта в iOS — Уверенно пишешь на Swift — Понимаешь MVC / MVVM, Clean Architecture — Работал с асинхронностью и многопоточностью — Умеешь проектировать расширяемый код — Работал с REST API Будет большим плюсом: — Опыт с iOS Accessibility (VoiceOver, UIAccessibility и др.) — Понимание accessibility tree и работы фокуса — Опыт с инструментами тестирования доступности Условия: — Удаленная работа из РФ

Location: Espoo; Berlin Workplace: Hybrid - Title: Staff Platform Engineer - Department: Platform & Release Engineering - Location: Espoo, Finland / Berlin, Germany - Reports to: Infrastructure Engineering Lead - Employment type: Permanent - Workplace model: Hybrid - Employment is subject to applicable security screening (incl. SUPO) WHY THIS ROLE MATTERS: As a Senior / Staff Platform Engineer, you’ll own and evolve the foundations that all services rely on, leading the design and operation of a secure, scalable Kubernetes platform across cloud and on-prem environments so product teams can ship faster with less friction and stronger reliability at scale. WHO WE ARE ICEYE delivers space-based intelligence, surveillance, and reconnaissance (ISR) capabilities to governments and allied nations. This includes sovereign and turnkey ISR missions leveraging ICEYE’s world-leading synthetic aperture radar (SAR) satellite technology, as well as access to data from the world’s largest SAR satellite constellation. These capabilities enable partners to detect and respond to critical changes anywhere on Earth with unprecedented speed and accuracy, day or night and in any weather, supported by ultra high-resolution imagery and high-frequency revisits. As a trusted partner for defense, intelligence, security, and maritime domain awareness, ICEYE’s near real-time data creates a tactical advantage for mission-critical operations. Designed for dual use, the platform also serves civil protection and commercial users for natural-catastrophe intelligence, insurance, maritime monitoring including oil-spill detection, and finance, contributing to global security and community resilience. ICEYE is headquartered in Finland and operates globally across Europe, North America, the Middle East, and Asia-Pacific. We have more than 900 employees, united by a shared vision: improving life on Earth by becoming the global source of truth in Earth Observation. YOUR DAY-TO-DAY RESPONSIBILITIES - Design, operate, and continuously improve a secure, scalable, and resilient Kubernetes platform across cloud and on-prem environments - Build and maintain standardized platform capabilities such as ingress, service mesh, secrets management, and lifecycle automation - Develop reusable infrastructure patterns and Terraform modules for AWS and on-prem platforms to enable fast, auditable provisioning - Strengthen observability through clear metrics, logs, traces, dashboards, and actionable alerting that support effective operational decisions - Reduce platform friction for product teams by providing architectural guidance, platform standards, and hands-on enablement - Automate platform lifecycle management including bootstrap, upgrades, scaling, and operational maintenance to reduce manual effort and risk - Drive technical direction and sound architectural choices across platform engineering with pragmatic trade-offs between reliability, security, speed, and maintainability - Help raise engineering maturity by mentoring others and shaping shared engineering standards across teams WHAT WE’RE LOOKING FOR MUST HAVES: - 8+ years of experience in Platform Engineering, SRE, DevOps, or infrastructure roles operating production-critical services at scale - Deep hands-on expertise with Kubernetes, including cluster architecture, upgrades, control plane operations, networking, ingress, storage, security, and lifecycle management - Strong understanding of AWS fundamentals, including networking, IAM, compute, storage, and security patterns - Strong experience with Terraform and infrastructure as code, including reusable modules, abstractions, and scalable provisioning patterns - Strong practical observability experience, including SLO and SLI design, instrumentation, dashboarding, alert strategy, and production performance analysis - Proficiency in at least one backend language such as Python or Go for automation, tooling, and internal platform capabilities - Experience providing technical leadership through platform standards, architectural guidance, and hands-on enablement - Ability to operate effectively in complex environments and make pragmatic technical decisions across reliability, security, speed, and maintainability NICE TO HAVES: - Experience with Rancher, Istio, External Secrets, Vault, and software supply-chain hardening practices - Experience operating Kubernetes in restricted, disconnected, or air-gapped environments - Experience with hybrid platforms spanning AWS and on-prem environments such as vSphere or VxRail APPLICATION PROCESS - Talent Attraction Introduction - Hiring Manager Alignment - Task Assignment - Technical Interview - Director Interview WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the why behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. OUR COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us and we will do our best to help. Apply now to start your ICEYE journey and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.

