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Location: South Africa; Pakistan; Philippines; Poland; Romania; North Macedonia About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Job Type: Full-time Location: Remote About the Company Our client is a rapidly expanding European business operating in a highly data-centric environment. They are focused on leveraging analytics, technology, and operational efficiency to improve decision-making across commercial, financial, and operational functions. As part of their ongoing digital transformation, they are investing heavily in modern business intelligence infrastructure, advanced reporting capabilities, and enterprise-wide analytics solutions. Job Summary We are looking for a highly analytical and detail-oriented Business Intelligence Analyst to support strategic decision-making through advanced reporting, data modelling, and actionable insights. This role is ideal for someone who thrives in a fast-paced environment and enjoys transforming complex data into meaningful business recommendations. You will play a key role in developing scalable reporting systems, maintaining enterprise data environments, and uncovering trends that drive operational and commercial performance. The ideal candidate brings strong expertise in Power BI, Microsoft Fabric, SQL, Dynamics 365 CRM, and ERP reporting, combined with excellent communication and stakeholder management skills. Key Responsibilities Business Intelligence & Reporting Design, develop, and maintain Power BI dashboards and reporting solutions across sales, finance, operations, inventory, and customer performance metrics Own the full reporting lifecycle, including requirements gathering, data modelling, deployment, testing, and ongoing optimization Ensure reporting accuracy, consistency, scalability, and alignment with business KPIs Manage report scheduling, refresh processes, access permissions, and version control Continuously improve reporting capabilities to support evolving business needs Data Engineering & Analytics Infrastructure Build and maintain scalable data solutions using Microsoft Fabric, including Lakehouses, Dataflows, Data Pipelines, and Warehouses Create optimized semantic models and datasets that enable self-service analytics across teams Support data governance, quality assurance, and data consistency initiatives Collaborate with technical and operational teams to improve integrations and reporting architecture CRM & ERP Data Analysis Analyze Microsoft Dynamics 365 CRM data to provide insights into sales pipelines, customer engagement, and account performance Develop reporting and insights from ERP systems covering purchasing, pricing, inventory, and operational performance Help unify CRM and ERP reporting into a centralized and accurate business intelligence environment Strategic Insights & Forecasting Identify business trends, anomalies, risks, and opportunities through proactive data analysis Deliver recurring insight reports and presentations to leadership teams and stakeholders Support forecasting, scenario modelling, and strategic planning initiatives Provide actionable recommendations that support business growth and operational improvements Stakeholder Collaboration Partner closely with leadership, sales, finance, and operations teams across multiple European markets Translate complex datasets into clear, executive-level insights and recommendations Promote data literacy through documentation, reporting guidance, and stakeholder training Requirements 3–5+ years of experience in Business Intelligence, Data Analytics, or a similar analytical role Advanced experience with Power BI, including data modelling and Power BI Service administration Hands-on experience with Microsoft Fabric, including Lakehouses, Dataflows, Warehouses, and Pipelines Strong SQL skills and experience working with relational databases Experience working with Microsoft Dynamics 365 CRM environments Ability to translate complex analysis into commercially focused business insights Excellent communication, stakeholder management, and presentation skills Experience supporting multi-country or European business operations is highly preferred Knowledge of Microsoft Purview or data governance frameworks Experience with Azure Data Services such as Azure SQL, Synapse, or Azure Data Factory Exposure to predictive analytics, forecasting models, or advanced analytics techniques Background in manufacturing, wholesale, logistics, or distribution industries Familiarity with Power Automate and workflow automation tools Benefits 💰 Competitive salary package based on experience and technical expertise 🌍 Remote-first working environment with flexibility 📊 Work with cutting-edge Microsoft data technologies including Fabric and Power BI 🚀 Join a growing organization investing heavily in analytics transformation 📈 High visibility role with direct impact on strategic business decisions 🤝 Collaborate with senior leaders across European markets 🎯 Opportunity to shape reporting strategy and become a trusted business advisor 📚 Ongoing professional development and learning opportunities

Location: Belgrade, Serbia Workplace: remote At Novakid, we’re building one of the world’s most engaging online English-learning platforms for kids. Today, we serve 100,000+ students and work with 4,000 + teachers across 15+ countries. We’ve already proven the demand. Now we’re scaling the platform, expanding AI-driven learning experiences, and rethinking how our backend should evolve for the next stage of growth. This is where you come in. About the Role Novakid is hiring a Head of Data & Analytics to lead the next stage of our analytics evolution — transforming a strong existing foundation into a modern, AI-enabled decision system that scales with the business. This is a strategic leadership role with broad scope: you'll own the analytics organization, the technology transformation, data science, and the data culture across the company. You won't be starting from scratch — you'll be accelerating a transformation already underway. What You'll Lead Analytics Strategy & Operating Model Define how data and analytics supports growth, product development, commercial performance, and operations. Shape what is self-serve, AI-assisted, automated, and expert-led. Analytics Team Leadership Lead a team of analysts embedded across product squads and business functions. Raise the bar on speed, strategic impact, and self-service enablement while keeping analysts focused on the highest-value work. AI-Powered Analytics Scale practical AI use cases: natural-language data access, AI-assisted insight generation, anomaly detection, automated reporting, and productivity tooling for analysts and stakeholders. Experimentation & A/B Testing Strengthen Novakid's experimentation culture — making it faster and easier to design, launch, measure, and learn from experiments without heavy analyst involvement at every step. Data