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As a Product Manager at Upsun, you own a significant area of Upsun Cloud, our cloud application platform, and the outcomes it delivers for the developers who build on it. The team you join owns the platform's foundations: the API, the runtime, environments, and the reliability every application running on Upsun depends on.

Design and implement extensions to EVM clients (Geth/Reth) for supporting stateful precompiles. Implement novel mechanism design primitives, collaborating with our research team, into the execution layer.

Crusoe is looking for a Senior Software Engineer CAPE to build cloud infrastructure management platforms and workflows.

Crusoe is looking for a Senior Performance Engineer to benchmark and optimize Linux-based infrastructure performance.

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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is a large distributed system: training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts. As an engineer in RL Engineering, you'll work on keeping that system secure as it scales. This is a hands-on engineering role. You'll work in the RL codebase and the infrastructure underneath it, alongside the engineers and researchers who build and use it. The system is large and changes as fast as the research does, so security work here has to keep up with that pace without costing performance or velocity. We're hiring from two backgrounds: security engineers who want to work on large-scale ML systems, and ML systems or research engineers who want to work on security. Strong candidates have depth in one and real interest in the other. Key responsibilities Design, build, and operate security controls for RL training systems and the infrastructure they run on Work across the stack (orchestration, environments, training, inference) wherever the work is needed Review designs and code across the RL stack, find security problems, and fix them Build shared libraries and tooling that other RL engineers and researchers build on Build the observability needed to understand what these systems are doing Work with researchers and performance engineers to make sure security changes preserve training correctness and performance Write clear design documents for what you build Minimum qualifications Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go Experience designing, building, and operating large-scale distributed systems or security systems in production Strong understanding of security fundamentals Working knowledge of Linux, containers, and cloud infrastructure Experience debugging complex problems across many hosts and services Ability to reason about tradeoffs between security, performance, and reliability Strong written communication, including design documents Preferred qualifications Experience running ML training or inference infrastructure at scale Experience with infrastructure security, such as isolation, access control, networking, or identity Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale Experience building observability for large fleets Experience supporting research teams or other fast-moving internal users Familiarity with reinforcement learning or large language model training workloads 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: $320,000 — $405,000 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: USA (Remote); Canada (Remote) Workplace: Remote Mysten Labs’ mission is to advance the internet through step-function improvements in what technology makes possible. We build foundational infrastructure and products that give people, businesses, and developers new ways to interact, transact, and create value. Our work spans on-chain finance and the emerging agent economy. Through Sui, Move, and our broader technology stack, we’re building the systems that make these experiences possible - from secure, scalable blockchain infrastructure to new ways for businesses and AI agents to interact. Mysten Labs is looking for a hands-on Security Engineer with strong application security fundamentals and a track record of finding and fixing real vulnerabilities. You’ll own bug bounty programs and external audits, secure our code and software supply chain, and build tooling that protects Mysten’s products and users across the Sui ecosystem. Responsibilities - Run Mysten's bug bounty programs: triage, severity, responses, internal escalations, fix validation, and the budget and payouts. Turn recurring report classes into automated checks. - Own audit engagements: scope and schedule external audits, act as the technical counterpart during the engagement, and track findings through remediation and fix validation. - Conduct code and design reviews of systems built by Mysten, its subsidiaries and partners (Rust, TypeScript, Move). Drive issues to conclusion, including investigation and incident response, and run variant analysis so each bug class is closed everywhere it occurs. - Own software supply chain security: dependency and CI/CD malware defenses, Endor Labs, the code security service (GitHub controls, merge bots), and the ongoing code security self-auditing service. Detect and respond to compromised packages, maintainers and build pipelines, and secure the provenance and signing of what Mysten ships. - Build and improve anti-scam and anti-abuse tooling for the Sui ecosystem: detect phishing sites, malicious dApps, drainer contracts and other threats that target Sui users, and work with wallet teams on mitigations. - Build security tooling: LLM-driven triage and review agents, and static and dynamic analysis (taint, call graphs, fuzzing) wired into CI and code review. Build in known-clean checks so people trust the results.   