Location: Switzerland Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. - Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. Location & Employment - Location: remote within Switzerland - Employment type: Full-time, permanent employment - Hiring model: Employment via Employer of Record (EOR) Candidates must already have the legal right to work in Switzerland, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: UK Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. The base salary range for this full-time position is £140,000 – £200,000. In addition to base pay, total compensation includes equity and benefits. Within the range, individual pay is determined by work location, level, and additional factors, including competencies, experience, and business needs. The base pay range is subject to change and may be modified in the future. Candidates must already have the legal right to work in the United Kingdom, as visa sponsorship is not available for this role. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Serbia Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. - Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Germany Workplace: Remote About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. - Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. For candidates interested in relocating to the San Francisco Bay Area in the future, full U.S. visa and relocation support may be available, subject to business needs and applicable legal and work authorization requirements. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Remote in the United States or Canada Workplace: Remote At Sanity.io http://Sanity.io, we’re building the future of AI-powered Content Operations. Our AI Content Operating System gives teams the freedom to model, create, and automate content the way their business works, accelerating digital development and supercharging content operations efficiency. Companies like SKIMS, Figma, Riot Games, Anthropic, COMPLEX, Nordstrom, and Morningbrew are using Sanity to power and automate their content operations. Your team ensures that enterprise customers are successful and happy using Sanity. This means working closely with technical leaders at our customers to align their strategic goals with implementation details; facilitating brainstorming sessions between editors, designers, and developers; and helping developers make decisions for their unique business needs.  In this role you will take ownership of your customer relationships and drive both internal and external conversations.  You'll also have the opportunity to learn more and develop expertise on the people side of technology. WHAT YOU WOULD DO: - Lead onboarding workshops that are customized to each customer’s needs and background. - Proactively develop relationships with technical and product stakeholders at our customers. - Meet regularly with technical customers to demonstrate how new features work for the customer’s specific needs, answer their questions, and help them plan their Sanity implementation. - Work with account managers to develop expansion opportunities at existing customers - Support the new account sales cycle through technical workshops and proof of concept development - Create and share examples to help customers understand concepts and implement more quickly - Develop and maintain guides and learning modules to address common topics - Develop and maintain plugins for common integrations and implementation patterns - Represent clients’ requests and requirements to the internal product team - Work with Support Engineering to work through customer challenges and unblock specific scenarios - Support marketing and product research teams to connect  with relevant customers and planning events and webinars ABOUT YOU: - Based in: Remote in the United States or Canada - 3-5 years of experience in a software development role - Advanced experience with at least one of the following frameworks: React, Vue, Angular, Astro - Familiar with backend architecture and SaaS platform integrations - Experience with one of the following: - Implementing headless CMS - Implementing headless ecommerce - As a Solution Engineer or Solution Architect at a developer-focused SaaS - Outstanding communication skills, both verbally and in writing - Proven experience developing solutions with customers - Problem solving skills with a result oriented mindset - Exceptional organizational and time management skills - Structured with a strong attention to details - Bonus: experience in a B2B customer-facing role, such as consulting or account management - Bonus: you have used Sanity in production WHAT WE CAN OFFER: - A highly-skilled, inspiring, and supportive team - Positive, flexible, and trust-based work environment that encourages long-term professional and personal growth - A global, multi-culturally diverse group of colleagues and customers - Comprehensive health plans and perks - A healthy work-life balance that accommodates individual and family needs - Competitive salary and stock options program WHO WE ARE: Sanity.io http://Sanity.io is a modern, flexible content operating system that replaces rigid legacy content management systems. One of our big differentiators is treating content as data so that it can be stored in a single source of truth, but seamlessly adapted and personalized for any channel without extra effort. Forward-thinking companies choose Sanity because they can create tailored content authoring experiences, customized workflows, and content models that reflect their business. Sanity recently raised an $85m Series C led by GP Bullhound and is also backed by leading investors like ICONIQ Growth, Threshold Ventures, Heavybit and Shopify, as well as founders of companies like Vercel, WPEngine, Twitter, Mux, Netlify and Heroku. This funding round has put Sanity in a strong position for accelerated growth in the coming years. You can only build a great company with a great culture. Sanity is a 300+ person company with highly committed and ambitious people. We are pioneers, we exist for our customers, we are hel ved, and we love type two fun! Read more about our values here! https://www.sanity.io/blog/our-sanity-values Sanity.io http://Sanity.io pledges to be an organization that reflects the globally diverse audience that our product serves. We believe that in addition to hiring the best talent, a diversity of perspectives, ideas, and cultures leads to the creation of better products and services. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, or gender identity.

