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Location: San Francisco, CA 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's Business Risk & Insurance (BRI) team, part of Treasury, safeguards the company's balance sheet, people and physical assets. We are the financial and operational safety net for a company building some of the world's most advanced AI systems, from large-scale compute and data center infrastructure to our offices and the products we put in customers' hands. The team is scaling quickly as Anthropic grows. As a Risk & Insurance Specialist, you'll build operational excellence across contracts, claims, and day-to-day insurance operations, using AI and automation to streamline processes wherever you can. You'll work closely with Compute, Engineering, Finance, Legal, Security, Product and Payroll to spot emerging risks early, help structure global insurance programs, support our risk-financing strategy and drive loss prevention. This is a rare chance to insure one of the fastest-growing companies, where parts of the risk landscape are still being defined, and to help Anthropic pursue its mission boldly by keeping our operations resilient and protected. Key responsibilities Insurance review of contracts: Review insurance and indemnity requirements in customer, vendor, lease, and compute agreements, and advise Legal and business partners on compliant, practical positions. Insurance operations: Manage claims intake and tracking, certificates of insurance, broker coordination, and policy administration. Build a data warehouse / repository and repeatable processes as volume scales. Data gathering and reporting: Collect and maintain exposure data (property values, payroll, revenue, headcount, etc.) for renewals, audits, and underwriting submissions. Actuarial and quantitative analysis: Support limit-adequacy, loss, and retention analyses to inform program structure and decisions. Captive operations: Support captive formation and ongoing operations, including fronting and reinsurance coordination. Automation: Identify and implement ways to automate manual insurance workflows using AI and workflow tools. Cross-functional support: Partner with Compute, Finance, Legal, and Payroll on insurance questions across the business. Minimum qualifications Experience in insurance, corporate risk management, brokerage, underwriting, or risk consulting. Hands-on experience supporting a multi-line commercial insurance program (property, casualty, cyber/tech E&O, D&O/management liability, and similar). Preferred qualifications 8–12 years in insurance, corporate risk management, brokerage, underwriting, or risk consulting At least 4 years on the corporate (buyer) side, or in a broker or carrier role serving corporate clients Experience at, or insuring, a technology company or other fast-growing, complex organization Property insurance experience, including large or complex property, construction, or data center exposures Captive insurance experience (formation, management, fronting, or reinsurance) Experience insuring emerging technology risks, such as AI or technology liability and cyber Background at a major broker, carrier, or large technology company risk team Actuarial training or credentials, or experience with actuarial analysis Familiarity with insurance management systems, SQL or Python, or building workflow automation Experience building processes from scratch in an ambiguous, fast-moving environment 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: $180,000 — $230,000 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. 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.

• Функциональное тестирование платформы OpenMetadata. • Проверка процессов сканирования источников данных (ingestion), профилирования данных и управления тегами и глоссариями.

Location: Remote - US Role Overview This is a senior individual contributor role with significant architectural ownership. You will set the technical direction for how Backblaze detects, correlates, and responds to infrastructure incidents across our data centers, and you will mentor other engineers on the team as that platform matures. If you have a passion for making complex distributed systems visible, you are comfortable making architecture decisions that will outlive your tenure, and you are excited about applying AI and agentic automation to infrastructure operations, this role was built for you.. Key Responsibilities Technical Leadership Set technical direction and standards for observability across the organization, including instrumentation conventions, alerting philosophy, and dashboard design patterns. Mentor engineers on the Observability team and act as a technical resource for SRE, Storage Engineering, and Network Engineering on observability practice. Lead design reviews for observability work and represent the team in cross-functional architecture discussions. Evaluate build-versus-buy decisions for observability and AIOps tooling, including data sovereignty and compliance considerations. Produce and maintain design documentation, runbooks, and architectural decision records that make the platform operable and extensible by future contributors. Observability Platform Own and evolve our metrics pipeline, including VictoriaMetrics, Prometheus, and the Consul-based service discovery layer that keeps scrape targets current as infrastructure scales. Own and expand our logging stack (OpenSearch, Logstash, and Filebeat) across all Backblaze data centers. Architect and expand distributed tracing with Jaeger and OpenTelemetry, extending coverage beyond the current application instrumentation to new services. Define and maintain Grafana dashboard standards for infrastructure, storage, and application performance visibility. Drive expansion of internal application telemetry in partnership with application teams to improve visibility. Define capacity and retention strategy for the telemetry stack as the fleet grows. Infrastructure & Automation Own infrastructure-as-code for observability stack deployments across multiple Kubernetes clusters. Write and review automated playbooks for configuration management and automation across Debian-based bare metal servers. Partner with the SRE team on Consul-based service discovery for VictoriaMetrics scrape target automation. Lead Ceph storage observability, including OSD health, performance metrics, and integration with alerting. Collaborate with the Network Engineering team on BGP, routing, and network-level observability. Required Qualifications 8+ years in a systems engineering, SRE, DevOps, or observability-focused role, including demonstrated technical leadership on a platform or infrastructure team. Deep hands-on experience with Prometheus, VictoriaMetrics, or equivalent metrics platforms, including PromQL, Alertmanager, and operating these systems at scale. Experience designing and operating log aggregation pipelines such as Elasticsearch/OpenSearch, Logstash, Filebeat, or similar. Working knowledge of distributed tracing (Jaeger, OpenTelemetry, or equivalent), including instrumentation strategy, not just operation. Proficiency in Python and/or Go for automation and tooling. Experience with Kubernetes, including deploying workloads and understanding pod networking and storage. Experience with infrastructure-as-code tooling and configuration management. Strong understanding of Linux internals, with Debian/Ubuntu preferred. Demonstrated experience mentoring engineers and raising the technical bar on a team. Excellent written and verbal communication skills. You'll work across engineering, SRE, security, and leadership, and you'll be expected to write design documents that drive decisions. Preferred Qualifications Experience leading the evaluation or deployment of AIOps tooling, including alert correlation, deduplication, or automated root cause analysis. Experience building, deploying, or operating AI agents or agentic AI systems. This is a strong differentiator. Familiarity with LLM APIs (Anthropic, OpenAI) or self-hosted LLM inference in an infrastructure context. Familiarity with Ceph storage, including OSD management, pool configuration, and CRUSH maps. Experience with incident management platforms. Familiarity with BGP, network observability, or working in multi-DC environments. Experience with secrets management in production environments. Experience operating in a regulated or compliance-driven environment. Prior experience in a storage-focused company or hyperscale infrastructure environment. What You'll Work On A telemetry stack spanning several data centers with exabytes of storage under observation. Real infrastructure at scale: Kubernetes, Ceph, Vitess, KVM, and a custom storage platform serving hundreds of thousands of customers. A collaborative team that values engineering excellence, transparency, and operational rigor. Pay Transparency To provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. Final offer amounts are determined by multiple factors including candidate location, skills, depth of work experience, and relevant licenses/credentials. The expected salary range for this role is $178,000 - $200,000 plus 10% target annual bonus and RSUs. At Backblaze, we value being fair and good to our customers, partners, and employees. 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 are proud to be an Equal Opportunity Employer.