MINIMUM QUALIFICATIONS - Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience. - 3+ years of hands-on experience in security engineering, application security or product security, with a track record of finding real vulnerabilities (bug bounty reports, audit findings, CVEs or published research). - Strong Web2 security fundamentals: XSS, CSRF, SSRF, authorization flaws, injection, deserialization, software supply chain failures, cryptographic failures. - Proficiency in one or more of Rust, TypeScript, Python or Move, and experience reviewing and writing security-sensitive code. - Hands-on knowledge of software supply chain attack surface: package ecosystems (npm, crates.io http://crates.io, PyPI), CI/CD (GitHub Actions workflow injection, token exposure, unpinned actions), and build provenance. - Solid understanding of applied cryptography fundamentals and the common ways cryptographic systems are misused in practice. - Experience on either side of a bug bounty program or an audit engagement. - Strong written and verbal communication, including the ability to influence teams you have no formal authority over. - Interest in the web3 space is required.   PREFERRED QUALIFICATIONS - Smart contract or wallet security: Move, Solidity or Rust-based chains; Sui's object and capability model is a plus. - Static or dynamic program analysis: CodeQL, Semgrep, taint analysis, fuzzing, symbolic execution. - Experience building security tooling with LLM agents (Claude Code skills or comparable), and a clear sense of where models help and where deterministic tooling has to do the work. - Anti-phishing, anti-fraud or trust & safety experience: domain and content monitoring, crawling, classifiers, threat intelligence. - Knowledge of recent crypto incidents and the defect classes behind them: drainer kits, DeFi frontend compromises, package-registry compromises. - Notable bug bounty rankings, CVEs, publications or conference talks. Employment is contingent upon the successful completion of a background check, which may include verification of employment history, education credentials, criminal history, and other relevant information. Regarding the recent rash of technology job scams: Be aware that emails from genuine Mysten Labs group recruiters will always come from the @mystenlabs.com http://mystenlabs.com domain or related subdomains (e.g., mystenlabs.com/careers http://mystenlabs.com/careers). Remember: you can always verify positions on our job boards at www.mystenlabs.com/careers http://www.mystenlabs.com/careers. To support an efficient and fair hiring process, we may use technology-assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers. Our team is remote first and we are hiring across the world. Here at Mysten Labs, you’ll be joining a world-class team with tremendous growth potential as we bring the next billion users to web3. We raised a $300M Series B round from top Silicon Valley led venture funds like Jump Crypto, Andreessen Horowitz (a16z), Binance Labs, Redpoint, Lightspeed, Coinbase Ventures, Electric Capital, Standard Crypto, NFX, Slow Ventures, Scribble Ventures, Samsung Next, Lux Capital, among other investment firms and strategic partners. Come join us and build the future of web3!

Location: Remote Workplace: Remote We are looking for an experienced Senior Game Mathematician to take a leading role in developing mathematical models for an in-house slot game portfolio. The position combines advanced game mathematics, statistical modelling, and simulation with the opportunity to influence the technical foundations of math development. Beyond creating and balancing game mechanics, you will contribute to the evolution of internal simulation tools and mathematical frameworks, working closely with game designers, producers, and engineers. Responsibilities - Take full ownership of slot game mathematics, developing models from initial game concepts through balancing, testing, and regulatory certification - Create and fine-tune mathematical configurations for different slot formats, including reel-based, ways/Megaways, cluster pays, grid games, jackpots, and feature buy mechanics - Define and optimize key game parameters such as RTP, volatility, hit frequency, maximum win, payout distribution, and bonus contribution, ensuring alignment with gameplay and product objectives - Develop and adjust reel strips, paytables, symbol distributions, free spins, multipliers, cascades, bonus features, and progressive mechanics, including multiple RTP configurations and ante bet options - Perform large-scale Monte Carlo simulations, validate theoretical and simulated RTP, and evaluate