Location: Mountain View, California, USA Workplace: Hybrid About Inworld Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads. Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production. We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA. Who We're Looking For A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood. Experience We Find Useful You don't need all of this. But you need enough to make a case. - Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM. - Model Acceleration. Hands-on experience with quantization, distillation, caching strategies , continuous batching, paged attention, and speculative decoding. - High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs. - Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections. - Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups. - Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production. - Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems. Who Thrives Here - You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go. - You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations. - You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem. - You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make. What Working Here Is Like We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater. We believe in the power of in-person collaboration to solve the hardest problems and foster a strong team culture. We offer relocation assistance and look forward to you joining us in our Mountain View office. The base salary range for this full-time position is $270,000 - $430,000+ bonus + equity + benefits. Inworld Jobs Privacy https://inworld.ai/jobs-privacy

Location: Poland; Ukraine; Romania; Argentina; Portugal; Colombia About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms across industries such as SaaS, MarTech, FinTech, and EdTech. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. This means you work closely with internal teams, contribute to meaningful projects, and have real opportunities for career growth. Role Type: Full-time Engagement: Independent Contractor About the Company Our client is an AI-first GTM (Go-To-Market) systems company founded by experienced revenue leaders. They build end-to-end automated revenue engines that transform market signals into qualified pipeline using AI agents, workflow automation, and scalable data infrastructure. Their stack combines tools like workflow automation platforms, enrichment systems, CRM integrations, and custom AI agent orchestration layers—serving high-growth companies scaling from $1M to $100M+ ARR. Job Summary We’re hiring a Head of Engineering, GTM Systems to lead the transition from no-code automation to Claude Code-powered AI agent architecture . This role is for a hands-on builder who has deep experience in Clay-based GTM systems and is now building scalable, production-grade systems using Claude Code and modern programming languages . You will own the infrastructure that powers revenue generation—designing intelligent systems that scale across clients and evolve with real-time signals. Key Responsibilities AI Agent Architecture & Engineering Design and build AI-powered GTM systems—from signal detection and enrichment to campaign orchestration and response handling Develop scalable backend systems using Python, JavaScript, or TypeScript Architect integrations across CRMs, APIs, data sources, and outreach platforms Build reusable agent frameworks, templates, and SDK-like components for rapid deployment Team Leadership & Engineering Culture Lead and scale a distributed team of engineers (including offshore talent) Establish best practices for version control, testing, documentation, and deployment Mentor automation-focused engineers into AI-agent and software engineering roles Own hiring, onboarding, and performance management Platform Development & Innovation Drive the shift from no-code workflows to code-first AI systems Evaluate emerging AI tools, LLM capabilities, and automation frameworks Contribute to internal AI tooling and reusable automation libraries Prototype and validate new automation opportunities quickly Systems Reliability & Performance Ensure system reliability through monitoring, logging, and error handling Optimize infrastructure for cost, performance, and scalability Build observability systems to proactively detect and resolve issues Requirements Must-Have Experience Proven experience building GTM automation systems in production (e.g., enrichment workflows, API integrations, CRM automation) Strong understanding of data pipelines, webhooks, and multi-step automation logic Hands-on coding experience in Python, JavaScript, or TypeScript Experience working with AI/LLM-powered systems (prompt design, chaining, context handling) Deep understanding of outbound sales workflows and revenue operations Experience leading or mentoring engineers or technical teams Preferred Qualifications Production-level engineering experience with scalable systems Background in agencies, consultancies, or multi-client environments Familiarity with DevOps practices (CI/CD, monitoring, cloud infrastructure) Active participation in automation, AI, or GTM engineering communities Benefits 💻 Fully Remote: Work from anywhere with international teams 🚀 Career Growth: Join companies in SaaS, MarTech, and B2B services 🤝 Peer Community: Connect with high-performing sales professionals in our network 🧭 Ongoing Support: Receive guidance from Huzzle before and after placement 💰 Tailored Compensation: Salaries vary by client and candidate preference — we’ll match you with options that fit your goals