Science Build a structured, high-impact data science capability spanning ML for business use cases, forecasting, experimentation support, AI-powered product features, and research for new learning experiences. Metric Governance & Data Foundation Drive clearer KPI ownership, stronger documentation, and a trusted semantic layer across Product, Growth, Sales, Marketing, and Finance — reducing ambiguity and conflicting interpretations. What Success Looks Like Faster turnaround on common business questions and broader stakeholder self-service A modern AI-enabled analytics capability adopted across the company A stronger experimentation practice with less dependency on analyst bandwidth Clear KPI ownership and trusted, well-documented data A well-structured data science function supporting both business and product innovation Strong executive confidence in data-driven decision-making What We're Looking For Significant leadership experience in analytics, BI, or data functions within high-growth digital businesses Proven track record transforming analytics toward scalable, self-serve, AI-enabled models Strong technical grounding in modern data stacks, cloud warehouses (we use BigQuery), BI tooling, and semantic modeling Hands-on SQL fluency and solid understanding of analytics engineering principles Experience leading or reshaping embedded analyst teams Practical, hands-on experience applying AI in analytics at scale Experience building or rebuilding a data science function spanning business support and product features What we offer… Fully remote work A chance to shape the future of AI-driven education. A fun, dynamic team that loves building innovative products.Unlimited holidays – because we trust you to deliver. Bonuses and stock options – we grow together

Location: Hong Kong, Hong Kong SAR; Singapore, Singapore Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About The Opportunity The Compliance team's primary objective is to ensure that OKX operates in accordance with regulatory requirements while maintaining the highest ethical and moral standards. The team owns the full compliance engineering stack: KYC onboarding and refresh, sanctions / PEP / adverse-media screening, transaction monitoring (TM) and travel-rule enforcement, case management, and regulatory reporting. We achieve this by developing compliance service solutions, integrating with KYC & AML vendors, and enabling robust business growth, which ultimately strengthens user trust in our platform. Our ultimate goal is to create a culture of compliance excellence, where innovation and responsible business practices are seamlessly integrated. In compliance, a system that is mostly right is wrong — so every control we build must be deterministic in its enforcement, complete in its coverage, and explainable in its outcome. What You’ll Be Doing Formulate, select, and develop technical schemes for platform projects across the compliance domain — KYC onboarding flows, identity verification and refresh, sanctions / PEP / adverse-media screening, transaction monitoring, travel-rule, case management, and regulatory reporting — including AI/ML-powered features such as intelligent screening disambiguation, document verification, anomaly detection, automated risk scoring, and analyst-assist agents. Organize and coordinate resources, leading project research and development, troubleshoot problems, and ensure quality and timely completion — including delivery of AI model integration work within KYC, screening, and monitoring workflows. Facilitate cross-team communication and promote teamwork efficiency through code quality control and collaboration, including partnering with Data Science, Risk, and Legal to productionize models and ensure reliable, auditable inference infrastructure. Define where probabilistic AI is appropriate versus where deterministic logic is mandatory — and design the boundary cleanly so models assist without compromising auditability or enforcement integrity. Undertake team tasks and cultivate technical talents in the industry, with a focus on building AI engineering best practices across the compliance engineering team — patterns for agentic coding, prompt libraries, eval suites, and human-in-the-loop review of AI-generated work in a regulated environment. What We Look For In You A compliance-first systems mindset — you instinctively reach for state machines, idempotency keys, exactly-once semantics, reconciliation jobs and immutable audit logs. You understand that in compliance, false negatives cost millions and false positives cost trust, and you design accordingly. Prior experience in KYC, AML, sanctions, fraud, or payments is a strong plus; experience surviving a regulatory audit is an even stronger plus. Daily, fluent use of modern AI coding tools — Claude Code, Cursor, GitHub Copilot, Codex CLI, or equivalents. You can describe the specific workflows you run, the failure modes you have hit, and the guardrails you have built around AI-generated code. AI fluency is required, not nice-to-have. Production experience integrating AI/ML model inference into Java services — REST/gRPC-based model serving, feature engineering pipelines, latency-sensitive inference optimization, graceful degradation, and drift / rollback playbooks. Hands-on experience with LLM application patterns — at least one of: RAG pipelines (vector store + retrieval + grounding) for policy / KYC / case lookup, agentic workflows (tool use, multi-step reasoning, validation loops) for analyst assistance, or LLM-based classification / extraction shipped to production. Discipline around AI output — you do not ship LLM features without evals, hallucination tests, prompt regression suites, and human-in-the-loop review for high-stakes decisions. You have an opinion on when to reach for a frontier model vs. a fine-tuned small model vs. a deterministic rule, and can defend that trade-off to a regulator. Exposure to LLM integration or AI agent frameworks is a strong plus — e.g. prompt engineering at the system level, RAG pipelines, or orchestrating AI workflows within a regulated environment. Good understanding of software engineering basics, distributed system principles, including CAP, consistency, idempotency, and exactly-once vs at-least-once semantics. Clear logic, quick thinking, and good communication skills — including the ability to write clearly for non-engineers (compliance officers, auditors, regulators). AI Proficiency Expectations & Interview Process AI fluency is a required engineering competency for this role, on the same level as ‘can write good Java’. We will assess it explicitly during the interview, and a strong showing here is a meaningful plus: AI-augmented workflow demo — walk us through how you use AI tools day-to-day. The prompts, the tasks you delegate to an agent vs. write yourself, how you review AI-generated diffs, and how you measure the impact (commit velocity, defect rate, test