Сбор данных из внутренних сервисов, LLM Gateway, GitLab, Jira, логов AI-агентов и других источников. Проектирование и наполнение баз данных и аналитических витрин для оценки использования CodeGen-платформы.

Location: New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE The ways customers buy from us are multiplying as fast as the business is growing. Enterprise order forms. Private offers through AWS, GCP, and Azure. A self-serve business running on usage-based pricing, with commits, drawdowns, and true-ups behind it. Each one is a distinct path from signature to cash, and each one runs today on some mix of manual steps and automation that grew up with the business. This role owns what comes next. You'll run order operations end to end - booking, provisioning, invoicing, amendments, and renewals - on a stack we picked deliberately and recently: Salesforce, Metronome for metering and billing, Rillet for ERP. The stack is modern, but the processes on top of it were built to keep up with growth, not designed to scale. Your job is to decide what each one should become: keep it, rebuild it, automate it, or retire it. Our bias is to invest in systems rather than in a growing queue of manual work, so you'll be setting the automation roadmap at the same time you're operating the function - deciding what a person should touch, what a workflow should handle, and what should never have been a step in the first place. Getting that right is what lets order volume grow by an order of magnitude without ops growing with it. This is a senior individual contributor role. You'll own order operations, working closely with Deal Strategy and Operations, GTM Systems, Finance and Accounting, and Enterprise Engineering. Those teams are your partners and much of your build capacity. Bringing them onto one shared order-to-cash roadmap is a core part of the job, and the reason we're hiring someone senior to do it. WHAT YOU'LL DO - Own the order-to-cash path end to end: order form intake from Deal Desk, booking in Salesforce, plan and entitlement setup in Metronome, invoicing and revenue recognition through Rillet, and the amendments, true-ups, and renewals that follow - Build out cloud marketplace operations across AWS, GCP, and Azure: private offer setup, usage reporting to each marketplace, and reconciling marketplace disbursements back to what we billed. Every new channel launches against defined readiness criteria, so marketplace deals run on the same clean path as direct ones - Own self-serve billing operations: usage metering, plan changes, dunning, credits, rebills, refunds, and the escalations behind them - Own billing and usage completeness at month-end close. Every order, credit, and metered event is reconciled between Metronome and Rillet before revenue is recognized, not after - Partner with Deal Strategy and Product as our pricing evolves. Bring the billing view into pricing and deal-structure decisions early, so new models and non-standard terms can be billed accurately and automated, not handled by hand - Set the automation roadmap. Instrument the path, put a number on every place a human touches an order, and decide what gets automated, what gets designed away, and what stays manual on purpose - Treat every billing error as a defect: find the root cause and fix the class of problem, not just the one invoice - Ship automations yourself where that's fastest, and partner with GTM Systems and Enterprise Engineering where the work belongs in core systems or the product - Write the playbook and the controls behind it: approvals, segregation of duties, reconciliations, and exception handling, built so order ops scales through systems rather than headcount and holds up under audit - Own three numbers and move them: touchless order rate, signature-to-provisioned cycle time, and billing accuracy WHAT WE'RE LOOKING FOR - 6+ years in order management, order-to-cash, billing operations, or revenue operations at a B2B SaaS company, including time building the function at an early-stage or fast-scaling one - Hands-on fluency with a modern billing and ERP stack. We run Salesforce, Metronome, and Rillet - you should know something comparable well enough to have opinions, and get to depth on ours quickly - Real experience with usage-based pricing. Per-seat is straightforward; metered consumption, commits, drawdowns, overages, and true-ups are where order ops gets interesting, and that's most of our business - Working knowledge of ASC 606 and month-end close. You don't need to be an accountant, but you should know what Revenue Accounting needs from billing data and why - Cloud marketplace experience (AWS, GCP, or Azure private offers), or a track record of getting deep on a system like that fast - A history of automating your own job. We'll ask you to walk us through a manual process you deleted: what it cost before, what you built, and what it costs now - The ability to build alignment across teams with different priorities and get to a decision, without relying on org authority - Comfort shipping a v0 earlier than feels comfortable, then iterating with real feedback NICE TO HAVE - SQL, Python, or low-code tooling in your own hands rather than on someone else's backlog - Experience building agents or LLM workflows for internal operations. We'd like to run more of our own back office on the LangSmith Platform, wherever it's the right tool and meets the same accuracy bar as the rest of order-to-cash - Audit prep or SOX readiness experience Compensation: $155,000 - $185,000 salary + options Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE The ways customers buy from us are multiplying as fast as the business is growing. Enterprise order forms. Private offers through AWS, GCP, and Azure. A self-serve business running on usage-based pricing, with commits, drawdowns, and true-ups behind it. Each one is a distinct path from signature to cash, and each one runs today on some mix of manual steps and automation that grew up with the business. This role owns what comes next. You'll run order operations end to end - booking, provisioning, invoicing, amendments, and renewals - on a stack we picked deliberately and recently: Salesforce, Metronome for metering and billing, Rillet for ERP. The stack is modern, but the processes on top of it were built to keep up with growth, not designed to scale. Your job is to decide what each one should become: keep it, rebuild it, automate it, or retire it. Our bias is to invest in systems rather than in a growing queue of manual work, so you'll be setting the automation roadmap at the same time you're operating the function - deciding what a person should touch, what a workflow should handle, and what should never have been a step in the first place. Getting that right is what lets order volume grow by an order of magnitude without ops growing with it. This is a senior individual contributor role. You'll own order operations, working closely with Deal Strategy and Operations, GTM Systems, Finance and Accounting, and Enterprise Engineering. Those teams are your partners and much of your build capacity. Bringing them onto one shared order-to-cash roadmap is a core part of the job, and the reason we're hiring someone senior to do it. WHAT YOU'LL DO - Own the order-to-cash path