Location: Remote About the Role We are building StartaleApp, a next-generation Web3 application that brings together a wide range of blockchain and DeFi functionality into a single user experience. The platform interacts with multiple blockchain networks, smart contracts, wallets, tokens, and on-chain protocols, creating complex flows that span frontend applications, backend services, blockchain infrastructure, and decentralized systems. As a Senior Software Development Engineer in Test (SDET) , you will own the engineering foundations of quality across the platform. Rather than simply writing automated tests, you will design and build the testing architecture, automation frameworks, developer tooling, CI/CD integrations, and AI-powered quality systems that enable the entire engineering organization to ship quickly and confidently. You will work across frontend applications, backend services, blockchain integrations, smart contracts, and DeFi functionality to ensure correctness, reliability, and security across complex real-world Web3 flows. This is a highly technical software engineering role focused on building quality systems, not performing manual testing. We are looking for engineers who enjoy building platforms, tooling, and automation that other engineers rely on every day. Key Responsibilities Quality Engineering Platform - Design, build, and evolve the company’s quality engineering platform. - Define testing architecture across unit, integration, contract, API, and end-to-end testing. - Build and maintain reusable testing frameworks, shared libraries, fixtures, and developer tooling. - Continuously improve developer experience around testing and quality engineering. AI-powered Quality Engineering - Design and implement AI-assisted quality engineering workflows throughout the software development lifecycle. - Build systems that leverage LLMs for automated test generation, test maintenance, failure analysis, root cause identification, and regression detection. - Develop internal tooling that combines traditional automation with AI to improve engineering productivity and software quality. - Continuously evaluate emerging AI technologies and integrate them into the team’s quality engineering practices. Test Automation & CI/CD - Build comprehensive automated test suites covering APIs, backend services, frontend applications, blockchain interactions, and Web3 user flows. - Integrate automated testing into CI/CD pipelines with fast feedback cycles and automated quality gates. - Optimize test execution through parallelization, intelligent test selection, caching, and infrastructure improvements. - Drive automation-first engineering practices across development teams. Web3 & DeFi Validation - Validate complex Web3 user flows involving wallets, authentication, token operations, smart contracts, and on-chain transactions. - Test interactions between frontend applications, backend services, blockchain networks, RPC providers, indexers, and smart contracts. - Validate transaction lifecycle and state transitions, including transaction submission, confirmation, failure, retries, reorgs, and delayed or inconsistent blockchain state. - Design automated regression suites covering critical Web3 and DeFi functionality. - Validate token transfers, swaps, liquidity operations, staking, lending, and other DeFi flows as applicable to the platform. - Test edge cases involving gas estimation, transaction failures, insufficient balances, slippage, network conditions, and blockchain state changes. Infrastructure, Performance & Reliability - Build and maintain containerized testing environments using Docker and modern infrastructure tooling. - Design contract, integration, and end-to-end testing strategies for distributed and blockchain-based systems. - Develop automated load, stress, endurance, and resilience testing for backend services and Web3 infrastructure. - Validate system behavior during degraded conditions, network failures, RPC failures, timeouts, blockchain congestion, transaction failures, and infrastructure outages. - Collaborate with engineering teams to improve system observability and accelerate production issue investigation. Qualifications Required Experience - 5+ years of experience in Software Development Engineer in Test (SDET), Quality Engineering, Test Automation, or Software Engineering roles. - Strong software engineering skills with JavaScript or TypeScript. - Experience designing testing architecture for complex distributed systems. - Experience building scalable automation frameworks and reusable testing libraries from scratch. - Strong experience with modern end-to-end testing frameworks such as Playwright or Cypress. - Strong experience testing APIs (REST, JSON-RPC, GraphQL, WebSocket, or similar). - Experience integrating automated testing into CI/CD pipelines. - Experience working with Docker and containerized testing environments. - Experience designing API, integration, contract, and end-to-end testing strategies. - Experience debugging distributed systems across frontend, backend, APIs, databases, and infrastructure. - Experience designing and implementing performance, load, and reliability testing. - Strong understanding of observability practices and production debugging. - Experience testing complex transactional, financial, distributed, or high-throughput systems. - Strong communication skills and the ability to collaborate effectively across engineering disciplines. Nice-to-Have - Professional experience testing Web3 applications, blockchain infrastructure, or DeFi protocols. - Strong understanding of blockchain fundamentals, smart contracts, wallets, tokens, RPCs, and on-chain transaction flows. - Experience testing DeFi functionality such as swaps, liquidity provision, staking, lending, borrowing, or other on-chain financial protocols. - Experience with blockchain testing frameworks, local networks, testnets, or smart contract development environments. - Experience designing AI-assisted testing systems or integrating LLMs into QA workflows. - Experience using AI for automated test generation, failure analysis, regression detection, code review, or test maintenance. - Experience evaluating and integrating AI tools to improve engineering productivity. - Experience with Kubernetes and cloud-native infrastructure. - Experience with observability platforms such as OpenTelemetry, Prometheus, Grafana, or Datadog.