statistical reliability through variance analysis, confidence intervals, and convergence testing - Prepare mathematical documentation, including PAR sheets, RTP calculations, and supporting materials required for independent testing and certification - Contribute to the design and continuous improvement of an internal math development and simulation framework, participating in architectural discussions, technical reviews, and implementation - Evaluate live game performance data, identify potential improvements, and provide mathematical recommendations for existing and upcoming releases - Partner with producers, game designers, and developers to assess new mechanics, balance gameplay experience, and address mathematical or technical risks - Help establish consistent math development standards, share technical knowledge, and support the professional growth of other mathematicians Requirements - 5+ years of professional experience in slot game mathematics within a game provider or development studio, rather than an operator - Track record of at least 10 commercially released slot titles, preferably including games with demonstrated market success - Extensive knowledge of probability, combinatorics, and statistical modelling, with the ability to apply these principles to complex slot mechanics - Proven ability to build complete mathematical models around defined targets, including RTP, volatility, hit rate, maximum exposure, payout distribution, and feature contribution - Practical expertise in balancing different slot formats and mechanics, including Megaways, cluster pays, grid slots, bonus buys, jackpots, free spins, multipliers, and cascading features - Strong understanding of reel and paytable configuration, bonus buy and ante bet mathematics, and multiple RTP variants, with the ability to balance feature frequency, payout sizes, and overall player experience - Advanced experience in mathematical validation and high-volume simulations, including analytical RTP verification, Monte Carlo methods involving billions of spins, variance analysis, confidence intervals, and convergence assessment - Familiarity with gaming certification standards and testing procedures, including requirements associated with GLI, BMM, eCOGRA, iTech Labs, and preparation of mathematical reports and PAR sheets - Ability to independently manage mathematical development throughout the complete game lifecycle, from initial design to final certification - Degree in Mathematics, Applied Mathematics, Statistics, Physics, or a related discipline, preferably at Master's level or above - Previous involvement in building or improving proprietary slot math engines or simulation frameworks - Knowledge of mathematical optimization techniques, including genetic algorithms, simulated annealing, and linear programming, for automated adjustment of reels and paytables - Experience designing mathematical models for crash games, instant-win products, or other alternative gaming formats - Understanding of the interaction between mathematical models, game clients, and backend systems - Fluent English for technical documentation, collaboration with international stakeholders, and communication with testing laboratories or regulators - Strong communication skills, with the ability to translate complex mathematical concepts into practical explanations for non-mathematical colleagues - Willingness and ability to mentor junior and mid-level mathematicians and contribute to knowledge sharing within the team Would be a plus - Proficiency in at least one programming language: Python, C++, C#, Rust, Java, or Go - Experience developing high-performance simulation software, including multithreading, performance optimization, and large-scale data processing - Familiarity with Git, automated testing, and code review practices, as well as software architecture principles such as modularity, well-defined interfaces, and deterministic simulation results - Contributions to industry research, professional publications, conferences such as ICE, SiGMA, or G2E, or relevant technical communities What's in it for you - Opportunity to contribute to the development of innovative iGaming products and influence key technical decisions - Work on challenging projects involving advanced game mathematics and simulation technologies - Opportunities for professional development and career growth - Collaboration with experienced professionals in a supportive, knowledge-sharing environment

