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Location: Tel Aviv-Yafo, Tel Aviv District, Israel About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role We are looking for an experienced Engineering Team Lead to build and lead the FirstRead team , a new product-focused team within Aidoc’s Imaging Platform group. FirstRead, Aidoc’s report-generation initiative, is one of the company’s most important and high-potential new products. We have decided to found this team, following a highly successful product beta, in which our AI drafted thousands of full radiology reports, covering hundreds of different clinical findings with near-human accuracy. The product is evolving rapidly, and so will the team around it. With the opportunity to shape the product and its technical direction from the ground up, the FirstRead team will be accountable for the product outcome end-to-end . The team will work across the stack, using existing platform capabilities where possible, evolving them where needed, and building new services and capabilities when required. This is a role for a TL who enjoys shaping new products and turning evolving opportunities into clear technical direction. The team’s scope, architecture, priorities, and  longer-term mission will evolve as we learn. You will play a central role not only in delivering FirstRead, but also in building the team itself and shaping how product-focused teams operate within Imaging Platform . You will work closely with Product, AI teams, and other engineering teams across Imaging Platform to turn rapidly evolving product needs into working software, while balancing speed, technical quality, and long-term platform considerations. Responsibilities End-to-End Ownership: Lead the engineering effort required to make FirstRead successful, across engineering disciplines including  backend, frontend, AI infrastructure, DICOM pipelines, existing platform services, and entirely new components. Creating Clarity in a Fast-Moving Environment: Turn changing product needs and incomplete information into technical direction, priorities, and executable plans. Continuously adapt as the product evolves. Technical Leadership: Drive architecture and technical decisions across a broad technical surface. Know when to move quickly, when to invest in robust solutions, and when to involve domain experts. Cross-Team Engineering: Work closely with other TLs and engineers across Imaging Platform. Enable the team to contribute to existing services and platforms while respecting their architecture, ownership, and long-term direction. Team Building: Build the FirstRead engineering team, establish its culture and ways of working, develop engineers, and help shape its longer-term mission as a product-focused team. Delivery and Product Partnership: Partner closely with Product and other stakeholders, taking ownership of turning evolving product direction into concrete engineering execution. Engineering Excellence: Maintain strong engineering standards while operating in a fast-moving environment, balancing experimentation and delivery speed with reliability, maintainability, and scalability. Requirements Senior hands-on software engineering experience , including experience building complex systems end-to-end. Exceptional track record leading engineering teams , while remaining actively involved in technical and architectural decisions. Strong sense of urgency, with the ability to drive execution and maintain momentum in fast-paced, high-priority projects. Proven ability to lead projects in ambiguous, rapidly changing environments , where requirements and technical direction are not fully defined upfront. Broad technical experience and passion for working across different areas of the stack rather than specializing exclusively in a single domain. Strong system design and software engineering fundamentals, with experience designing and building distributed production systems. Demonstrated ability to take ownership of an outcome from early concept through implementation, production, and continued evolution . Excellent collaboration and communication skills, with demonstrated ability to work effectively across engineering teams and organizational boundaries. Strong product and business orientation, with the ability to balance technical considerations with speed, learning, and business impact. Strong leadership, mentorship, and team-building skills. Advantages Experience working in an environment with shared platforms and multiple engineering teams contributing to the same product. Experience across multiple areas such as backend, frontend, cloud infrastructure, data pipelines, or AI/ML systems. Experience with AI-powered products or production AI systems. Working at Aidoc Our Perks: Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. Amazing and healthy breakfasts and lunches prepared daily by our personal chef! Stocked up kitchen & meal card Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. Amazing culture - collaborative, transparent & fun! Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Location: Amsterdam Workplace: OnSite ABOUT US: Tebi is creating the first Connected Restaurant Management System that makes hospitality flow. In one seamless platform, Tebi embeds sales, reservations, kitchen prep, payments, and all the data that powers it, creating smooth service and intuitive insights. Founded by Arnout Schuijff, co-founder of Adyen, and backed by €50 million in funding from Index Ventures & CapitalG, Tebi is built in service of hospitality first. Thousands of restaurants, cafés, bars, and coffee shops across the Netherlands, UK, Italy, Spain, Germany, Denmark and Finland already love running on Tebi.   ABOUT THE ROLE: We’re looking for a seasoned Fullstack Mobile Engineer to help shape the core experience for thousands of restaurant teams. This is a senior role focused on building performant, polished applications across mobile platforms. You’ll lead development of cross-platform features, collaborate closely with design and product, and contribute to shared backend components when needed. You should bring a strong product mindset, care deeply about developer experience, and be excited about building better software, faster. This role is ideal for someone who has experience shipping real-world apps, and is looking to make high-impact technical decisions in a fast-moving team.   Our Tech Stack: We use Kotlin multiplatform and Jetpack Compose. Everything runs in GCP and our database it’s Postgres.   WHAT YOU WILL DO: - Work on the development of our app architecture across Android and iOS - Design and implement shared business logic and client code, as well as platform-specific UI components where needed - Work closely with designers, PMs, and other engineers to deliver intuitive, delightful product experiences - Contribute to backend services where necessary, ensuring tight integration and performance across the stack - Continuously improve build tooling, developer experience, and code quality - Play a critical role in shaping how Tebi scales across new markets, languages, and user types   WHAT YOU BRING: - 7+ years of experience in software engineering, with deep expertise in mobile engineering - Strong experience building and shipping Android apps; familiarity with iOS and multiplatform development patterns. - Strong experience with Kotlin - Comfortable owning architecture decisions and collaborating with cross-functional teams to ship features - A strong product mindset, you care about solving real problems for users, not just writing code - Great communication skills and a pragmatic approach to building scalable systems If this speaks to you we can be the right fit. Learn more about how we work from our Recipe here: https://www.tebi.com/gb/careers.   BENEFITS: - Start-up Equity - Competitive Salary - Lunch Provided in Office - Team building events - Unlimited time off Note: Interviews will start after the 14th of September.   What is Restaurant Software? Restaurants and other merchants use various software systems such as Point of Sale (POS), Reservations, Kitchen Display Systems (KDS), Payments, Inventory, Staffing, and the list goes on. These systems all need to speak to each other which they frequently don’t. It’s a mess, and we are fixing it. From buying a croissant at a cafe to having dinner with friends, it’s a €4 Trillion+ global market and a critical part of everyday life in today's economy.   How we use AI at Tebi We use AI the way our merchants use Tebi, to cut out the friction and get to what matters faster. We believe in a world where AI increases quality, efficiency and speed. At Tebi, AI isn't a policy or a checkbox, it's just part of how we work. It helps us write, analyse, build, and improve but doesn’t make the last call. If there's a smarter way to do something, we want to find it.