Location: Abu Dhabi, United Arab Emirates Workplace: on-site At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking a .Net Developer to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. Dot Net Developer, will work closely with senior developers and cross-functional teams to design, develop, test, and deploy innovative software solutions. Role Description Design and develop software systems, ensuring adherence to coding standards, best practices, and design patterns. Collaborate with senior developers and stakeholders to understand project requirements and objectives. Assist in designing and implementing software solutions that meet business needs. Write clean, maintainable, and efficient code following coding standards and best practices. Participate in code reviews and contribute to continuous improvement initiatives. Debug, troubleshoot, and resolve software defects and issues. Contribute to the development of technical documentation. Stay current with emerging technologies and industry trends to enhance skills and knowledge. Collaborate with cross-functional teams, including QA, UX/UI, and product management. JOB SPECIFIC KNOWLEDGE & SKILLS: Strong experience with version control systems (Git) including branching strategies (GitFlow, feature branching), pull requests, and code reviews. Proficient in modern front-end technologies including Angular, React, TypeScript, JavaScript (ES6+), HTML5, CSS3, with a solid understanding of component-based architecture, state management, and responsive design. Hands-on experience in back-end development using frameworks such as .NET Core / Java Spring Boot / Node.js, including building scalable and maintainable server-side applications. Experience in designing, developing, and consuming RESTful APIs, with understanding of API standards, versioning, authentication (JWT/OAuth), and integration patterns. Good understanding of database design and data management, including relational databases (SQL Server, MySQL, PostgreSQL) and NoSQL databases (MongoDB, Redis), along with query optimization and basic performance tuning. Familiarity with microservices architecture, including service decomposition, inter-service communication, and API gateway patterns. Exposure to cloud platforms (Azure, AWS, or GCP) and containerized environments using Docker and Kubernetes is an advantage. Experience with CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins) for automated build, testing, and deployment. Exposure to mobile application development (iOS, Android, or hybrid frameworks like Ionic/React Native) is an added advantage. Strong understanding of software design principles and patterns (SOLID, MVC, Repository Pattern, Dependency Injection, Clean Architecture). Experience with testing frameworks such as xUnit, NUnit, and understanding of unit testing, integration testing, and test-driven development (TDD). Proficient in debugging and troubleshooting, using browser developer tools, API testing tools (Postman), and backend logging/monitoring systems. Understanding of security best practices, including input validation, authentication/authorization, data protection, and secure coding standards. Familiarity with Agile/Scrum methodologies, sprint planning, backlog grooming, and collaborative development practices. Strong analytical, problem-solving, and communication skills, with the ability to work effectively in cross-functional teams. Demonstrates continuous learning mindset, with the ability to quickly adapt to new technologies, frameworks, and evolving industry trends. QUALIFICATIONS IENCE Strong understanding of programming languages such as C#, JavaScript, Typescript. Knowledge of web development technologies, frameworks, and tools (angular/react). Familiarity with database concepts and SQL. Basic understanding of software development methodologies and principles. Strong problem-solving and analytical skills. Excellent communication and teamwork abilities. Eagerness to learn and take on new challenges.

Location: Argentina; Canada; United Kingdom; Poland; Estonia; Romania About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms across industries such as SaaS, MarTech, FinTech, and EdTech. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. This means you work closely with internal teams, contribute to meaningful projects, and have real opportunities for career growth. Role Type: Full-time Engagement: Independent Contractor About the Company Our client is an AI-first GTM (Go-To-Market) systems company founded by experienced revenue leaders. They build end-to-end automated revenue engines that transform market signals into qualified pipeline using AI agents, workflow automation, and scalable data infrastructure. Their stack combines tools like workflow automation platforms, enrichment systems, CRM integrations, and custom AI agent orchestration layers—serving high-growth companies scaling from $1M to $100M+ ARR. Job Summary We are hiring a Head of Engineering, GTM Systems to lead the transition from no-code automation to AI-agent-driven, code-first infrastructure . This role is ideal for a builder who started in automation (e.g., workflow tools, enrichment pipelines, API integrations) and is now evolving into full-scale engineering—designing scalable systems, writing production code, and leading technical teams. You will own the architecture powering revenue operations, build intelligent agent systems, and lead a team of engineers delivering high-impact GTM infrastructure across multiple client environments. Key Responsibilities AI Agent Architecture & Engineering Design and build AI-powered GTM systems—from signal detection and enrichment to campaign orchestration and response handling Develop scalable backend systems using Python, JavaScript, or TypeScript Architect integrations across CRMs, APIs, data sources, and outreach platforms Build reusable agent frameworks, templates, and SDK-like components for rapid deployment Team Leadership & Engineering Culture Lead and scale a distributed team of engineers (including offshore talent) Establish best practices for version control, testing, documentation, and deployment Mentor automation-focused engineers into AI-agent and software engineering roles Own hiring, onboarding, and performance management Platform Development & Innovation Drive the shift from no-code workflows to code-first AI systems Evaluate emerging AI tools, LLM capabilities, and automation frameworks Contribute to internal AI tooling and reusable automation libraries Prototype and validate new automation opportunities quickly Systems Reliability & Performance Ensure system reliability through monitoring, logging, and error handling Optimize infrastructure for cost, performance, and scalability Build observability systems to proactively detect and resolve issues Requirements Must-Have Experience Proven experience building GTM automation systems in production (e.g., enrichment workflows, API integrations, CRM automation) Strong understanding of data pipelines, webhooks, and multi-step automation logic Hands-on coding experience in Python, JavaScript, or TypeScript Experience working with AI/LLM-powered systems (prompt design, chaining, context handling) Deep understanding of outbound sales workflows and revenue operations Experience leading or mentoring engineers or technical teams Preferred Qualifications Production-level engineering experience with scalable systems Background in agencies, consultancies, or multi-client environments Familiarity with DevOps practices (CI/CD, monitoring, cloud infrastructure) Active participation in automation, AI, or GTM engineering communities Benefits 💻 Fully Remote: Work from anywhere with international teams 🚀 Career Growth: Join companies in SaaS, MarTech, and B2B services 🤝 Peer Community: Connect with high-performing sales professionals in our network 🧭 Ongoing Support: Receive guidance from Huzzle before and after placement 💰 Tailored Compensation: Salaries vary by client and candidate preference — we’ll match you with options that fit your goals

Location: 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. _______________________________________________________________________ THE ROLE Docker is shipping a wave of new products this year, and we’re investing heavily in the platform underneath all of it. That platform supports hundreds of engineers and carries high-scale production traffic every day — and it has grown faster than its foundations. This year is about closing that gap. Right now, too much of that work leans on a handful of experts unblocking the same provisioning and operational workflows by hand. The top priority for this role is turning that into paved roads: self-service systems with clear ownership, safe defaults, strong guardrails, and adoption we can measure — a platform teams trust enough to stop thinking about, so they can focus on their products instead of ours. The concrete goal is on this year’s roadmap: spinning up a new region or application environment should take hours, not days. Getting there means building real multi-region, cross-account networking and a continuous-deployment flow teams can trust, then a self-service layer on top. We’re the container company building our own internal platform, so the bar for the easy path also being the safe path is high. You’d join a team of four, growing to seven this year — this is one of those hires. We’re looking for a senior engineer who can own significant parts of this platform end to end, drive projects to real production adoption, and raise how the whole team builds. _______________________________________________________________________ RESPONSIBILITIES This is a senior, deeply hands-on role. You’ll own significant components, drive projects from design through production adoption, and shape the platform’s technical direction while helping teammates grow. Concretely, you will: - Turn ambiguous infrastructure problems into clear designs and working systems — contributing to RFCs and architecture reviews, and driving your projects to done. - Build self-service capabilities and platform APIs (primarily in Go) for onboarding, provisioning, deployment, observability defaults, and day-2 operations — with contracts and docs teams actually use. - Apply and help shape delivery standards with Terraform, GitOps on Argo CD, progressive rollout, and strong testing — including the continuous-deployment flow we’re missing today. - Strengthen the multi-tenant EKS foundations for reliability, security, scale, and cost: Envoy Gateway ingress, traffic routing, and multi-region, cross-account connectivity. - Improve SLOs, alerting, and incident follow-up on Grafana Cloud so production gets safer and less dependent on heroics. We measure this work by outcomes the consuming teams feel: how fast they can provision and ship, how much they can do without us, and how reliably it all runs. AI-ASSISTED OPERATIONS We’re investing in AI-assisted and agentic workflows to cut operational toil, and we care that they stay safe, auditable, and human-reviewed. You’ll help shape where they earn their place and where they don’t. Early targets: - Alert enrichment and incident context-gathering: assembling the relevant signals, history, and runbook so the on-call engineer starts with context instead of a blank page. - Runbook-assisted diagnosis and remediation recommendations, with a human in the loop on anything that changes production. - Onboarding and readiness assistants that answer the questions our experts answer today. If you’ve built operational automation and have a healthy skepticism about where automation belongs, this is a place to put both to work. ON-CALL Operational ownership is part of the job. You’ll join the rotation after onboarding and shadowing, and help improve on-call itself: better alerts, stronger runbooks, less toil, and blameless postmortems aimed at prevention. _______________________________________________________________________ QUALIFICATIONS - 6+ years of hands-on software engineering in backend, infrastructure, or platform engineering, though