coverage). Concrete examples beat slogans. Live agentic exercise — a working session using the AI coding agent of your choice on a realistic compliance-flavoured problem. We look at how you scope, prompt, validate, and integrate AI output, not whether the agent gets it right first try. Design discussion with a probabilistic twist — expect at least one system-design question where the right answer involves deciding when not to use an LLM, and how to design the deterministic fallback. We hire engineers who can defend that boundary. Evaluation & guardrails — be ready to discuss an eval suite or guardrail you have built for an AI feature in production (e.g. an LLM-assisted SAR narrative drafting tool, an AI-assisted KYC document review step, or screening-hit disambiguation). If you have not shipped one, tell us how you would design it. Perks & Benefits Competitive total compensation package L&D programs and education subsidy for employees' growth and development — including budget for AI tools, courses, and conferences Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: New York; Ohio; Rhode Island; New Jersey; Delaware; Maine; Maryland; Vermont; North Carolina; Florida; Massachusetts; South Carolina; Virginia; Connecticut; Georgia; Pennsylvania; New Hampshire Workplace: Remote The engineering team at Chainalysis is inspired by solving the hardest technical challenges and building products that establish trust in cryptocurrencies. We're a global organization that thrives on challenging work and doing it alongside exceptionally talented teammates. Our industry evolves rapidly, and our mission is to build a flexible, AI-driven platform that automates entity resolution, optimizes data labeling pipelines, and creates predictive models that identify illicit patterns before they escalate. Our data and solutions have been used to solve some of the world's most high-profile criminal cases and grow consumer access to cryptocurrency safely. Now, by pairing the industry's most trusted blockchain data with agents that reason, investigate, and act, we help our customers scale their workflows as the cryptocurrency economy becomes increasingly mainstream. As a Senior Infrastructure Engineer in the Investigations group, you'll be a technical leader on the Government Systems team — the group responsible for the deployment platform and operational infrastructure that delivers Chainalysis Reactor to government and high-security customers. The mission of the Government Systems team is to ensure that Chainalysis's most security-sensitive customers can run Reactor reliably in their own environments — including networks with strict access controls and limited connectivity. Government Systems sits at the intersection of infrastructure operations and product delivery. Product teams own their application code, but rely on Government Systems to provision environments, manage release pipelines, and operate the deployment platform. As a senior engineer you will be the connective tissue between these groups — setting technical direction, resolving cross-cutting issues, and ensuring the platform evolves to meet growing demands. Note: This position requires eligibility to access U.S. Government information and systems. Due to applicable government security requirements, only U.S. citizens are eligible for this role. Due to collaboration with Europe, we are highly prioritizing candidates based in EST timezone. In this role, you'll: - Lead the design and evolution of RKE2 Kubernetes clusters across development, acceptance, and production environments — driving upgrades, capacity planning, networking strategy, and operational resilience - Architect and maintain infrastructure as code (Terraform) to provision and manage AWS-based environments, establishing patterns and modules that the team can scale with confidence - Own the CI/CD platform (GitHub Actions) end-to-end — designing pipeline architecture, improving build performance, and ensuring releases flow reliably through staged environments - Drive GitOps-based delivery strategy using Flux CD, defining standards for Helm charts and Kustomize overlays and ensuring consistent reconciliation across clusters - Define container image lifecycle policies — building, signing, storing, and distributing images across OCI registries for multiple deployment targets - Identify and eliminate operational toil through automation, improving environment provisioning, configuration management, and deployment processes at a systemic level - Establish and maintain monitoring, alerting, and incident response practices — owning dashboards, runbooks, and post-incident reviews that raise platform reliability over time - Serve as a technical point of contact for product service teams integrating into the deployment pipeline — unblocking teams, troubleshooting complex environment issues, and advocating for infrastructure best practices - Own the security posture of the deployment platform — managing secrets, certificates, RBAC policies, and security configurations to meet compliance and operational security requirements - Mentor and grow other engineers on the team through code review, pairing, design discussions, and knowledge sharing We're looking for candidates who have: - Deep experience operating Kubernetes in production at scale — cluster lifecycle management, Helm, networking, persistent storage, performance tuning, and complex workload troubleshooting - Expert-level proficiency with Terraform for provisioning and managing cloud infrastructure across multiple environments, including module design and state management strategies - Strong Linux systems administration skills (RHEL or similar — networking, storage, systemd, performance analysis, shell scripting) - Extensive experience designing and maintaining CI/CD pipelines (GitHub Actions, Jenkins, or similar), with a focus on reliability, speed, and developer experience - Deep familiarity with AWS services commonly used in infrastructure (EC2, S3, VPC, IAM, EBS, Lambda, and related networking and security services) - A strong operational mindset — you take ownership of reliability, think about failure modes proactively, and build automation to prevent recurring issues before they impact customers Nice to have experience: - Experience with GitOps tools such as Flux CD or ArgoCD in complex, multi-environment setups — including designing promotion strategies and managing drift - Familiarity with container registry operations, image distribution, OCI artifact management, and image signing or verification workflows - Experience managing databases in Kubernetes environments (e.g., PostgreSQL operators, stateful workloads, backup and recovery strategies) - Familiarity with Kafka or other message brokers in a containerized environment, including operational management and scaling - Experience with configuration management or automation tools (Ansible or similar) at fleet scale - Advanced scripting proficiency in