Location: Paris; London ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE As a Research Engineer on the Latency & Throughput team, you will push the frontier of LLM inference by researching and prototyping techniques that reduce latency and increase throughput — from speculative decoding and quantization to KV compression and new attention variants. The team sits at the intersection of research and production: you will take ideas from recent literature, form hypotheses, run experiments, and ship the techniques that prove out into our serving stack. This role sits between our inference engineers, who own the production serving stack, and our research scientists, who focus on paper-level contributions. You will be more science-focused than a pure engineer: you are expected to generate new ideas, keep up with the state of the art, and implement proof-of-concepts that bridge the gap between academic results and production impact. Some techniques you explore will be lossy or require integration into training — retraining models, tuning architectures, or training auxiliary models to improve inference. You will work closely with the Inference Foundation and Kernels teams, who turn your validated techniques into production recipes, and with pretraining and RL teams when your work touches model training. Success is measured by demonstrated latency or throughput gains, first at small scale, then adopted in production. What You Will Do - Research and prototype inference techniques — speculative decoding, quantization, KV compression, watermarking, and new model architectures — by reading recent literature and forming testable hypotheses. - Design and run experiments to validate or refute ideas, iterating quickly on small-scale setups before proposing production integration. Demonstrate clear latency or throughput gains without unacceptable quality loss. - Collaborate with the Inference Foundation team to integrate validated techniques into the vLLM-based serving stack. - Partner with pretraining and RL teams when techniques require co-training, retraining, or training auxiliary models to improve inference. Build the right tooling and validation platforms to facilitate AI-driven inference research. What We're Looking For - A strong ML background with solid knowledge of LLM training techniques — architecture, tokenization, fine-tuning, and evaluation. - Hands-on experience with Python and PyTorch; you write clean, experimental code and iterate fast. JAX is acceptable with strong Python proficiency. C++ and Rust are not required, CUDA and GPU knowledge is expected but hands-on experience is not required. - Research experience of some form: a thesis, publications, a dedicated research project, or efficiency-oriented work in a lab or industry research setting. A PhD is not required, but we are looking for genuine research depth. - A track record of conducting experiments: forming hypotheses, designing controlled comparisons, and drawing clear conclusions from results. - Familiarity with the state of the art in LLM inference — you know what has been tried, what works, and where the open problems are. - Self-starter, low-ego, and collaborative. You are comfortable with ambiguity, negative results, and are eager to take matters into your own hands. - Inference or serving experience is a plus, not a requirement. Prior work with vLLM, production LLM deployments, or serving systems will help you ramp up faster. Location and Remote This role is based in our Paris or London offices (hybrid). We will prioritize candidates who reside in the Paris area or are open to relocating. We strongly believe in the value of in-person collaboration to foster strong relationships and seamless communication within our team. For senior profiles, we will also consider remote candidates based in France. In that case, we ask all new hires to visit our Paris office: - For the first week of their onboarding (accommodation and travel covered) - Then at least 3 days per month WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Global, EU We are the creators of a new fintech era! Our mission is to change this world by making blockchain accessible to everyone in everyday life. WhiteBIT is a global team of over 1,200 professionals united by one mission — to shape the new world order in the Web3 era. Each of our employees is fully engaged in this transformative journey. We work on our blockchain platform, providing maximum transparency and security for more than 8 million users worldwide. Our breakthrough solutions, incredible speed of adaptation to market challenges, and technological superiority are the strengths that take us beyond ordinary companies. Our official partners include the National Football Team of Ukraine, FC Barcelona, Lifecell, FACEIT and VISA. The future of Web3 starts with you: join us as a DevOps Engineer with Big Data Skills! Requirements We're looking for a DevOps engineer with 4+ years of hands-on experience, at least 2 of them spent building and running data or analytics infrastructure. You've designed systems that move, store, and serve data at scale. Warehouse maintenance is part of your daily routine, and writing Python, Bash, or SQL scripts is second nature. You treat data security as a core responsibility: you protect confidentiality, enforce zero-trust, least-privilege access, and automate everything you touch. Solid IaC skills are a must. IaC & CI/CD: Production experience with Terraform, Ansible, and Helm, plus CI/CD systems (GitLab CI, GitHub Actions, Jenkins, or ArgoCD). We expect you to design pipelines, not just use them. Containerization: Working knowledge of Docker and Kubernetes, including running data workloads on it (like Spark on Kubernetes, stateful services, operators). Cloud: Solid experience with AWS (S3, EC2, EMR, Redshift, Glue, IAM) or an equivalent cloud provider. Linux & Networking: Solid Linux administration