Location: AU: Sydney (45 Clarence St) Workplace: Hybrid The role & impact As an Engineering Manager in our Machine Learning & AI team, you'll lead a high-performing, inclusive team of engineers building and operating AI-powered experiences and capabilities across Xero. The team's work spans traditional machine learning, from predictive models and intelligent automation through to LLM-powered and agentic AI experiences that bring new ways for customers to interact with and get value from Xero. - You'll lead engineering across a broad range of technology surfaces, from customer-facing AI experiences and intelligent product workflows to the backend services, platforms and infrastructure that power them. You'll help turn research, models and emerging AI capabilities into reliable, secure and scalable production products that make a real difference for millions of small businesses. - You'll balance predictable delivery with a relentless focus on engineering quality and system health, building our maturity across MLOps, LLMOps, observability, evaluation and the operational practices needed to run AI systems in production. As AI continues to evolve, you'll also champion AI-native engineering practices and help your team adapt how we design, build, test and operate software. - Working closely with senior individual contributors, including staff and principal engineers, you'll help shape technical direction while focusing on team growth, delivery excellence and sustainable engineering practices. This is a role for someone who wants to build both the systems and the people that enable Xero to deliver AI-powered products at scale. The team & how they connect You'll join Xero's Data & AI organisation, within the AI Products division, reporting to the GM of ML Engineering. The team partners closely with Applied Science, Data Engineering, Product and other engineering teams to bring AI capabilities from research and experimentation into production. Our scope goes beyond building and serving models. We build the end-to-end engineering capabilities that bring AI to life in Xero's products, spanning traditional ML-powered automation and predictions, conversational AI assistants, LLM-powered workflows and agentic experiences. This means working across the full stack, integrating AI into customer experiences and product workflows while building the front end & backend services, platforms and infrastructure needed to make those experiences safe, reliable and scalable. It's a collaborative, evolving space where you'll help translate advances in ML and generative AI into practical customer outcomes, while building the engineering foundations to support the next generation of AI-native products. The team is currently working on - Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production. - JAX (Just Ask Xero): Powering Xero's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences. - Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks. - XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across Xero’s products and supporting reliable, reusable agentic experiences at scale. - End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work. Where and how you can work We support a flexible working model that empowers you to balance your professional and personal life. You'll have the option to work in a hybrid capacity, combining the focus of remote work with the collaboration of our office spaces and team boost days to foster connection and alignment. Here are some of the things we're looking for, for this role - You'll bring a strong track record of leading, coaching and developing engineers, building team capability and creating an environment where people can do their best work. - You have strong technical judgement across architecture, system design and engineering trade-offs, and can guide decisions across a broad and evolving technology landscape. - You've translated business goals into executable engineering plans, balancing near-term delivery with long-term technical health and maintainability. - You're experienced in delivering roadmaps predictably in fast-paced, evolving environments, navigating ambiguity and adapting as priorities and technology change. - You understand what it takes to build and operate production-grade software, from customer-facing experiences and backend services through to distributed systems, platforms and infrastructure. - You stay hands-on when it counts, comfortable writing, reviewing or debugging production code to unblock your team, support an incident or help resolve a complex technical challenge. - Experience with machine learning, generative AI or AI-powered products is a bonus rather than a requirement. You don't need to be an ML specialist, but genuine curiosity about the space and an appetite to learn how these technologies are changing software engineering will help you thrive here. Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.