we weight real depth and impact more heavily than exact tenure. - Strong software engineering in Go or a similar language: design, testing, debugging, review, and long-term maintainability. - A track record of building, shipping, and operating cloud services or infrastructure in production. - Deep expertise in at least one of Kubernetes, networking, cloud platforms, reliability engineering, or developer platforms — plus solid Linux and production-ops fundamentals. - Experience shaping technical direction and working effectively across teams. - Clear written and verbal communication in a remote environment (RFCs, design docs, incident writeups). - Bachelor’s in CS/Engineering or equivalent practical experience. Nice to have: EKS and ingress/CNI/service-mesh experience; observability with OpenTelemetry/Prometheus/Grafana; CI/CD and progressive delivery (GitHub Actions, Argo CD, canaries); driving migrations or adoption programs across teams. You don’t need every item here. We value strong systems judgment, real depth in at least one area, and curiosity across the rest. _______________________________________________________________________ WHAT TO EXPECT First 30 days - Build context, meet partner teams, ship your first change, and shadow on-call. First 90 days - Own a meaningful platform component or project with a clear plan and metrics, and take an improvement from design to production. One-year outlook - Own a significant part of the platform and become a go-to for it — contributing to a major cross-team initiative (for example, self-service provisioning of new regions and environments, or the multi-region networking and CD foundations behind it) and establishing durable patterns your team relies on. Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________ COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $160,900 – $260,700 base ______________________________________________________________________ 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: Strava SF Workplace: Hybrid ABOUT STRAVA Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. We are looking for a Machine Learning Engineer to join the growing AI and Machine Learning team at Strava. This team is responsible for sophisticated machine learning models and systems which provide value to Strava athletes including personalization, recommendations, search, and trust and safety. The team also maintains the ML platform and infrastructure that enables our team to iterate on models quickly and deploy them reliably at scale. This is an important role in the ML team and across Product teams designing, roadmapping, and implementing innovative machine learning algorithms. We value full stack ML engineers who are able to work on all parts of an ML pipeline from model building, evaluation, optimizing performance, and ensuring the scalability and reliability of these production models. We also seek those who can improve the systems and tools behind the ML pipeline to further empower the team. We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco Office — three days per week. WHAT YOU’LL DO: - Build for a Well Loved Consumer Product: Work at the intersection of AI and fitness to launch and optimize product experiences that will be used by tens of millions of active people worldwide - Own End to End AI Systems: Drive key projects powered by ML on the Strava platform end-to-end, from initial model prototyping to shipping production code to scaling and optimizing inference and deployment - Shape AI at Strava: Be a strong voice on a highly collaborative team with a range of experience levels. Work across teams to deploy ML solutions in multiple surfaces and build out our technical ML capabilities. - Innovate in AI for Fitness: Design and develop novel models and methodologies to take on novel problems that improve athlete experience, including recommendation systems, activity prediction, and personalized insights. - Build from a rich dataset: Explore and use Strava’s extensive unique fitness and geo datasets from millions of users to extract actionable insights, inform product decisions, and optimize existing features YOU WILL BE SUCCESSFUL HERE BY: - Driving innovation with Product in mind: Stay up-to-date with the latest research in machine learning, AI, and related fields. Experiment, advocate and get buy-in for innovative techniques to improve existing products or explore new features that result in step function changes to how we build AI at Strava. - Leading as an Owner: Owning your work end-to-end and being accountable for the outcomes in the projects you drive and landing impact for the business. Ensure the end-to-end system delivers as expected through collaboration with partners. - Analyzing the Data: Work closely with product managers, data scientists, and engineers to find opportunities for applying machine learning to drive business impact and enhance Strava’s features and measure impact. - Collaborating in and across teams: Build relationships, advocate, and communicate with cross-functional partners and product verticals to identify opportunities and bring your technical vision to life. - Raising the ML standard: Help work towards best practices for model development, deployment, and maintenance. - Being passionate about the work you are doing and contributing positively to Strava’s inclusive and collaborative team culture and values WHAT YOU’LL BRING TO THE TEAM: - Have worked on numerous machine learning problems and broken them down into incremental tasks. - Have demonstrated solid interpersonal and communication skills, and collaborative approach to drive business impact across teams. - Have experience building, shipping, and supporting ML models in production at scale. - Have experience with exploratory data analysis and model prototyping, using languages such as Python or R and tools like Scikit learn, Pandas, Numpy, Pytorch, Tensorflow, and Sagemaker. - Have built and worked on data pipelines using large scale data technologies (like Spark, Hadoop, EMR, SQL, and