skills and foundational networking knowledge relevant to distributed systems. Analytical Databases: Hands-on operation of ClickHouse and/or the Hadoop ecosystem (HDFS, Hive, YARN), including cluster setup, tuning, and scaling. Data Warehouses: Practical experience with Snowflake or Redshift, covering warehouse sizing, workload management, performance tuning, and cost control. Large Databases: Experience administering databases at terabyte scale: replication, backup and restore strategies, partitioning, and migrations with minimal downtime. SQL & Scripting: Strong SQL skills, including reading execution plans and optimizing heavy queries. Confident in Python and Bash for automation, data parsing, and investigation. Data Lakes & Object Storage: Working knowledge of S3-compatible storage, columnar formats, partitioning strategies, and data lifecycle management. Orchestration & Streaming: Familiarity with Airflow (or similar orchestrators) and Kafka, and how they fit into data pipelines. Extra Credit / Big Pluses Experience with Tableau, Power BI, Looker, Superset, or similar BI tools, including administration, performance tuning, and data source design. Hands-on experience with dbt and analytics engineering practices. Experience with open table formats (Apache Iceberg, Delta Lake, Hudi) and query engines like Trino/Presto or Athena. FinOps experience in data platforms: managing Snowflake credits, Redshift clusters, and storage costs at scale. Spark performance tuning and job optimization. Change data capture (CDC) with Debezium or similar tools. Data quality tooling (Great Expectations, Soda) integrated into CI/CD. Golang or Rust tooling experience. Knowledge of data governance and compliance (GDPR, data retention, PII handling). Understanding of business processes in the FinTech/Banking/Crypto sector. Responsibilities Infrastructure Ownership: Own the infrastructure behind our data and analytics platform, from provisioning to daily operations. Keep it reliable, scalable, and cost-efficient as data volumes grow. Infrastructure as Code: Provision and configure all data infrastructure with Terraform, Ansible, and Helm. CI/CD Pipelines: Build and maintain delivery pipelines for both infrastructure and data code (ETL jobs, Airflow DAGs, dbt models, schema migrations), with automated testing, safe rollouts, and fast rollback. Database & Warehouse Operations: Maintain ClickHouse, Snowflake, Redshift, and вPostgreSQL at multi-terabyte scale, handling replication, backups, upgrades, capacity planning, and disaster recovery. Data Lake Storage: Manage S3-compatible data lake storage, including partitioning, file formats, and lifecycle policies. Automation & Script Optimization: Refactor and automate Python, Bash, and SQL scripts to cut runtimes and eliminate manual work. Performance & Cost: Right-size clusters and warehouses, tune heavy queries, and keep compute and storage spend under control. Monitoring & Alerting: Cover data infrastructure with metrics, logs, and alerts for cluster health, pipeline SLAs, and job failures. Security & Access Control: Enforce least-privilege access, secrets management, encryption, and auditability for sensitive data. BI Infrastructure: Support the infrastructure behind Tableau or similar BI tools. Big Data Platforms: Deploy, tune, and troubleshoot Hadoop, Spark, and Kafka clusters in production. Collaboration: Work with data engineers, analysts, and developers to turn their workloads into solid infrastructure decisions. Security & Access Control: Implement role-based access, secrets management, encryption at rest and in transit, and auditability for sensitive datasets in line with regulatory requirements. Working terms Immerse yourself in Crypto & Web3: Master cutting-edge technologies and become an expert in the most innovative industry. Work with the Fintech of the Future: Develop your skills in digital finance and shape the global market. Take Your Professionalism to the Next Level: Gain unique experience and be part of global transformations. Drive Innovations: Influence the industry and contribute to groundbreaking solutions. Join a Strong Team: Collaborate with top experts worldwide and grow alongside the best. Work-Life Balance & Well-being: Modern equipment. Comfortable working conditions, and an inspiring environment to help you thrive. 24 calendar days of paid leave. Additional days off for national holidays. With us, you’ll dive into the world of unique blockchain technologies, reshape the crypto landscape, and become an innovator in your field. If you’re ready to take on challenges and join our dynamic team, apply now and start a new chapter in your career! Let’s Build the Future Together! WhiteBIT offers all candidates an equal opportunity to join the team. All hiring decisions are made without regard to race, national origin, gender identity or sexual orientation, age, religion, disability, medical condition, marital status, familial status, veteran status, or any other legally protected characteristic of an individual. Your privacy matters to us. You can learn more about how we handle your personal data with regard to your application in our Candidate Privacy Notice .