end to end: order form intake from Deal Desk, booking in Salesforce, plan and entitlement setup in Metronome, invoicing and revenue recognition through Rillet, and the amendments, true-ups, and renewals that follow - Build out cloud marketplace operations across AWS, GCP, and Azure: private offer setup, usage reporting to each marketplace, and reconciling marketplace disbursements back to what we billed. Every new channel launches against defined readiness criteria, so marketplace deals run on the same clean path as direct ones - Own self-serve billing operations: usage metering, plan changes, dunning, credits, rebills, refunds, and the escalations behind them - Own billing and usage completeness at month-end close. Every order, credit, and metered event is reconciled between Metronome and Rillet before revenue is recognized, not after - Partner with Deal Strategy and Product as our pricing evolves. Bring the billing view into pricing and deal-structure decisions early, so new models and non-standard terms can be billed accurately and automated, not handled by hand - Set the automation roadmap. Instrument the path, put a number on every place a human touches an order, and decide what gets automated, what gets designed away, and what stays manual on purpose - Treat every billing error as a defect: find the root cause and fix the class of problem, not just the one invoice - Ship automations yourself where that's fastest, and partner with GTM Systems and Enterprise Engineering where the work belongs in core systems or the product - Write the playbook and the controls behind it: approvals, segregation of duties, reconciliations, and exception handling, built so order ops scales through systems rather than headcount and holds up under audit - Own three numbers and move them: touchless order rate, signature-to-provisioned cycle time, and billing accuracy WHAT WE'RE LOOKING FOR - 6+ years in order management, order-to-cash, billing operations, or revenue operations at a B2B SaaS company, including time building the function at an early-stage or fast-scaling one - Hands-on fluency with a modern billing and ERP stack. We run Salesforce, Metronome, and Rillet - you should know something comparable well enough to have opinions, and get to depth on ours quickly - Real experience with usage-based pricing. Per-seat is straightforward; metered consumption, commits, drawdowns, overages, and true-ups are where order ops gets interesting, and that's most of our business - Working knowledge of ASC 606 and month-end close. You don't need to be an accountant, but you should know what Revenue Accounting needs from billing data and why - Cloud marketplace experience (AWS, GCP, or Azure private offers), or a track record of getting deep on a system like that fast - A history of automating your own job. We'll ask you to walk us through a manual process you deleted: what it cost before, what you built, and what it costs now - The ability to build alignment across teams with different priorities and get to a decision, without relying on org authority - Comfort shipping a v0 earlier than feels comfortable, then iterating with real feedback NICE TO HAVE - SQL, Python, or low-code tooling in your own hands rather than on someone else's backlog - Experience building agents or LLM workflows for internal operations. We'd like to run more of our own back office on the LangSmith Platform, wherever it's the right tool and meets the same accuracy bar as the rest of order-to-cash - Audit prep or SOX readiness experience Compensation: $155,000 - $185,000 salary + options Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Lisbon; Portugal Workplace: Hybrid ROLE HIGHLIGHTS: - Role: Forward Deployed AI Engineer - Department: Forward Deployed Engineering - Location: Portugal (Lisbon) - Reports to: VP, Forward Deployed Engineering - Working type: Hybrid (On-site at customer locations approx. 50% of time) - Must be eligible and able to attain relevant national and NATO security clearances. - Must be based in-country and native level speaker of the country you're deploying to. THE MISSION OF THE FORWARD DEPLOYED AI ENGINEER In this role, you'll be the hands-on AI builder defense and intelligence customers rely on. You’ll deploy ICEYE’s intelligence platform into secure (often air-gapped) environments and rapidly ship AI-powered workflows on top of it—everything from Docker-based deployments to RAG systems fusing SAR imagery with intelligence reports. This is a ship-code-daily role: turning raw satellite data into mission-critical tools analysts use to protect nations. WHO WE ARE ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. DAY TO DAY RESPONSIBILITIES: PLATFORM DEPLOYMENT & INTEGRATION - Deploy ICEYE's intelligence platform into customer secure environments (on-premise, air-gapped networks, classified data centers). - Build and maintain containerized applications (Docker) and manage deployments in customer Kubernetes clusters. - Develop APIs and data pipelines connecting ICEYE systems to customer C4ISR infrastructure and intelligence tools. - Troubleshoot deployment issues in disconnected environments without external internet access. AI SOLUTION DEVELOPMENT & CUSTOMIZATION - Build Retrieval-Augmented Generation (RAG) systems that combine ICEYE SAR data with customer intelligence documents for context-aware analysis. - Develop AI agents and workflows using frameworks like LangChain, LangGraph, or similar tools to automate analytical tasks. - Implement prompt engineering strategies and conversational AI interfaces that enable analysts to query satellite data using natural language. - Create Model Context Protocol (MCP) integrations connecting AI systems with customer data sources. DATA FUSION & INTELLIGENCE WORKFLOWS - Build data fusion pipelines combining SAR imagery with additional intelligence sources (AIS, RF signals, optical imagery, SIGINT). - Develop automated workflows that correlate and cross-reference information across different data modalities. - Create lightweight tools, dashboards, and alerting systems tailored to customer operational needs. CUSTOMER ENGAGEMENT & RAPID PROTOTYPING - Work embedded with intelligence analysts, data scientists, and military operators to understand mission-critical problems. - Rapidly prototype AI-powered solutions (code first, polish later) that address immediate operational requirements. - Conduct hands-on training sessions on platform capabilities and AI workflow usage. - Gather customer feedback and translate it into technical requirements for ICEYE's product and engineering teams. WHAT WE ARE LOOKING FOR MUST HAVE SKILLS: - 3+ years hands-on software engineering building and deploying production systems. - Strong Python programming skills (required) plus one of: Go, TypeScript, or Rust. - Hands-on experience with LLMs, prompt engineering, and RAG systems. - Working knowledge of agent frameworks (LangChain, LangGraph, pydantic-ai) and vector databases. - Experience with Docker and deploying in secure / isolated / air-gapped environments. - Practical experience with APIs, data pipelines, and integrating systems in production, - Familiarity with Linux and basic Kubernetes operations. - Builder mindset: ship fast, iterate with feedback, and prioritize working solutions over