Location: Europe or US About the SQL Console Team The SQL Console team operates with a great degree of autonomy inside ClickHouse, building the rich web interfaces, interactive query environments, data visualization dashboards, and dynamic AI agents that developers use daily to interact with ClickHouse Cloud. We solve extreme UI performance and scalability challenges that only a handful of tech companies in the world ever reach. We are builder-first, heavily leverage modern AI coding tools like Cursor and Claude, and give engineers end-to-end product ownership. What You Will Do - Build highly interactive React web applications, developer tools, and IDE extensions handling real-time, high-throughput data streaming. - Optimize frontend rendering performance, state management, and DOM virtualization for large-scale datasets and complex visualizations. - Write high-performance Node.js / Express services when API, data streaming, or backend optimizations are required. - Act with a founder mindset: take ambiguous product problems, architect clean solutions, and ship maintainable code with high autonomy. - Leverage modern AI development tools (Cursor, Claude, Codex) as force multipliers to ship features rapidly. What We Are Looking For - React Architecture Depth: Deep expertise in building complex, state-heavy web applications in React (Zustand, Redux, TanStack Query, or Context API). - Rendering & Data Viz Performance: Proven ability to handle high-volume data rendering using DOM virtualization (react-window), Canvas/D3.js, or memoization techniques. - Full Stack Comfort (Node.js): Strong hands-on experience writing asynchronous Node.js / Express microservices and streaming APIs. - Founder / Builder Mindset: Previous experience as a startup founder, side-project creator, or early engineer who thrives in fast-paced environments without rigid specifications. Nice to Haves - Experience building VS Code extensions, web-based IDEs, query editors (Monaco), or developer tools. - Hands-on experience with ClickHouse or columnar real-time databases. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: New York City, NY; New York City, NY | Seattle, WA; Remote-Friendly, United States; 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 Anthropic is looking for Software Engineers to join the Memory & Search team. We own how Claude remembers you and how it finds what it needs, across Claude.ai, Cowork and Claude Code. That spans the user-facing experience (what Claude remembers, how people see and edit it, how search surfaces the right conversation) and the shared infrastructure underneath it, the memory service, indexing, retrieval and vector search. Memory is one of the biggest levers on whether Claude feels like it knows you. We recently moved memory from a periodically synthesized summary to a dynamic, editable, on-demand system, and then unified it so the same memory follows you across products. Search went from a top user complaint to something people rely on to find past work. The platform is now in place, and the next phase is finding the product form factors that make memory the most compelling and sticky part of using Claude. That is why we are hiring product engineers. The team is strong on infrastructure, and we want people who have shipped user-facing products at scale, have a sharp sense for what makes a product feel good, and have built agentic systems where the model, the tools and the user interface have to work together. You will run short, demo-driven experiments on top of the memory and search stack, decide what to keep based on real usage, and help the whole team think like a product team. If you have founded a company, been an early engineer at a startup, or taken a product from zero to one, you will recognize the way we want to work. This is a trust-sensitive surface. Memory touches privacy, consent and enterprise controls, so you will work closely with product, design, privacy, legal and safeguards, and you will be expected to treat those constraints as part of good product design rather than obstacles to it. Key responsibilities Design, build and ship memory and search experiences in Claude.ai, Cowork and Claude Code, owning them end to end from the backend service through the model's tools to the user interface Run product experiments on the memory and search stack: form a hypothesis, build a demo, put it in front of real users, measure, and make a clear persevere-or-pivot call Shape how Claude uses memory and retrieval inside its agentic loop, including what the model stores, when it searches, how results are ranked and presented, and how the user stays in control Define and track the metrics that tell us whether memory is actually making Claude more useful, and build the evaluations that keep quality honest as the system evolves Improve search relevance and recall across conversations and memories, working across embeddings, hybrid retrieval and ranking as well as the interface that presents results Partner with product, design, privacy, legal and safeguards to ship features that respect user consent and enterprise requirements such as customer-managed encryption keys and data retention policies Raise the bar on product quality for the team through design reviews, code reviews and the standards you set for latency, polish and reliability Share the on-call for the systems you own Minimum qualifications Experience building and operating user-facing products used by a large number of people, including the backend services behind them Experience building agentic systems or LLM-powered products, including tool use, retrieval and prompt or context design Strong programming skills in Python and TypeScript, with experience across backend services and web front ends A track record of taking a product or feature from an idea to launch, and iterating on it based on usage data and user feedback Experience defining product metrics and running experiments to make decisions Strong product judgment: you notice when something feels off and you fix it, and you can explain why a design choice matters to users Strong written and verbal communication, with experience working closely with product managers, designers and non-engineering partners Interest in AI safety and Anthropic's mission Preferred qualifications Experience as a founder, early-stage engineer, or someone who has taken a product from zero to one Experience building search or retrieval systems: embeddings, vector search, hybrid lexical and semantic retrieval, or ranking Experience building evaluations for LLM or ML systems, or measuring the quality of retrieval and ranking Experience on consumer products with strong retention, or on personalization systems Experience shipping features that handle sensitive data or meet enterprise requirements such as customer-managed encryption keys, data residency or HIPAA Experience with latency-sensitive, performance-critical product work Experience mentoring engineers or setting technical direction for a 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: San Francisco; Seattle; New York City ABOUT THE ROLE The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. KEY RESPONSIBILITIES - Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. - Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. - Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. - Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls. - Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost. - Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety. - Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes. QUALIFICATIONS - 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation. - Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications. - Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack. - Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows. - Deep expertise in at least one of the following: - Evaluation infrastructure, benchmark design, and automated grading. - Agent harnesses, tool interfaces, and reusable skills for complex workflows. - Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows. - Model selection, routing, and inference efficiency, including context management and caching. - Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise. - Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements. - A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship. If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.