Python for infrastructure automation, tooling, and integration work - Experience supporting environments with strict security or compliance requirements (FedRAMP, FIPS, IL environments, or similar) - Exposure to or passion for the cryptocurrency technology ecosystem Technologies we use: - Kubernetes: RKE2, Helm, Kustomize, Flux CD - Cloud provider: AWS (EC2, S3, EBS, VPC, IAM, Lambda) - Infrastructure as code: Terraform - CI/CD: GitHub Actions, semantic-release - Monitoring and alerting: Prometheus, Grafana, Datadog, Humio - Scripting and automation: Shell, Python - Container registries: OCI/Docker - Database management: PostgreSQL - Event streaming: Kafka - Operating systems: RHEL, Rocky Linux, Amazon Linux AI at Chainalysis AI is not a feature at Chainalysis - it is a new way of working. One that turns instructions into work done, and helps us move faster than the threats we're built to counter, and we expect our employees to take ownership of the output and ensure quality. As the world's most trusted blockchain analytics platform, Chainalysis sits at a rare intersection of proprietary data, regulatory relationships and crypto expertise that makes it uniquely placed to shape and lead the next era of AI-driven intelligence - and we expect everyone here, regardless of role, to be an active part of it. AI fluency is tied directly to how we measure performance and how we plan to win. There is no substitute for your own curiosity. We provide the tools, workflows, and space to experiment - but the expectation is that you develop these capabilities yourself, bring ideas, and collaborate across teams to reinvent the way work gets done. We are not using AI to do less. We are using it to do what was never possible before. About Chainalysis Chainalysis is the blockchain data platform, making it easy to connect the movement of digital assets to real-world services. Powered by deep blockchain data and AI, organizations can investigate illicit activity, manage risk exposure, and develop innovative market solutions built on the industry's most trusted blockchain intelligence. Our mission is to build trust in blockchains, blending safety and security with an unwavering commitment to growth and innovation. You belong here.  At Chainalysis, we believe that diversity of experience and thought makes us stronger. With both customers and employees around the world, we are committed to ensuring our team reflects the unique communities around us. We’re ensuring we keep learning by committing to continually revisit and reevaluate our diversity culture. We encourage applicants across any race, ethnicity, gender/gender expression, age, spirituality, ability, experience and more. If you need any accommodations to make our interview process more accessible to you due to a disability, don't hesitate to let us know. You can learn more here https://go.chainalysis.com/rs/503-FAP-074/images/Interview%20Accommodations%20Request.pdf. We can’t wait to meet you.

Location: South Africa; Pakistan; Philippines; Poland; Romania; Spain About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Job Type: Full-time Location: Remote About the Company Our client is a growing European business focused on leveraging data-driven decision-making to improve performance across sales, customer operations, finance, and business strategy. They are investing heavily in modern analytics infrastructure and seek an experienced Business Intelligence Analyst to transform complex data into actionable business insights. Job Summary We’re looking for a highly analytical and technically skilled Business Intelligence Analyst to own reporting, analytics, and business insight generation across a European operation. This is an exciting opportunity for someone passionate about Power BI, Microsoft Fabric, CRM analytics, SQL, and business intelligence reporting. You’ll act as the analytical engine of the business, helping leaders make smarter, data-led decisions through dashboards, forecasting, and strategic insights. This role goes beyond building reports—you’ll proactively identify trends, opportunities, and risks while becoming a trusted partner to leadership teams. Ideal candidates have experience in business intelligence, data analytics, reporting automation, and executive stakeholder engagement. Key Responsibilities Reporting & Dashboard Development Design, build, and maintain Power BI dashboards and reporting solutions for key business metrics. Own the reporting lifecycle from requirements gathering through deployment and ongoing optimization. Manage report accuracy, performance, data refreshes, and KPI consistency. Continuously improve existing reporting assets as business needs evolve. Microsoft Fabric & Data Engineering Build and manage scalable data pipelines using Microsoft Fabric technologies including Lakehouses, Warehouses, and Data Pipelines. Develop semantic models and support self-service analytics initiatives. Ensure data governance, quality, and consistency across systems. Collaborate with technical teams to improve data architecture and integrations. CRM & ERP Analytics Integrate and analyze data from Microsoft Dynamics 365 CRM and ERP platforms. Develop dashboards covering sales pipeline performance, customer activity, account performance, inventory, and operational metrics. Maintain data integrity across multiple systems to provide a unified business view. Business Insights & Strategic Analysis Analyze business trends, anomalies, and opportunities. Deliver regular business insight reports and executive presentations. Identify risks and opportunities before they materially impact performance. Build forecasting models, trend analysis, and scenario planning initiatives. Stakeholder Engagement Partner with leaders across sales, operations, and finance teams. Translate business needs into analytical solutions. Promote data literacy and support self-service reporting initiatives. Document KPIs, reporting logic, and analytical standards. Requirements 3–5+ years of experience in Business Intelligence, Data Analytics, Reporting, or a related field Advanced experience with Power BI including data modeling and dashboard development Strong hands-on experience with Microsoft Fabric Experience with Microsoft Dynamics 365 CRM analytics and reporting Strong SQL skills for querying and data transformation Experience translating complex data into executive-level insights Excellent communication and stakeholder management skills Strong analytical thinking and commercial awareness Experience supporting European or multi-country operations Knowledge of Microsoft Purview and Azure Data Services Forecasting or predictive analytics experience Experience within manufacturing, distribution, or wholesale industries Power Automate exposure for workflow automation Benefits 💰 Competitive salary package based on experience and technical expertise 🌍 Remote-first working environment with flexibility 📊 Work with cutting-edge Microsoft data technologies including Fabric and Power BI 🚀 Join a growing organization investing heavily in analytics transformation 📈 High visibility role with direct impact on strategic business decisions 🤝 Collaborate with senior leaders across European markets 🎯 Opportunity to shape reporting strategy and become a trusted business advisor 📚 Ongoing professional development and learning opportunities