perfect architecture. - Strong communication + customer engagement, able to work embedded with intelligence analysts / military operators. - Strong spoken and written English, able to explain technical concepts to non-technical stakeholders. - Willingness to travel 40–60% to customer sites within the region. NICE TO HAVE SKILLS: - Experience in defense, intelligence, or government operational environments. - Deploying to on-prem data centers and/or air-gapped networks. - Familiarity with geospatial data, satellite imagery, or remote sensing. - Experience with MCP integrations, multi-agent systems, or agentic workflows. - Deeper Kubernetes, IaC (Terraform/Ansible), and/or offline CI/CD. - Understanding of intelligence analysis workflows and defense/government requirements. - Experience with data fusion, multi-source intelligence integration, or GIS tools (ArcGIS, QGIS). - Background in solution engineering, technical consulting, or customer success. - Experience in defense tech (e.g., Palantir, Anduril, Scale AI, similar startups). APPLICATION PROCESS - Talent Acquisition Interview - Take home task - Hiring Manager Interview - Hiring Team Interview - Offer Decision WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing—at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. OUR COMMITMENT TO DIVERSITY, EQUITY AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com https://www.iceye.com

Location: Москва Вакансия для того, кто хочет строить инновации мирового уровня и видеть реальный след от своей работы. Команда создаёт ИИ-решение для анализа реализации стратегии Сбера. Это кейс на уровне топовых мировых исследований в области сценарного моделирования комплексных экономико-социальных систем и построения предиктивных алгоритмов. Ищем в команду ребят с сильным техническим и концептуальным мышлением и жаждой создавать новое. Обязанности ### Обязанности * сбор, анализ, формализация и согласование требований (функциональные, нефункциональные) * участие в проектировании и анализе архитектуры системы, интеграционных взаимодействий и клиентского пути * формализация требований к AI-функциональности: функциональные требования + требования к качеству ответов LLM и критерии приёмки GenAI фич * верификация и приёмка AI-функционала с учётом недетерминированности * описание требований к агентским сценариям и интеграциям * формализация требований к оценке качества (evals, golden set, процедуры регресса) в постановках для разработки * описание требований к RAG и корпоративной памяти: состав и структура источников, разметка, права доступа, качество данных * подготовка технических спецификаций для команд разработки, консультации в процессе реализации, приемка готового функционала * участие в проведении тестирования разработанного функционала и проведение демонстрации разработанного функционала для заказчика. Требования ### Требования * опыт работы с высоконагруженными системами на позиции системного аналитика от 5 лет * понимание GenAI технологий (LLM, RAG, агенты) и умение формализовать требования к качеству недетерминированных систем * Глубокое понимание микросервисной архитектуры, практический опыт работы с Kafka или другими брокерами сообщений * опыт проектирования баз данных и умение написать SQL запрос средней сложности * понимание методологий проектирования сложных информационных систем, опыт моделирования бизнес-процессов (UML, BPMN 2.0) и построения архитектурных моделей * опыт разработки и документирование API-контрактов (REST, SOAP), проектирование RestApi в Swagger OpenAPI * умение тестировать запросы с помощью инструментов Postman/Insomnia/Swagger * понимание и опыт работы с форматами данных: JSON, YAML, XML, HTML * понимание основ UI/UX. ### Будет плюсом * навык работы в PlantUML * навыки чтения Python и Java кода * опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов. Условия ### 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.

Location: 🇧🇷 São Paulo / 🌎Remote Workplace: Remote A little bit about us: We are Belvo, an open finance API platform with the bold vision of democratizing access to financial services in Latin America. We enable any financial innovator to access and interpret financial data, as well as initiate payments from their end-users accounts. We’re turning the messy complexities of the Latin American financial ecosystem into a modern set of tools to access and interpret data and move money in a seamless and secure way. We’re a highly-technical, passionate, and driven team. We are more than 90 people and our team currently represents 20 nationalities. We have offices in São Paulo and Mexico City – while a large portion of us work remotely. We are tackling a very stimulating problem: connecting fintech innovators with legacy financial infrastructure. We strive to go beyond the limits of what is possible today and to do so in an elegant and developer-first way. Since starting our adventure in May 2019, we have raised $71m from the leading VC investors globally. You can read more about our company here https://belvo.com/about/ and about our team and culture here https://belvo.com/careers/. Also, head to our blog https://belvo.com/blog/ for more news about what we’re building and how we work https://belvo.com/blog/category/working-belvo/. About the team: - We work in cross-functional, autonomous teams. We follow continuous delivery best practices executed on top of a modern technology stack.  - Our products are built for developers, by developers. Technological excellence is at the heart of what we do.   - We are pragmatic and customer-focused. We strive to find the right set of trade-offs in order to validate our hypothesis as early as possible, iterating on our products based on customer feedback.  - We communicate transparently. We do weekly all-hands where we get together to discuss company performance and goals. - While we are global and remote-friendly, we also operate from our vibrant offices in CDMX and Sao Paulo. To accommodate the various time zones in which we are based, we ensure we’re always synced up for at least 3 hours per day. - Also, we are backed by some of the leading investors in Silicon Valley and Latin America, including Founders Fund, Kaszek Ventures, and YCombinator. The challenge The Intelligence Squad is Belvo's AI enabler team. One part of the squad builds the platforms and patterns that let every team at Belvo ship AI. This role sits in the other part: turning the financial data and payments we aggregate across Latin America into models that make real decisions, who looks creditworthy, which transaction is fraudulent, what category a payment belongs to, whether an income statement checks out. That data drives real financial outcomes for the people and businesses on the other end, so the bar for rigor is high. You'll be the data science reference in the squad. We're not hiring someone to execute a modeling backlog someone else wrote. We want someone who decides which problems are worth modeling, defines how we know a model is good enough, and raises the data science bar for everyone they work with. You'll be deep enough in statistics and ML to defend a modeling choice to anyone, whether this is a set of rules to simplify a problem or a complex model that you build. You'll be close enough to the business to turn a commercial problem