Location: San Francisco; Seattle; New York City ABOUT THE ROLE The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate. KEY RESPONSIBILITIES - Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state. - Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes. - Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability. - Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls. - Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost. - Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety. - Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes. QUALIFICATIONS - 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation. - Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications. - Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack. - Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows. - Deep expertise in at least one of the following: - Evaluation infrastructure, benchmark design, and automated grading. - Agent harnesses, tool interfaces, and reusable skills for complex workflows. - Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows. - Model selection, routing, and inference efficiency, including context management and caching. - Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise. - Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements. - A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship. If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.

Location: Prague, Czechia; Lisbon, Portugal; Madrid, Spain CloudLinux is a global remote-first company. We are driven by our principles: do the right thing, employees first, we are remote first, and we deliver high-volume, low-cost Linux infrastructure and security products that help companies to increase the efficiency of their operations. Every person on our team supports each other and does what we can to ensure we all are successful. Check out our website for more information: cloudlinux.com We are currently hiring Staff Engineers for various projects within the Imunify360 product. Imunify360 is CloudLinux's multi-layer security suite for Linux web servers: antivirus and malware cleanup, WAF, IDS/IPS, Proactive Defense, patch management (KernelCare/Patchman), and IP/domain reputation. It runs on hundreds of thousands of shared, VPS and dedicated hosting servers, under cPanel, Plesk, DirectAdmin and standalone. The engineering org is 60+ engineers in squads covering backend, core, server agent, malware research, WAF/WebShield, and Patchman. Core services are Python; agents and performance-critical paths are Go and Rust. We run on Hetzner and our own bare metal. Check out our website for more information: https://imunify360.com/ Role Mission & Scope Most complex technical challenges in Imunify360 go beyond individual squads. A single detection change can impact the scanner, agent, UI, reputation backend, and release process. While squad leads own delivery within their teams, the Staff Engineer ensures technical alignment across the product. As a Staff Engineer, you'll be a hands-on technical leader working across the entire product , focusing on the most critical and high-impact challenges as priorities evolve. You'll drive technical decisions, improve architecture, establish engineering standards, and help teams build sustainable solutions. This is an individual contributor role , without direct people management responsibilities. You'll remain actively involved in development, spending approximately 30–50% of your time writing production code , rather than focusing solely on architectural design. While deep expertise in a particular area is valued, this role requires the flexibility to work across different components, collaborate with multiple squads, and tackle challenges wherever your expertise can make the greatest impact. What you will own Architecture and technical direction Own the end-to-end architecture of Imunify360 as a product: agent ↔ server ↔ cloud backends, data flows, and the contracts between them. Write and drive ADRs and RFCs for cross-squad changes. Run the Wed/Fri architecture sync together with the Technical Director. Keep a living tech-debt and risk register (security / compliance / uptime) with owners and dates, and get the top items funded on the roadmap. Hard cross-cutting problems (examples of what lands on your desk) Agent resource footprint on dense shared hosts: CPU, memory and I/O budgets for scanning, file monitoring (inotify/fanotify) and WAF, measured on real