Location: South Africa; Pakistan; Philippines; Poland; Romania; Spain About Huzzle At Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. Job Type: Full-time Location: Remote About the Company Our client is a growing European business operating within a data-driven commercial environment, focused on improving performance through technology, analytics, and operational excellence. They are investing heavily in modern reporting infrastructure and advanced analytics capabilities to drive smarter business decisions across sales, operations, finance, and customer functions. Job Summary We are seeking a highly analytical and technically skilled Business Insights Analyst to become the analytical engine behind a European division. This role is ideal for someone passionate about transforming complex datasets into actionable insights and strategic recommendations. You will build and maintain scalable reporting ecosystems, own end-to-end business intelligence processes, and proactively identify trends that influence growth and performance. The ideal candidate combines strong technical expertise in Microsoft Fabric, Power BI, SQL, Dynamics 365 CRM, and ERP data environments with a commercial mindset and exceptional stakeholder communication skills. Key Responsibilities Reporting Development & Business Intelligence Design, build, and maintain Power BI dashboards and reporting solutions across key business metrics including sales performance, customer trends, inventory, operational efficiency, and financial KPIs. Own the reporting lifecycle from requirements gathering and data modelling through deployment and maintenance. Ensure all reports remain accurate, scalable, and aligned with agreed business KPIs. Manage scheduled refreshes, version control, and enhancements as reporting needs evolve. Data Engineering & Microsoft Fabric Build and manage scalable pipelines using Microsoft Fabric, including Lakehouses, Data Pipelines, Dataflows, and Warehouses. Create semantic layers and optimized data models supporting self-service analytics. Maintain data quality, governance, and consistency across enterprise data assets. Collaborate with IT and engineering teams to improve architecture and integration standards. CRM & ERP Analytics Integrate and analyze Microsoft Dynamics 365 CRM data to provide visibility into customer activity, account performance, and sales pipelines. Develop insights from ERP systems, including purchasing, inventory, pricing, and customer behavior data. Ensure CRM and ERP platforms provide a unified and accurate business view. Strategic Insights & Forecasting Move beyond reporting by proactively identifying trends, anomalies, and performance opportunities. Deliver weekly, monthly, and quarterly insight presentations for senior stakeholders. Flag emerging business risks and opportunities before they become critical. Support strategic planning through forecasting, trend analysis, and scenario modelling. Stakeholder Partnership Work closely with leadership, sales, finance, and operational teams across European markets. Serve as a trusted advisor by translating complex datasets into executive-level recommendations. Promote data literacy through documentation, reporting guidance, and stakeholder enablement. Requirements 3–5+ years of experience in Business Intelligence, Data Analytics, or a related field Advanced expertise in Power BI, including data modelling and Power BI Service administration Hands-on experience with Microsoft Fabric (Lakehouses, Pipelines, Dataflows, Warehouses) Experience working with Microsoft Dynamics 365 CRM Strong SQL skills and experience querying relational databases Proven ability to convert complex analysis into executive-ready business insights Strong communication and presentation skills Experience supporting European or multi-country operations Knowledge of Microsoft Purview Familiarity with Azure Data Services such as Azure Data Factory, Azure SQL, or Synapse Experience with predictive analytics or forecasting models Background in manufacturing, wholesale, or distribution environments Exposure to Power Automate and workflow automation Benefits 💰 Competitive salary package based on experience and technical expertise 🌍 Remote-first working environment with flexibility 📊 Work with cutting-edge Microsoft data technologies including Fabric and Power BI 🚀 Join a growing organization investing heavily in analytics transformation 📈 High visibility role with direct impact on strategic business decisions 🤝 Collaborate with senior leaders across European markets 🎯 Opportunity to shape reporting strategy and become a trusted business advisor 📚 Ongoing professional development and learning opportunities

Location: London, UK About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We run one of the industry's largest AI compute fleets, spanning multiple cloud providers and datacenters, to train, research, and serve frontier AI models. Those fleets run on Kubernetes, and the Kubernetes Platform team owns the control plane that makes them work. We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure. We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow. Key responsibilities Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on Build and maintain custom controllers, operators, and CRDs Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities Collaborate with cloud providers on required features and escalations Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures Minimum qualifications Significant software engineering experience building and operating production distributed systems Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++) Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on Strong written and verbal communication; comfort building consensus with internal stakeholders Preferred qualifications Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents) Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments) Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF 12+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects 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: £325,000 — £485,000 GBP 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.