into a modeling roadmap and a business case. And you'll be a strong enough engineer to take your models from notebook to production and own them there. Responsibilities - Model development and selection: Lead the design of statistical and ML models (classification, regression, ranking, NLP or LLM-based) for problems like risk scoring, fraud detection and transaction categorization. Choose approaches on their merits and defend those choices with data, not habit. - AI-leveraged delivery: Use agentic coding and research tooling as a core part of how you work: exploring data, generating and testing feature hypotheses, scaffolding pipelines, writing the service around the model. We care about the decisions you ship, not hours at the keyboard, and we expect you to keep compressing the gap between the two. - Feature engineering with business context: Work with Product and the business teams to figure out which signals in Belvo's financial data actually explain the outcome you're modeling, and translate an ambiguous business question into a well-scoped modeling problem. - Productionization and ownership: Take models past the notebook. Build or shape the pipelines, APIs and services that run them reliably in production, and own them once they're live: monitoring, drift, retraining, and retirement when the evidence says so. - Experimentation: Design and run experiments (A/B tests and offline evaluation) to confirm that a model change actually moves the metric it's meant to move. - Cross-functional partnership: Work closely with Engineering, Data Research, Product, and the rest of the Intelligence Squad to ship end to end, and with stakeholders across the business to keep your models grounded in what actually matters to them. - Business and customer partnership: Work directly with stakeholders and, when needed, customers. Translate ambiguous business questions into well-scoped problems, and explain trade-offs and impact clearly to non-technical audiences, executives included. - Staying current: GenAI moves weekly. We expect you to be genuinely plugged in: model releases, papers, and tooling, to hold an opinion on what's real versus hype, and to bring the useful parts back to the squad as a demo, a doc, or a session for our company-wide AI Chapter. - Framing the problem: Decide what's worth modeling. Push back when a rule, a heuristic, or a better data pipeline solves the problem without a model, and be willing to kill or retire your own model when the evidence says so. This position may be for you if - 5+ years of experience as a Data Scientist, Applied Scientist, or in a similar hands-on modeling role. - You've owned models end to end in production, from framing the problem to monitoring it live, and you can point to the measurable business impact they had. - You have a solid grounding in statistics and can explain how your models work at that level, not just how to call them. - You've built and compared more than one type of model (for example tree-based methods, regression, deep learning) for the same problem and can justify why you picked the one you shipped. - You're comfortable in Python for data science (pandas, scikit-learn, and at least one of TensorFlow or PyTorch) and in SQL for pulling and shaping your own data. - You've taken several models you built into production yourself, not just handed it off to someone else to deploy.You http://deploy.You understand engineering fundamentals: testing, version control, CI/CD, and how to write code someone other than you can maintain. - You've built with LLMs past the API-call level: tool use or agents, retrieval, structured outputs, and shipped at least one to production. You can explain how you knew it was good enough, which means you've built some form of evaluation, not just eyeballed outputs. - Agentic coding tools are part of your daily workflow, not a novelty. You can walk us through a specific task that used to take you days and now takes hours: how you set it up, what you delegated, and where you still don't trust the output. - You're proficient in written and spoken English. Amazing if - You've worked in fintech, financial risk, or another regulated data environment before. - You have a business or strategy background alongside data science (an MBA, consulting, or a product/strategy role). - You've worked in a customer-facing data science role, such as a forward-deployed engineer or a solutions/applied team at a data platform company. - You've worked with MLOps tooling for model versioning, monitoring, and automated retraining. - You've deployed models on AWS (for example SageMaker or an equivalent managed ML service). - You've written evals or an LLM-as-judge harness for a non-deterministic system, and have opinions about where that approach breaks. - You've used LLMs inside the data pipeline itself: labeling, extraction, categorization, and can say where they beat a classical model and where they quietly don't. Tech stack - Python is our primary language for data science and modeling (pandas, scikit-learn, and deep learning frameworks as needed). - SQL against a cloud data warehouse for data access and feature work.Claude deployed company-wide and Claude Code for every engineer. Agentic tooling is part of how we work daily, not a side experiment. - Cloud infrastructure on AWS, favoring managed services so you can focus on the modeling problem rather than infrastructure plumbing. - An experimentation platform for A/B testing and offline evaluation. - We use Datadog for service observability across the company. - We follow Continuous Integration and Continuous Delivery best practices. Our tech stack: - We’re building our platform using modern technologies, putting the focus on reliability and long-term maintainability - We primarily use Python on the backend. We use battle-tested technologies such as Django, and we are heavy users of Python’s asyncio for some parts of our stack - We use Javascript, Vue.js and Sass on the frontend. We are developing and leveraging our own design system and component library - We run our infrastructure on top of Amazon Web Services, leveraging managed services. We tend to favor the use of managed services wherever possible, in order to focus on our business problems - We observe and monitor our services using Datadog - We follow Continuous Integration and Continuous Delivery best practices Our process steps: At Belvo every hire is so important to us, that we share the decision to hire as a team. - People team chat - Take-home challenge - Challenge presentation - Team fit chat - Meet the founders Our perks: 🚀 Stock options (we are all owners and this is very important to us) 📈 Annual company bonus linked to company performance 🔆 Flexible working hours 🔝 Remote friendly 🐶 Pet friendly 👩🏻‍⚕️ Health Insurance 🎊 Paid time off on your birthday 💻 Renew your laptop every 3 years 🙋 Training Budget 😎 Team building events 🙀 Bank holidays swap within 30 days 🔋 Fitness/ wellness stipends 🚀 Yearly company offsite 🍒 Fresh fruit every week, all-you-can-drink tea and coffee 🏝 Extra days off accrued when completing 2, 3, 4 years and beyond at Belvo 🎳 Yearly department offsite