kernels, not benchmarks from elsewhere. Detection pipeline quality: false positive / false negative rates, signature and ML model rollout with staged gates and rollback. Upgrade and release safety across a large, heterogeneous fleet (CentOS/AlmaLinux/CloudLinux/Ubuntu, multiple control panels, old kernels). Backend scale and cost of reputation, ThreatIntel and telemetry services. Migrating hot paths from Python to Go/Rust where the data shows it pays off, and saying no where it doesn't. Engineering standards Set the bar for design reviews, code review, testing strategy, observability (Prometheus/Grafana/Sentry) and secure SDLC (OWASP ASVS, CIS Benchmarks as relevant). Lead or co-lead SEV1/SEV2 incidents when the cause is unclear or cross-squad; make sure the blameless post-mortem ships within 24 h and its actions get closed. Drive the AI-augmented SDLC in practice: show what good agentic coding looks like (prompt specificity, context provision, review quality, tool boundaries) on real changes, not slides. People multiplier (no direct reports) Mentor senior engineers and squad leads toward staff-level scope. Act as the technical bar-raiser in hiring loops for senior and lead roles. Be the engineering voice in product and sales discussions: estimates, feasibility, and no dated customer commitment without a written squad-lead estimate. Key Milestones 30 days: Shipped at least one non-trivial change to production. Can explain the full request path from agent to backend. Has a personal list of top 10 technical risks. 90 days: Owns one cross-squad initiative with an approved ADR, a measured baseline, and a staged rollout plan. Published risk register reviewed in arch sync. 6 months: That initiative is in production with before/after metrics. At least one engineering standard (e.g. release gating, agent perf budget, design review template) is adopted by 3+ squads. 12 months: Recognized by squad leads as the default escalation point for cross-cutting technical decisions. At least one senior engineer grown into broader scope with your mentorship. Requirements Must have 10+ years building and operating production software, with 3+ years in a Staff/Principal/Tech Lead scope spanning several teams. Strong production experience in Python and at least one of Go or Rust . Deep Linux internals : processes, filesystems, networking, kernel interfaces (inotify/fanotify, eBPF or similar), packaging (RPM/DEB), systemd. Track record of designing and running distributed systems at scale: async backends, queues, databases, caching, failure modes. You have owned systems that run on customer machines (agents, daemons, on-prem software) and know what upgrade safety, backward compatibility and resource budgets mean there. Security mindset: threat modeling, secure coding, handling of untrusted input (files, HTTP traffic, user content). Writes clear, short technical documents and drives decisions in async, remote teams across time zones. Uses AI coding tools (Cursor, Claude, MCP-based tooling) daily and can judge their output critically. Nice to have Experience in server security: AV/malware detection, WAF (ModSecurity/Coraza), IDS/IPS, rootkit detection, CVE/patch management. Experience with WordPress and Node.JS web application hosting at scale ML in production for classification/detection, including evaluation and safe model rollout. Observability at scale: Prometheus, Grafana, Sentry, ClickHouse or similar. CI/CD ownership: GitLab CI, Jenkins, build systems for multi-distro packaging. Open-source contributions in security or systems tooling. Benefits What's in it for you? Stay hands-on technically while owning complex, high-impact engineering work. Work on challenging Linux, automation, and cybersecurity problems across mature and newer products. Influence technical direction and make meaningful architectural decisions. Work independently with a high level of ownership and autonomy. Fully remote work with flexible working hours. 24 paid vacation days, 10 national holidays, and unlimited sick leave. Private medical insurance compensation. Co-working and gym/sports reimbursement. Education budget. Opportunity to receive a reward for innovative ideas that the company can patent. By applying for this position, you consent to the processing of your personal data as described in our Privacy Policy ( https://cloudlinux.com/candidate-privacy-notice ), which provides detailed information on how we maintain and handle your data.