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We run one of the industry's largest AI compute fleets, spanning multiple cloud providers and datacenters, to train, research, and serve frontier AI models. Those fleets run on Kubernetes, and the Kubernetes Platform team owns the control plane that makes them work. We are operating at a scale where the defaults stop working. We own the scheduler and extend it to place topology-sensitive ML workloads across thousands of accelerators at once. We scale the control plane itself — apiserver, etcd, controllers — so it stays responsive as object counts and node counts grow by orders of magnitude. And we build the core cluster services every workload depends on, like service discovery, so they hold up under the same pressure. We make sure the control plane is fast, correct, and always available. Your work will directly determine whether Anthropic can keep reliably and safely training frontier models as our compute footprint continues to grow. Key responsibilities Own, operate, and extend the Kubernetes scheduler for Anthropic's accelerator fleets, including custom scheduling plugins and policies for gang scheduling, topology awareness, and preemption Scale the Kubernetes control plane (apiserver, etcd, controller-manager) to support clusters far beyond typical limits, and find the next bottleneck before it finds us Design, build, and operate core cluster services such as service discovery that every workload in the fleet depends on Build and maintain custom controllers, operators, and CRDs Partner with research, training, and inference to understand workload shapes and turn their requirements into platform capabilities Collaborate with cloud providers on required features and escalations Participate in on-call, lead incident response, and design processes (postmortems, runbooks, SLOs) that help the team avoid repeating failures Minimum qualifications Significant software engineering experience building and operating production distributed systems Proficiency in at least one systems-appropriate language (e.g., Go, Python, Rust, or C++) Deep, hands-on Kubernetes experience (well beyond "user of”) into scheduler, controllers, apiserver, or operating large multi-tenant clusters Demonstrated ability to debug complex issues across the stack, from API behavior down to node and network-level root causes A track record of designing for reliability, correctness, and clear failure semantics in systems other engineers depend on Strong written and verbal communication; comfort building consensus with internal stakeholders Preferred qualifications Experience with Kubernetes internals or contributions: kube-scheduler / scheduling framework, apiserver, etcd, client-go, controller-runtime, or similar Experience building or operating cluster schedulers or batch systems (e.g., Kueue, Volcano, Slurm, or in-house equivalents) Background scaling control planes or coordination systems (etcd, ZooKeeper, Consul, or large DNS/service-mesh deployments) Familiarity with ML infrastructure: GPUs, TPUs, or Trainium; gang scheduling; topology-aware placement; collective networking such as NCCL Experience with GCP and/or AWS, including GKE/EKS internals and Infrastructure as Code Low-level systems experience such as Linux kernel tuning, cgroups, or eBPF 10+ years of relevant industry experience, including time leading large, ambiguous infrastructure projects 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, 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 metrics change quickly. New models, products and pricing land every few weeks, and each one moves the numbers in ways leadership needs to understand and act on quickly. The Finance Analytics & Business Intelligence team is hiring a senior individual contributor to own how finance leadership reviews key business metrics. You'll run the weekly company metrics update and forum, explain what is driving revenue and usage across products, customers and models, and turn open-ended business questions into clear, data-driven answers. You'll also build what makes those answers repeatable and scalable: governed metric definitions, executive dashboards, and Claude-powered workflows for recurring analysis. The work is technical, fast-moving and highly visible, and it spans Finance, Product, Go-to-Market, Data Science and Data Engineering. In this role, you will: Own the weekly company metrics update and forum: shape the story the numbers tell, evolve the structure and content as fast as the business changes Define the metrics that matter: help establish the headline KPIs leadership uses to track the business, and the driver views beneath them. Surface macro trends: explain what is driving growth across products, customers, and channels, and flag leading indicators early Lead deep dives on executive questions: take a broad question from leadership, put a measurement approach around it, and work with partner teams to deliver a clear, defensible answer Track performance against plan: explain where actuals differ from forecast and why it matters Partner across teams: work with finance leadership, product and GTM finance and strategy, data science, and data engineering to agree on how we measure the business, so everyone uses the same numbers. Raise the bar: land narratives in executive forums and up-level the team’s finance analytics practice by example You might be a good fit if you: Have run an executive metrics forum: you've owned a recurring business review for senior leadership, including its structure, content and discussion. Land narratives with executives: your analyses have changed business decisions, and you can simplify for senior leaders without losing rigor Put shape around ambiguity: you’ve personally defined the measurement approach for questions nobody knew how to answer, without waiting for a fully specified ask Stay hands-on at senior scope: you still write the SQL and Python yourself, and you’d rather ship a defensible v1 with honest error bars than wait for perfect data Are inherently curious: you go one level deeper than asked and are energized by how fast models, products, and the market are moving Thrive amid shifting priorities: you juggle multiple fast-moving work streams and stay effective when the plan changes weekly Work fluently with modern tooling: you’re strong at data visualization, use Claude and AI tools as force multipliers in analysis and BI, and can self-serve your own workflows across SQL, Python, dbt, and a cloud warehouse Strong candidates may also have: Significant experience in finance analytics, business analytics or data science, including direct partnership with senior leadership Revenue or growth analytics experience at a usage-based business (cloud, API or marketplace) Ownership of a company or executive business review Experience designing evals or benchmarks for AI models or products Fluency in the LLM model and product landscape Experience with a semantic or metrics layer Dimensional modeling and warehouse design experience (grain, SCDs, point-in-time correctness) Cloud platform experience (AWS, GCP) with orchestration, CI/CD for data, and testing/observability 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: $270,000 — $345,000 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.