Location: Valencia Workplace: OnSite Role highlights: - Title: Systems and Software Validation Engineer - Department: Global Manufacturing Organisation - Reports to: Head of MAITE Spain - Location: Valencia, Spain - Type of Contract: Permanent - Working model: On-site - Employment is subject to applicable security screening (incl. SUPO, where required) Why this role matters: As a Systems and Software Validation Engineer, you play a vital role in bringing every satellite that reaches our Valencia production line to operational readiness. You will own the first power-on, initial software and firmware loading, and end-to-end systems verification of fully integrated SAR satellites, running automated functional, power, and bus test campaigns, diagnosing issues at the boundary between software, firmware, and electronics hardware, and ensuring configuration control on final activities. Your work lets test campaigns run independently on the line, without pulling engineers away from other teams. Who We Are ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. Your day-to-day responsibilities - Execute initial satellite power-on, firmware flashing, and subsystem communication verifications. - Run, debug, and execute automated functional, power, and bus test scripts using Python, Shell, and Linux environments. - Work with Git repositories to manage test code, track updates, and verify software builds. - Operate mechanical and electrical ground support equipment (GSE), and troubleshoot electronic hardware, power distribution, and digital interface issues using lab instruments (oscilloscopes, power supplies, multimeters). - Diagnose whether an anomaly is a test setup issue or a genuine unit fault, and raise non-conformance reports (NCRs) in Jira. - Maintain detailed test logs and accurate documentation, and ensure configuration control on final activities. - Assist in managing activities related to satellite launch campaigns. - Actively contribute to continuous improvement initiatives - procedures, processes, tools, test automation, and 6S. - Assist in training and mentoring junior technicians, and communicate proactively with team members and supervisors regarding any challenges or obstacles. - Work closely with the RF Senior Technician, AIT Engineering, and Quality, ensuring clear communication so that satellite build-phase deadlines and technical specifications are met. What we’re looking for Must haves: - Relevant university degree in Aeronautical Engineering, Space Studies, Applied Physics, Electronics, or similar, or equivalent hands-on experience in a related role. - 4+ years of hands-on experience setting up, debugging, and running real test benches and satellite systems or interfaces, not just executing someone else’s scripts. - Proficient in a Linux environment, comfortable modifying and debugging Python scripts, and working with Git. - Systems thinking across avionics, power, and software, enough to tell a test setup fault from a genuine unit fault. - Experience using lab equipment such as power supplies, multimeters, and oscilloscopes. - Excellent communication skills, with particular attention to detail in procedures, preparation, and execution. - Ability to read and interpret technical drawings, assembly instructions, and schematics. - Proficient in English, both written and spoken, to ensure clear communication in a cross-functional environment. Nice to haves: - ICEYE-specific test frameworks, satellite bus specifics, Jira and MES flow, and launch campaign procedures. - Space or satellite AIT (Assembly, Integration, and Testing) background. - Experience with environmental testing (e.g. vibration/shaker rigs, thermal testing). - Experience using Atlassian Cloud (Jira, Confluence). - Lean & Six Sigma experience. Application Process - Talent Acquisition Interview - Hiring Manager General Interview - Technical Interview, including a Technical Challenge - Final Interview Working at ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. How We Work (Our Values) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. Benefits Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. Our Commitment to Diversity, Equity, and Inclusion We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com http://iceye.com.

Nscale is looking for a Senior Network Engineer Deployment to deploy and validate networks for GPU clusters across Europe.

Robinhood is looking for a Senior Software Engineer Web3 Backend to architect and scale backend services and distributed systems for crypto and wallet products.

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the role: We are seeking an exceptional Data Engineer II to join our Engineering team, with a high sense of ownership who is excited about our mission, eager to learn and teach others, and can deliver across the tech stack. The ideal candidate should have experience with a modern data stack and implementations of data pipelines using Python and SQL in AWS. Where you will work: This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Build, optimize, and maintain data pipelines that power our business Define and build out abstracted reusable data sets to be used for Business Intelligence, Marketing, and Data Science Research Design, build, and evangelize a federated data validation framework to be used to monitor potential data inconsistencies Protect our users’ privacy and security through best practices The ideal candidate has: 2+ years of software/data engineering experience (distributed data processing, data warehousing, data governance, Big Data, data variance, data privacy, and data quality). Expertise in SQL and Python Expertise in building scalable data pipelines, query optimization, data modeling, and defining reusable datasets Experience working with orchestration tools (especially Airflow), databases (especially PostgreSQL), data warehouses (especially Snowflake) Familiarity with SQL tuning, medallion/event-driven architectures, and telemetry. Familiarity with healthcare or insurance Familiarity with data security and HIPPA compliance A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time. What you'll get here: You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use: Postgres/SQL, Snowflake, Python, AWS, Terraform, Argo, Airflow, Spark, DuckDB, Iceberg, Airbyte, DBT, ElasticSearch (aka OpenSearch), OpenTelemetry, Looker This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare. Compensation Transparency: The target salary range for this position is $ 138,000 - $160,000 . Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Location: Brussels; Rome; Barcelona; Zug; Porto; Cape Town; Istanbul; Eindhoven; Geneva; Milan; Amsterdam; Manama; Madrid; London; Dubai; Berlin; Antwerp; Copenhagen; Vienna; Prague; Athens; Budapest; Paris; Frankfurt; Dublin; Warsaw; Sofia; Luxembourg; Remote; Zurich; Abu Dhabi; Lisbon; Tallinn; London OR Brussels; Seychelles; Rotterdam; Krakow; Johannesburg; Zagreb SENIOR DATA ENGINEER ABOUT KEYROCK Since our beginnings in 2017, we've grown to be a leading change-maker in the digital asset space, renowned for our partnerships and innovation. Today, we partner with over 250 team members around the world. Our diverse team hails from 42 nationalities, with backgrounds ranging from self-taught DeFi natives to PhDs. Predominantly remote, we have hubs in London, Brussels, and Singapore, and host regular online and offline hangouts to keep the crew tight. We are trading on more than 80 trading venues, and working with a wide array of asset issuers. As a well-established market maker, our distinctive expertise led us to expand rapidly. Today, our services span market making, options trading, high-frequency trading, OTC, and DeFi trading desks. But we’re more than a service provider. We’re an initiator. We're pioneers in adopting the Rust Development language for our algorithmic trading, and champions of its use in the industry. We support the growth of Web3 startups through our Accelerator Program. We upgrade ecosystems by injecting liquidity into promising DeFi, RWA, and NFT protocols. And we push the industry's progress with our research and governance initiatives. At Keyrock, we're not just envisioning the future of digital assets. We're actively building it. ABOUT THE TEAM AND WHY THE ROLE EXISTS The Central Data Team (CDT) is only a few months old, but data has been Keyrock's lifeblood since day one. We're now building the Keyrock Data Platform to give Keyrockers, and the AI agents working alongside them, the data and context they need to act fast and autonomously within agreed boundaries and aligned with our shared goals. Doing that means taking data from across the company and making sense of it in real time for all the functions that depend on it: trading desks, wealth and asset management, product, risk, finance, compliance, and research to name a few. You'd be one of the early hires in CDT and we expect you to contribute to most of the bigger decisions and build work. The standards we settle on and the way the team ends up working are still open. WHAT YOU’LL DO - Build streaming and batch pipelines that ingest, normalise, and distribute market, trading, and portfolio data, resilient to feed and exchange failures. - Build the self-serve tooling (SDKs, patterns, templates, AI agents) so other teams publish, consume, and build on data products without waiting on us. - Own data contracts and schema evolution. Keep schema changes from turning into multi-team coordination events. - Design the lakehouse and time-series layer around consumer query patterns. - Build and evolve the Data Governance and Data Quality Framework: stale-feed detection, schema validation, range checks, idempotent writes, lineage, ownership, self-healing. - Build the derived analytics the business runs on: cross-exchange spreads, VWAP at depth, order book microstructure for the desks; portfolio views, exposure, performance for wealth and asset management. - Make observability, cost, and performance first-class from day one. - Treat infrastructure as code (Docker, Terraform, CI/CD) alongside our Central Infrastructure Team. - Work in the open: write things down, partner closely with Architecture, Infrastructure, Platform, and the rest of the teams. WHAT WE’RE LOOKING FOR Tools matter less to us than how you think about problems. That said, here's the shape of the person we have in mind. Engineering Craft - 8+ years of building production data systems that other people rely on. - Strong proficiency in Python and SQL: not just being able to write a query, but being able to reason about what the engine is doing with it. - Code that's easy for someone else to read, test, and delete later. - Strong understanding of data modelling for both streaming and analytical workloads. - Efficiency, quality, idempotency, and observability are taken seriously by default. Systems Design - You've designed and operated streaming systems on Kafka, Redpanda, MSK, or Kinesis, and you have opinions about partitioning, consumer groups, offsets, and schema registries. - You've used a time-series store in production (ClickHouse ideally; TimescaleDB, QuestDB, or similar are fine too) and can talk about table design as a function of query patterns. - You've worked with a lakehouse architecture and reason about table layout, partitioning, and compaction as design choices that shape query performance and storage cost. - You build for self-healing and idempotency. Reprocessing is safe, retries don't double-write, and the system recovers without a human in the loop. Operational Readiness - Docker, Terraform, and CI/CD are how you work, not a separate "DevOps" thing. - You think about cost and performance early. - You instrument as you build: logs, metrics, and traces are part of the system from day one. - You design for data quality and governance up front covering contracts, validation, lineage, and ownership How You Think and Work - You reason from first principles when a problem is new, stay pragmatic when it isn't, and update your view when you learn more. - You treat the trading desks, wealth and asset management, product, risk, finance, compliance, and research as customers of what you build, and communicate with them that way. - You optimise for outcomes over output. A smaller, simpler thing that ships and works beats a bigger thing that doesn't. - You take ownership end-to-end: design, ship, operate, improve. - You say what you think including when it's an unpopular take. You change your mind when the argument is better. - You make the people around you better. Reviews are real, juniors grow from working with you, and peers want to work with you again. - You're curious about how markets work. Data engineering on its own won't keep you interested here. - You're honest about what you know and what you don't, and quick to close the gap. - You understand financial market data: order books, trades, reference data, portfolios, exposures. Crypto, TradFi, or both are a strong plus. NICE TO HAVE - Lakehouse experience with Apache Iceberg or Delta Lake. - Familiarity with DataHub or similar metadata/lineage platforms. - Rust. Some of our performance-critical services are written in it. Interest is welcome; fluency isn't required. WHAT YOU’LL GET - A from-scratch mandate. You'll be among the first hires in CDT, and the platform, the standards, and the team culture are yours to shape with us. - Strong partners. Close working relationships with Architecture, Infrastructure, Platform, and the desks themselves. You won't be building data in a vacuum. - Autonomy on how you work. Flexible hours, remote-first, business-hours on-call shared across the team. - A competitive salary package, with various benefits. - A team that likes each other. Regular online get-togethers and a yearly onsite where everyone's in the same room. OUR RECRUITMENT PROCESS We’re after those with the right skills and a conscious choice to join our field. The perfect fit? Someone who’s driven, collaborative, acts with ownership and delivers solid, scalable outcomes. As an employer we are committed to building a positive and collaborative work environment. We welcome employees of all backgrounds, and hire, reward and promote entirely based on merit and performance. Due to the nature of our business and external requirements, we perform background checks on all potential employees, passing which is a prerequisite to join Keyrock

We are looking for a Senior Software Engineer II, Applied AI to join our Agentic Systems team, where you'll build AI agents that automate workflows for teams across Wrapbook. Design and build production-grade AI agents with LangGraph that automate multi-step workflows for internal teams across Wrapbook.