Snowflake). - Are experienced and interested in production ML model operational excellence and best practices, like automated model retraining, performance monitoring, feature logging, and A/B testing. - Have built backend production services on cloud environments like AWS, using languages like (but not limited to) Python, Ruby, Java, Scala, and Go. For information on benefits, please click here. https://docs.google.com/document/d/e/2PACX-1vTkFMPz3eCjd0FgQ28VWnK4d2BEnzGyaSFGwATR-dQdBb9HxZgay6kboqnT0-V-qaBDzSvYIzI76vT5/pub WHY JOIN US? Movement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals. Our global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact. When you join Strava, you’re not just joining a company—you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together. Strava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together. Strava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. California Consumer Protection Act Applicant Notice https://docs.google.com/document/d/e/2PACX-1vSc8y6On4NlP5s12hf4kmWe_pvenVyQ78TbtVaz_clROhj9ADQ6kY4YScglBIuY2joKFKalOReX7vP_/pub

Location: EMEA Remote Hi, I’m Paul, VP of Engineering at Customer.io . We’re looking for curious, driven Fullstack (Product) Engineers who want to own big things and delight our customers. You’ll design, build, and ship the core product experiences our customers rely on - while helping the team push boundaries on what great communication tools can do. About Customer.io Over 9,000 companies - from scrappy startups to global brands - use our platform to send billions of emails, push notifications, in-app messages, and SMS every day. Customer.io powers automated communication that people actually want to receive. We help teams send smarter, more relevant messages using real-time behavioral data. Under the hood: Go, React, Ember and AI help us ship fast and scale with confidence. What We Value Ownership You own problems end to end. You move fast, act like an owner, and thrive in ambiguity. You've led complex projects before, whether officially or not, and you're ready to do it again. Engineers with product taste You think like a user, not just an engineer. You care about frontend polish, backend performance, and everything in between. A healthy skepticism for “the way things are done” You bring rigor and creativity. Best practices matter - but never more than forward motion. What You’ll Do Build fullstack features in Go, React, and Ember that power key customer workflows Collaborate with others to turn ideas into shipped customer value Share knowledge and raise the bar through sharing your progress publicly with short videos, thoughtful writing, and mentorship Participate in an on-call rotation as required, supporting the reliability of the systems you build Help evolve our systems to scale with more customers, messages, and use cases Use AI agents to make multi-file changes by scoping the work, writing the prompt, and verifying the output What we're looking for 7+ years of experience building and scaling backend services and product-facing features Fluency in TypeScript, React (or similar), and a statically typed backend language like Go A strong care for frontend polish, backend performance, and the overall customer experience Proficiency with APIs, relational databases, and writing testable, performant code A bias for action over perfection, and pride in owning technical decisions Compensation & Benefits We believe in transparency. Starting salary for this role is $150,000 - $250,000 USD (or equivalent in local currency) depending on experience and subject to market rate adjustment. In addition to base salary, this role includes an equity grant in the form of stock options, so you share in the success you help build. We know our people are what make us great, and we’re committed to taking great care of them. Our inclusive benefits package supports your well-being and growth, including 100% coverage of medical, dental, vision, mental health, and supplemental insurance premiums for you and your family. We also offer 16 weeks paid parental leave, unlimited PTO, stipends for remote work and wellness, a professional development budget, and more. See full benefits here → Our Process No gotchas, no trick questions - just a clear, human process designed to help both of us make an informed decision. Application - We review everyone with care. Tell us why you're interested. Recruiter Call (30 mins) - Let’s chat about what you’re looking for and how we work. Hiring Manager Interview (60 mins) - Talk with one of our hiring managers about your working style and a project you've owned end-to-end, plus a short AI-assisted coding exercise. System Design Interview (60 mins) - Design a system end-to-end. We're looking for how you think, communicate tradeoffs, and drive through ambiguity. Take-Home Assignment - Complete a short, realistic task similar to what you’d work on here. Assignment Review Calls (2 x 60 mins) - Walk us through your work and discuss tradeoffs, priorities, and how you’d iterate. All final candidates will be asked to complete a background check and employment verifications as part of our pre-employment process. Customer.io recognizes the stifling impact of systemic injustice on diverse communities. We commit to using our influence to increase inclusion and equity within the tech industry. We strive to build an inclusive team culture, implement bias-free hiring practices, and develop community partnerships to expand our global impact. Zoom is the only video conference platform that we use, virtual interviews will be conducted using the video capability (i.e., not via the chat), and offers will be extended in writing on official Customer.io letterhead. Please be vigilant in all of your job search activity, and if you have any questions please contact jobs@customer.io. Join us! We believe in empathy, transparency, responsibility, and, yes, a little awkwardness. If you’re excited by what you read and want to build software that makes communication better for everyone—apply now.