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building highload products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. Now we look for a Data Scientist to join our ML team Job Responsibilities Search & Retrieval Develop and improve retrieval pipelines for large-scale production search systems. Work on candidate generation, query processing, matching, filtering, and retrieval strategies. Improve search relevance, result coverage, and overall SERP quality. Analyse failed searches, irrelevant results, zero-result queries, and other search-quality issues. Explore lexical, semantic, behavioural, hybrid, and vector search approaches. Ranking & Relevance Build, train, and optimise ranking models for search and recommendation systems. Develop learning-to-rank solutions using behavioural, content-based, contextual, and real-time features. Design ranking features based on clicks, conversions, popularity, freshness, availability, and user behaviour. Evaluate ranking quality using Precision, Recall, NDCG, MAP, MRR, and related relevance metrics. Optimise models for low-latency inference and investigate relevance degradation, bias, and feedback loops. Recommendation Systems Develop recommendation models and candidate-generation strategies for personalised and non-personalised scenarios. Build recall and ranking stages for multi-stage recommendation pipelines. Work on related-item, complementary-item, next-action, and behavioural recommendation use cases. Develop user, item, session, and contextual representations. Balance relevance, diversity, novelty, coverage, and business constraints. Experimentation & Evaluation Design and run offline and online experiments for search, ranking, and recommendation improvements. Build evaluation frameworks that connect model quality with product and business outcomes. Design and analyse A/B tests using CTR, conversion, engagement, retention, and revenue-related metrics. Create reproducible pipelines for data preparation, model training, evaluation, and comparison. Evaluate model robustness across traffic segments, query groups, user cohorts, and edge cases. ML Pipelines & Collaboration Build end-to-end ML pipelines for feature generation, training, validation, deployment, and monitoring. Work with high-load, real-time, and low-latency production systems. Process large datasets using Python, SQL, batch pipelines, streaming systems, and Kafka. Collaborate with product, backend, data engineering, and MLOps teams to productionise ML solutions. Communicate technical decisions, experiment results, and trade-offs while contributing to ML best practices. You’ll thrive here if you have Strong hands-on experience building production search, ranking, or recommendation systems. Strong Python and SQL skills for machine learning, data processing, and analytical queries. Practical experience with learning-to-rank, candidate retrieval, search relevance, or recommender-system modelling. Experience building and evaluating multi-stage retrieval and ranking pipelines. Strong understanding of search and recommendation metrics, including Precision, Recall, NDCG, MAP, MRR, CTR, and conversion. Experience with feature engineering and behavioural data such as impressions, clicks, sessions, and conversions. Experience with ML libraries such as scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch, or TensorFlow. Experience working with large-scale production systems, distributed data processing, analytical databases, and streaming platforms. Strong understanding of experimentation and A/B testing, with the ability to independently build, and validate ML solutions. That can be a plus: Experience with Elasticsearch, OpenSearch, Solr, Lucene, or another search-engine stack. Experience with vector databases, approximate nearest neighbour search, and hybrid lexical-semantic retrieval. Experience with query understanding, classification, spell correction, synonyms, or query expansion. Experience with DSSM, two-tower models, BERT-based ranking, cross-encoders, or similar neural architectures. Experience with large-scale data and ML platforms such as Airflow, MLflow Conditions We know that great talent deserves great conditions, so here's what you can expect when joining us: EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family. Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. Private medical insurance for you and your family, a corporate mobile plan (unlimited in Cyprus with roaming included), and interest-free support for car purchases. Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus. Mindfulness & well-being support, including psychological assistance with 50% coverage. 50% coverage of school and kindergarten fees for your children. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals, and cycling purchase compensation. Investment in your growth: paid language courses and access to suited-for-you development programs, including conferences, training programs, and coaching to support your professional journey. A culture of recognition: a peer reward program to celebrate your contributions. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free catering in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team buildings, and hackathons—because great work happens in great communities. Recruitment process HR interview (40 min); Technical interview (1.5 hour); Final interview (45 min).