Location: Ireland, Dublin Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. We are looking for an experienced Senior Data Engineer to design, develop and operate trusted, scalable data solutions that power decision-making and transformation across Sony Interactive Entertainment (SIE). Working within Enterprise Data Engineering, you will build reusable data pipelines, integration services and curated data products for business domains including Finance, Supply Chain, IT Operations, People & Places, and Sales & Operations. You will partner with engineering, platform, product and business teams, take end-to-end ownership of complex solutions, and raise engineering standards through technical leadership and mentoring. You will help create reliable, governed and AI-ready enterprise data foundations. Responsibilities Design and deliver enterprise data solutions ·       Design, build, test and maintain robust batch and near-real-time data pipelines and ETL/ELT workflows across enterprise systems, APIs, SaaS platforms and cloud data environments. ·       Develop reusable, well-documented data models and domain-aligned data products, translating complex business logic into reliable engineering solutions. ·       Lead technical design for assigned initiatives, evaluate trade-offs, and ensure solutions are scalable, secure, maintainable and cost-effective. Own quality, reliability and operations ·       Own solutions throughout the engineering lifecycle, from requirements and design through deployment, monitoring, incident resolution and continuous improvement. ·       Implement automated testing, data validation, reconciliation, lineage, observability, alerting and operational runbooks. ·       Apply engineering practices including version control, code review, CI/CD, infrastructure automation and appropriate change controls; improve performance and platform efficiency. Provide technical leadership and collaborate ·       Mentor engineers, lead technical reviews and contribute to shared patterns, coding standards and communities of practice. ·       Partner with business stakeholders, architects, security, governance, analytics and platform teams to clarify requirements, dependencies and data ownership. ·       Proactively identify delivery risks, technical debt and cross-team dependencies; communicate progress, options and recommendations clearly. ·       Enable trusted data for analytics, planning, automation and AI use cases while respecting privacy, security and access controls. Skills and Qualifications ·       Typically 6+ years of professional data engineering or software engineering experience, including ownership of complex production data solutions. ·       Strong hands-on SQL and Python skills, with experience in distributed data processing using PySpark and/or Databricks. ·       Experience designing data pipelines and transformations using modern ETL/ELT tools and frameworks, such as dbt, Ab Initio or equivalent technologies. ·       Solid experience with cloud data platforms and warehouses, particularly Snowflake; knowledge of data modelling, dimensional design and data product principles. ·       Experience with orchestration, Git-based workflows, automated testing, CI/CD, monitoring and troubleshooting production data services. ·       Understanding of data security, access management, data quality, governance and regulatory considerations in enterprise environments. ·       Ability to influence technical decisions, mentor peers and communicate effectively with engineering and non-technical stakeholders. ·       Bachelor’s degree in a relevant discipline or equivalent practical experience. Desirable Experience ·       Enterprise integration experience with SAP S/4HANA, financial planning systems, supply chain applications, ServiceNow or HR platforms. ·       Experience with AWS services, APIs, event-driven integration and infrastructure as code. ·       Experience building reconciled financial data, master/reference data or enterprise operational data products. ·       Exposure to AI/ML data preparation, data observability, metadata management and modern data governance practices. ·       Experience working with globally distributed teams and supporting cross-functional transformation programmes. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. €87.800 — €131.800 EUR Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: San Francisco, CA | New York City, NY 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 As a Brand Insights, Measurement Lead at Anthropic, you will strengthen the evidence that fuels our brand decisions: knowing whether marketing spend and effort is working, saying so clearly on a schedule to the people who need to hear it. Marketing Insights turns market, campaign and user data into decisions that product, marketing, comms and sales leadership can act on. You'll tell us, with data, whether awareness is turning into consideration, whether consideration is turning into pipeline, and where that chain breaks down for a given audience. This role sits at the intersection of human understanding, marketing science discipline and organizational influence. In this role, you'll own the team's recurring measurement readouts, including the Prosumer and B2B brand health tracker studies and the metrics, headwinds and tailwinds that show up in front of business leadership and in all-hands updates, keeping them accurate, current and easy to act on. You'll partner closely with your Marketing Insights teammates, Comms and data science on the brand-health dashboard, Brand & Integrated Marketing leadership, brand data science, research vendors, and cross-functional stakeholders across Enterprise Marketing, product marketing and finance. Responsibilities Own the recurring executive and all-hands readouts that put key metrics, headwinds and tailwinds in front of marketing management and the broader team Lead process ownership of the Prosumer and B2B brand health tracker studies, including managing the research vendor relationships that field them Lead coordination across Comms, Marketing and data science on the brand-health dashboard, aligning all three groups on one consistent view of the data Support media mix modeling, multi-touch attribution and incrementality analyses that inform how marketing budget and effort get allocated, moving the team past correlation to a defensible read on what's actually driving outcomes Run best-practice pre- and post-campaign analysis on individual campaigns, covering creative, channel, audience, and timing effects, and turn each read into a specific change for the next campaign Roll up campaign-level learnings into a recurring view for leadership: which channels, creative approaches, and audiences are outperforming over time, and where the team should adjust the playbook next Build audience and funnel analyses that quantify how different audiences move, and relate to each other, from awareness through consideration to conversion, and what that means for where to invest Audit how customer sentiment gets reported across the business and design a more efficient, consistent process Manage the underlying data pipelines so that recurring readouts stay reliable and don't get rebuilt from scratch each cycle Partner with Marketing Insights teammates to keep measurement process and research design in sync, including feeding into the Marketing Business Review scorecard process Develop one defensible view from first-party behavioral data, campaign and media data, and survey or attitudinal research, being clear about what each source can and can't tell you on its own Present findings to non-technical audiences, including marketing leadership, enterprise sales and finance partners, translating hedged results into clear recommendations You may be a good fit if you Have a strategic orientation, strong curiosity for understanding what customers and users think and how to shift perceptions, and can use that to influence business and marketing direction Are fluent in SQL and Python or R, and move comfortably between a quick exploratory pull and a more rigorous statistical model Have designed or analyzed experiments (A/B tests, holdouts, lift tests) to establish a causal effect rather than settle for a correlation, and have applied regression, segmentation or other causal-inference methods to a real business question Have run campaign-level measurement end to end, from a pre/post read on a single campaign to synthesizing learnings across multiple campaigns into a change the team acts on next time Have built and maintained a recurring metrics report or dashboard that executives or cross-functional partners actually rely on, and kept it trustworthy over time Can turn a hedged, caveated finding into a clear recommendation a non-technical stakeholder can act on, and know which caveat matters enough to keep in the headline Start an analysis by pinning down the business question and the decision it needs to serve, not the method that's most interesting to run Can reconcile data with no universal taxonomy across first-party, third-party, real-time and survey sources Know when a directionally correct answer now beats a more rigorous one that arrives too late to matter Work well across functions, building credibility with both technical partners and non-technical leadership Are excited about Anthropic's mission to develop AI that is safe and beneficial Strong candidates may also have Experience with media mix modeling, multi-touch attribution or incrementality and lift testing specifically, rather than general-purpose analytics Experience advising marketing stakeholders on experimental design for live campaigns (email, paid social), or measuring marketing performance across multiple markets Familiarity with survey-based quantitative research (MaxDiff, conjoint, brand and sentiment tracking) alongside behavioral and usage data Experience with a modern data warehouse (Snowflake, BigQuery) and a BI tool (Tableau, Looker, Power BI) Prior experience in marketing, growth or brand analytics specifically, rather than data science in a general or product context A graduate degree in statistics, economics or another quantitative field A career trajectory spanning BI and dashboarding, applied causal inference and experimental design, and multi-market marketing measurement 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: $255,000 — $320,000 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. 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.

-Участие в разработке новых функций и исправлении ошибок в приложениях на Python и Django. -Написание тестов для проверки функциональности кода.