Location: New York City, NY | Seattle, WA; 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 a Staff+ Software Engineer to work on the vector search infrastructure behind Claude. Retrieval is how Claude learns about the world. Web search across claude.ai, the API and agentic surfaces, memory across conversations, and the reinforcement learning workloads that train our next models all depend on fast, cheap, high-recall nearest-neighbor search over billions of vectors. You'll join a small team responsible for the vector database layer that serves Claude's retrieval workloads: its architecture, performance, scalability and cost. This is a foundational role. The team is small, core architectural decisions are still open, and the engineers who join now will shape how the system evolves. The role sits in our Databases organization and works day to day with the Search Platform team, which owns web search indexing, retrieval and serving, and the Memory & Search team, which owns search and memory inside claude.ai. We're looking for someone who has built vector or search systems that ran in production, at scale, with real users and a real on-call. You'll be hands-on in the code, and you'll also be the person deciding how the pieces fit together. Key responsibilities Own the core of Anthropic's vector database layer: index structures, storage layout, query execution and the serving layer Own production readiness - benchmarking against exact search, capacity planning, onboarding new workloads, and the operational tooling to run it at scale Drive the recall, latency and cost trade-offs - quantization, filtered search, index build and refresh strategy, and how compute and storage are separated and scaled Scale throughput by an order of magnitude as research and training demand grows, and work out whether the bottleneck is architecture, hardware or engineering bandwidth Extend the retrieval stack toward hybrid retrieval - lexical search and fused ranking alongside vector search Set the evaluation methodology for the system -  recall targets, latency objectives, cost per query, and the regression detection that keeps them honest Set technical direction for a growing team - lead design reviews, make architectural decisions others build on, and mentor the engineers joining the effort Share the on-call for the systems you own Minimum qualifications Direct experience building a vector database or approximate nearest-neighbor search system that ran in production at scale Deep knowledge of ANN index structures (graph-based, clustering-based or disk-resident approaches), vector quantization and filtered search Experience with search relevance and ranking Strong systems programming skills in a language such as Rust, C++ or Go, including performance-critical and memory-intensive code Experience designing and operating large-scale distributed storage or serving systems with strict latency and reliability requirements A track record of independently scoping and delivering ambiguous, multi-quarter technical projects Strong written and verbal communication, with experience driving alignment across teams with different priorities Interest in AI safety and Anthropic's mission Preferred qualifications Experience with object-storage-backed or disaggregated compute and storage database designs Experience building or operating full-text search engines (inverted indexes, BM25) or hybrid retrieval systems Familiarity with embedding models and the retrieval demands of LLM training and inference Experience using GPUs or other accelerators for index build or search Prior experience as a technical lead on a database or search infrastructure 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: $320,000 — $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 - US About Backblaze Backblaze is the object storage leader in the open cloud movement, fueling customer success with cloud storage built purposefully to unlock budgets, unburden administrators, and unleash innovators. Together with our partners, we’re helping customers break free from the restrictive, overpriced legacy solutions that hold them back, and blaze forward with the full power of the open cloud in their hands. Founded in 2007, we scaled the business with less than $3 million in outside funding until 2021, when we did a traditional IPO on the Nasdaq stock exchange. Today, Backblaze generates over $100m in revenue and is the leading specialized storage cloud - managing over three billion gigabytes of data storage for 500K+ customers in 175+ countries, including businesses, developers, IT professionals, and individuals. Want to know what you’ll be doing? You will work on our data infrastructure platform which supports the B2 Object Storage and Computer Backup products, responsible for the data infrastructure that everything runs on. You will help improve automation, observability and stability for durability, increase throughput, and drive architectural changes to support the long term requirements of our service. Responsibilities: Design and build automation frameworks that let other engineers provision, configure, and repair fleet infrastructure themselves Design and extend the observability stack (metrics, logs, traces, alerts) that tells us whether the storage platform is healthy and where it is degrading Build reporting, dashboards, and visualizations that give engineering and leadership a clear view into fleet health, capacity, and operational trends Build system health tooling that detects failing hardware, drifting configuration, and capacity risk before they turn into incidents Lead technical design discussions and produce clear design documents for changes that span multiple services and teams Drive the implementation of large features from design through rollout, including the migration and