Location: Amsterdam, Netherlands; Berlin, Germany; London, United Kingdom; Madrid, Spain; Munich, Germany; Prague, Czech Republic; Warsaw, Poland At JetBrains, code is our passion. Ever since we started, back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create. We just unveiled JetBrains Central,  a platform for agent-driven software development that connects tools, agents, and infrastructure. It enables automated AI workflows to run, be monitored, and be managed across teams – with clear visibility into results, costs, and performance. JetBrains Central provides three core capabilities: Governance and control: Policy enforcement, identity and access management, observability, auditability, and cost attribution for agent-driven work. Some of these functionalities are already available via the JetBrains Central Console . Agent execution infrastructure: Cloud agent runtimes and computation provisioning that allow agents to run reliably across development environments. Agent optimization and context: Shared semantic context across repositories and projects, enabling agents to access relevant knowledge, and task routing to the most appropriate models or tools. Inside the Professional Services department, we are building a team of Forward Deployed Engineers to help our customers adopt AI-native development with JetBrains Central and enable JetBrains consulting partners to transform their customers’ AI-native software development lifecycle. About the role As a Principal Forward Deployed Engineer, you will work directly with early adopter customers to deploy JetBrains Central platform into complex enterprise environments and help them move from experimental AI usage to governed, scalable AI-native development. You will act as a trusted advisor to customer engineering teams and consulting partners, while also mentoring other Forward Deployed Engineers and helping with complex deployments. In this role, you will help establish best practices for enterprise AI adoption and influence how organizations implement AI-driven software development. This role is often a strong fit for engineers who have previously served as Principal or Staff Engineers, Heads of Engineering, CTOs, or Solutions Architects and who enjoy working directly with customers while staying deeply involved with complex technical systems. This role combines consulting, architecture, and hands-on engineering. Your work in the field will directly influence how our platform evolves and how enterprises adopt AI-driven development. You will work directly with the world’s most innovative companies — our client base includes 420 of the Fortune 500 — ensuring they maximize the value of their JetBrains investments. What you’ll do Deploy JetBrains Central platform into enterprise development environments, CI/CD systems, and internal developer platforms. Help organizations transition from ad-hoc AI experimentation to governed AI-native development workflows. Implement enterprise AI governance, including security policies, access management, and data privacy controls. Enable observability for AI-driven development to help organizations understand their AI usage and its impact on productivity, as well as their code-generation patterns. Design sustainable AI adoption strategies, including usage controls and cost visibility across multiple model providers. Integrate our cloud-based agent execution layer, allowing AI agents to run securely and at scale. Collaborate closely with JetBrains product teams to shape the platform based on real-world deployments and customer feedback. Create delivery frameworks and train JetBrains partners to deliver the desired scope of service. Mentor and support other Forward Deployed Engineers, sharing architectural expertise and helping to scale the team’s deployment practices. You will thrive in this role if you are A consultant at heart who can communicate effectively with both engineers and technical leadership. Able to see the whole picture of the software development lifecycle across developer tools, infrastructure, APIs, and cloud systems. Experienced at integrating complex software systems into enterprise environments. Curious about the future of AI agents and AI-native software development. Comfortable working with early adopters and overcoming ambiguous technical challenges. Motivated to mentor other engineers and contribute to building a new technical discipline. What you will bring Experience in software-related projects, ideally in a customer-facing or consulting environment. Familiarity with Java or Python. Experience building or integrating developer platforms, infrastructure systems, or software solutions. Familiarity with modern development workflows (CI/CD, developer environments, internal developer platforms, etc.). Experience working directly with customers or technical stakeholders. Strong problem-solving skills and the ability to operate in fast-evolving technical environments. Ability and desire to travel to meet customers. These would be a plus, but are not blockers Experience with industry-specific solutions (fintech, telco, retail, etc.) Experience with AI/LLM platforms, agent frameworks, or AI-assisted development tools. Experience in solutions engineering, consulting, or forward-deployed engineering roles. Familiarity with the JetBrains ecosystem or developer productivity tooling. #LI-KP1 We are an equal opportunity employer We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation. 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Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re hiring a Data Engineer to build and scale Baseten’s internal data platform. This role sits at the intersection of data engineering, analytics, and data science, transforming raw product and business data into reliable datasets that power decision-making. You’ll design the data models, pipelines, and analytics infrastructure that enable teams across Product, Engineering, Finance, Marketing, and Sales to understand usage and performance. This includes working with AI inference, infrastructure, and observability data to generate insights about the product, business operations and platform economics. You’ll partner closely with stakeholders to build robust, scalable pipelines, define company-wide metrics that inform strategy and planning. RESPONSIBILITIES - Design and maintain core data models and semantic layers - Develop and orchestrate batch and streaming data pipelines using technologies such as Apache Beam, Kafka, Airflow, or similar frameworks - Analyze inference and infrastructure telemetry, including data from OpenTelemetry, Grafana, and other observability tools - Define and maintain company-wide metrics across product usage, performance, and customer lifecycle - Enable self-service analytics through agents and tools, with well-structured semantic layers and context - Ensure data reliability and quality through testing, documentation, and governance PREFERRED QUALIFICATIONS - Understanding of inference metrics such as latency, throughput, token usage, and model performance - Experience supporting B2B SaaS and/or consumption-based platforms - Application of forecasting and predictive modeling (e.g., ARIMA, Prophet) to business processes BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Porto, Portugal Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Portuguese and fluent in English. Location: Must be based in Portugal. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Netherlands Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Dutch and fluent in English. Location: Must be based in Netherlands. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Japan Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Japanese and fluent in English. Location: Must be based in Japan. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Italy Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Italian and fluent in English. Location: Must be based in Italy. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: Spain Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in Spanish and fluent in English. Location: Must be based in Spain. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.

Location: France Workplace: remote We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance. Responsibilities: Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters. Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus. Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts. Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked. Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall. Draft technical launch readiness justifications (Launch Certification Documentation) for final. Requirement: Language Skills : Native fluency in French and fluent in English. Location: Must be based in France. Education : Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field. Prompt Engineering & AI Expertise : At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning. Data Analysis : Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools. Technical Agility : Ability to quickly learn and master proprietary tools with minimal supervision. Communication : Excellent verbal and written communication skills. Optional / Preferred Skills: Familiarity with enterprise-grade LLM interfaces like the Goose API. Experience in AI model evaluation, data science, computational linguistics, or software engineering. Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows. Linguistic expertise, including an understanding of semantics and logic.