Ручное тестирование frontend-backend архитектуры; Создание и поддержание документации по тестированию, тест-кейсов и чек-листов;

Задачи: — функциональное тестирование backend сервисов и UI и написание и поддержка тестовой документации (чек-листы, тест-кейсы, баг-репорты, инструкции) — подготовка тестовых данных для тестирования / проведения ПСИ, участие в релизах, проведение регрессионного тестирования и в проведении сценариев приемо-сдаточных испытаний (ПСИ) — участие в работе с обращениями от пользователей и анализ информации в БД и логах сервисов — построение и поддержка eval-набора (golden set) и регрессионного контроля качества при смене моделей, промптов и версий приложения — автоматизированная оценка качества генерации (LLM-as-judge, метрики типа Ragas) при релизах — тестирование RAG: качество поиска релевантного контекста, корректность источников, поведение при неполной / противоречивой информации — тестирование агентных сценариев: многошаговые цепочки, вызовы инструментов (MCP), повторные попытки, эскалация к человеку — участие в мониторинге качества в проде и настройке обратной связи от пользователей. Требования: — опыт работы в тестировании от 3 лет — понимание HTTP, кодов ответов, авторизации — опыт тестирования API (REST/JSON) для проверки интеграций и бизнес-логики, микросервисного взаимодействия — опыт тестирования запросов с помощью Postman/Insomnia/Swagger — опыт работы с форматами данных: JSON, YAML, XML, HTML — знание SQL, умение написать SQL запрос средней сложности — базовый опыт работы с системами сбора и визуализации метрик, работа с логами (Prometheus, Grafana) и понимание CI/CD и участия QA в пайплайнах доставки — понимание принципов работы LLM и их ограничений: недетерминированность вывода, галлюцинации, методы оценки качества генеративных моделей и опыт построения eval-наборов (golden set) и оценки качества LLM — желательно — LLM-as-judge, Ragas. Будет плюсом: — понимание RAG и методов оценки качества retrieval: релевантность контекста, корректность источников — опыт тестирования агентных систем: многошаговые агенты, tool calling — опыт работы с Python для автоматизации оценки (pytest) — понимание метрик качества AI-продукта и мониторинга качества в проде — опыт работы с Kafka — опыт работы с векторными / графовыми БД (например, Qdrant) Условия: — гибридный формат работы из офиса в г. — Москва — годовой бонус и ежегодный пересмотр — ДМС с первого дня + стоматологию и льготное страхование для семьи — корпоративный университет Сбера, внутреннюю образовательную платформу, участие в IT-конференциях — офис на Ленинском проспекте с зонами отдыха и спортзалом — льготную ипотеку в Сбере, корпоративную пенсионную программу, подписку СберПрайм с возможностью совместного использования на трёх близких, скидки от партнеров и сервисов группы компаний.

Тестированием Frontend и Backend частей облачных сервисов в рамках задач продуктовых команд; Автоматизацией процесса тестирования;

развивать и сопровождать код подрядчика для управления автопарком роботов; выполнять задачи в рамках backend (Python/Django) и frontend (React/TypeScript);

• Работа с backend-частью бизнес-критичных... • Опыт коммерческой разработки на PHP от 6 лет.

As the Engineering Manager for the AirCover Insurance Platform, you will lead the system that lets Airbnb launch, price, enroll and service insurance products in new regions, and that lets the business test what drives Hosts and guests to be covered. Depth in backend platforms, with experience in distributed systems and high-availability services.

-Выполнение продуктовых задач в поставленные сроки. -Вёрстка web-страниц на HTML, CSS.

-создавать новые автоматические тесты на Java (для backend - Rest assured, Kafka, gRPC). -проводить анализ требований и результатов авто-тестов.

Location: Dhahran, Saudi Arabia; Riyadh, Saudi Arabia; Lusail, Qatar; Dubai, United Arab Emirates We are seeking an experienced Lead Digital Solutions Analyst to support advanced AI technology initiatives and contribute to the development of next-generation AI solutions. The successful candidate will work on AI modules, scalable data pipelines, backend infrastructure, and real-time data processing systems, supporting the development of Large Language Models (LLMs), Large Time-Series Models, and Large Vision Models. Key Responsibilities Develop and implement AI modules, pipelines, solutions, and services for advanced AI technologies. Design and develop scalable backend infrastructure to support real-time data ingestion, AI model inference, and user access. Build real-time data processing components using event-driven architecture. Apply microservices and agentic AI architectures to support scalability and flexible system development. Develop data pipelines for data preprocessing, normalization, labelling, transformation, feature engineering, and storage. Support research and development initiatives for sovereign AI technologies, including Large Language Models, Large Time-Series Models, and Large Vision Models. Collaborate with cross-functional teams to develop, integrate, and optimize AI-driven solutions. Requirements Bachelor's degree in Graphic Design or an equivalent qualification, as specified for the position. Minimum 10 years of relevant professional experience in graphic design, data science, AI technologies, or a related field. Experience in AI solution development, data pipelines, or AI technology implementation. Knowledge of backend infrastructure, real-time data processing, and event-driven architectures. Familiarity with microservices, agentic AI architectures, and scalable AI applications. Understanding of data preprocessing, transformation, feature engineering, and data storage. Exposure to Large Language Models, time-series models, or computer vision technologies is an advantage. Strong analytical, problem-solving, and collaboration skills.

What You Will Do Test new features and run regression for iOS and Android apps; Test backend APIs and integrations: requests, responses, logs;