backfill work that real systems require Partner with the on-call rotation to turn recurring toil and incident findings into automation and better signal The Right Fit: 7+ years of backend development in an enterprise environment, working in an object-oriented or systems language (Java, Rust, C++, C#, Go, or similar) Experience designing automation frameworks or platforms that other engineers build on Experience building large scale software systems running on thousands of servers Experience building automation or tooling that other engineers depend on daily, whether internal platform services, operational tooling, or a deployment and configuration pipeline Working knowledge of an observability stack (Prometheus, Grafana, OpenTelemetry, ELK, Datadog, or equivalent), including instrumenting a service and designing alerts people trust Strong Linux fundamentals and comfort operating in a bare-metal or hybrid environment rather than a fully managed cloud Professional experience incorporating AI-assisted development tools (Gemini, Cursor, Claude Code, or similar) Comfortable with all aspects of the software development lifecycle, including design, implementation, testing, and rollout Exhibits curiosity and seeks to understand before offering solutions Communicates proactively in a remote environment by keeping the team informed, surfacing blockers early, and moving work forward Applies analytical thinking to ambiguous problems Bonus points for: Proficiency in Java Experience with configuration management or infrastructure-as-code tooling (Ansible, Salt, Puppet, Chef, Terraform) Experience designing SLOs and error budgets, or reducing alert noise on a fleet running at scale Experience with time-series databases and query languages such as PromQL Experience automating hardware lifecycle work: burn-in, failure detection, drive replacement, decommissioning Experience with discovering and implementing performance improvements, including CPU and IO Understanding of Linux internals and file systems Familiarity with hard drive performance and optimization, including host-managed SMR Experience building and interpreting models, dashboards, or reports Required for all Backblaze Employees: Good attitude and willingness to do whatever it takes to get the job done Strong desire to work for a small, fast-paced company Desire to learn and adapt to rapidly changing technologies and work environment Rigorous adherence to best practices Relentless attention to detail Excellent interpersonal skills and good oral/written communication Excellent troubleshooting and problem solving skills Backblaze Perks: Healthcare for family, including dental and vision Competitive compensation and 401K RSU grants for full-time employees ESPP program Flexible vacation policy Maternity & paternity leave MacBook Pro to use for work plus a generous stipend to personalize your  workstation Childcare bonus (human children only) Fertility treatment and support Learning & development program Commuter benefits Culture that supports a healthy work-life balance To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar-stage growth companies. Final offer amounts are determined by multiple factors, including candidate location, skills, depth of work experience, and relevant licenses/credentials, and may vary from the amounts listed below. The base pay range for this position is: $175,000 - $200,000 At Backblaze, we value being fair and good to our customers, partners, and employees. That’s why diversity, equity, and inclusion are at the core of our values. We are committed to fostering a workforce where all employees feel a sense of belonging regardless of race, ethnicity, nationality, gender, sexual orientation, age, religion, socio-economic status, ability, veteran status, and education. We believe that our dedication to cultivating a diverse workspace not only allows us to better serve our customers in over 175 countries, but further reinforces our commitment to doing the right thing. We are proud to be an Equal Opportunity Employer. To understand more about the data we collect and process as part of your application, please view our Backblaze Employee Privacy Notice.

Location: East Coast US & Europe (Remote) Workplace: Remote About Dune Dune's mission is to make onchain finance observable. We're the industry standard for onchain data: a blockchain data and intelligence provider that institutions, protocols, and analysts trust to understand the onchain world and the frontiers of finance. We deliver structured datasets, spanning stablecoins, RWAs, tokens, lending, trading, and more, from 130+ chains and counting, to 1,000+ industry leaders including Visa, WisdomTree, FINRA, the IMF, Bloomberg, Standard Chartered, Coinbase, Forbes, and the Financial Times. We're a tight knit team of ~50 hard working people, spread across Europe and eastern US timezones 🌍️, having an outsized impact on the industry. We take pride in being ambitious and doing world class work while staying humble and lighthearted. We believe in building open, verifiable data that lets individuals and institutions do deep research into ecosystems like Ethereum, Solana, Robinhood and many more. We're backed by some of the world's best investors. In February 2022, we announced our Series B funding round led by Coatue and Union Square Ventures, an important milestone that let us double down on our mission. If you like being challenged and want to work together with a brilliant team on an important mission, come join us. Learn more about us: About Dune https://dune.com/about Values and working at Dune https://dune.com/careers ABOUT THE ROLE Dune is building market data solutions for institutional customers who need timely, accurate and reliable financial data they can depend on. Our team turns onchain activity into realtime feeds and associated reference data along with historical data capture. You will work on our new market data platform, and help shape how it evolves to support the growing features and customer base. You’ll design systems that can grow across chains, protocols and product capabilities while making clear decisions about correctness, latency, reliability, and cost. This is a hands-on Staff Engineer role. You will be expected to turn ambiguous requirements into designs and deliverable work, implement difficult parts yourself, and help other engineers own meaningful parts of the platform. AI-assisted development is a core part of how we expect you to work, paired with strong engineering judgment and ownership of what you ship. IN THIS ROLE YOU WILL - Design and build distributed systems for ingestion, normalization, processing, storage, and delivery of realtime market data from blockchain and other relevant sources. - Build and operate streaming solutions that handle event ordering, timestamps, duplicates, replay, gaps, and recovery, including blockchain reorganizations and finality where they affect customer data. - Build reliable client feeds and APIs with clear delivery contracts, schema evolution, access controls, and predictable behavior under load or when consumers fall behind. - Partner with teams across Dune on reference data models and historical data capture. - Define and improve service objectives and data quality measures. - Instrument latency, freshness, completeness, and correctness, and turn incidents into lasting improvements in recovery and operations. - You will debug independently and drive root cause analysis to a fix that holds. - Own services through deployment and production support, including participation in the team’s on-call rotation. - Use AI throughout development: explore designs, implement changes, build tests, investigate failures, and improve documentation. Develop repeatable workflows and share what works with the team. - Lead technical decisions across team boundaries, write clear designs, and mentor engineers through implementation and review. YOU MIGHT BE A GREAT FIT IF - You have built and operated distributed backend or data services with demanding reliability and performance requirements. You understand their failure modes and can debug problems across service and data boundaries. - You have experience with realtime streaming systems, including concurrency, state management, backpressure, and recovery. You care about data correctness, from timestamps and numeric precision to schema changes and corrections. - You have strong computer science fundamentals and backend engineering skills. Experience in Rust, Go or comparable languages is also valuable. - You turn ambiguous requirements into pragmatic designs and production services, and help other engineers deliver parts of the solution. - You communicate clearly in writing and work effectively with a distributed team. - Financial or market data experience at a financial institution. NOT REQUIRED BUT A PLUS - Onchain data experience: blockchain indexing such as with EVM or Solana. - Reference data experience: instrument and entity masters, identifier mapping, effective-dated records, or tokenized asset and fund data. - Experience at a company where the data is the product. PERKS & BENEFITS - A competitive salary and equity package 🚀. Both salary and equity is top 25% of companies https://notion.so/Careers-at-Dune-Doing-the-best-work-of-your-life-f25e0b5e1f624d2aaf3ef2c81558ea96#7f745f5112394686bd7c127c720f2024 in the space - Our employee equity scheme has world-class employee-friendly terms with a heavily discounted strike price (~90%) and a 10-year exercise window - 5 weeks PTO + local public holidays (that can be swapped to suit you) 🏖 - A fully remote-first approach 🧑‍💻 within a distributed team with flexible working hours; you structure your own day  - Say goodbye to meeting overload! We believe in a healthy mix of async and sync work, so you can focus on what truly matters—no more wasted time on endless meetings! - Good health is important, so we offer private medical insurance, dental & vision as standard 🩺 - We believe in paid parental leave 👶 to help you celebrate this important milestone, transition to your new life, and bond with your new baby. We offer 16 weeks to primary and 6 weeks to secondary caregivers, fully paid. Plus a 2-week part-time phased return at full pay to help you get used to your new (and slightly more complex!) schedule - Quarterly offsites in various exciting locations as a company or team to connect, work together and have fun (so far in Tuscany 🇮🇹 Berlin 🇩🇪 Austria 🇦🇹 and Athens 🇬🇷). - On top of this 👆each person gets a yearly travel allowance to connect and co-work with someone or a team of people for a few days. - An allowance for your at-home setup, to ensure you are happy, comfortable and productive. If you prefer a local co-working space, we’ll pay for your desk. - An annual allowance for your Learning and Development needs. - Work with some of the best people you’ll ever get to meet! - And of course, you get some awesome Dune swag! ✌️😎 ------------------------------------------------------------------------------------------ We are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role but your experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. #LI-Remote

• Разработка и интеграция решений на основе CoinJoin. • Работа с Bitcoin-транзакциями.

• Разработка и интеграция решений на основе CoinJoin. • Работа с Bitcoin-транзакциями.

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.

Lovable is looking for a Data Infrastructure Engineer to build and operate scalable multi-tenant data infrastructure, storage, queries, connectors, and observability.

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.