Detection And Response Jobs

Who we are: Sardine is the leading agentic risk platform for fighting financial crime. Our integrated solution unifies data across risk teams to help organizations stop fraud in real time, prevent AI-driven attacks, and automate fraud and AML operations. Sardine’s platform is strengthened by one of the fastest-growing fraud consortiums in the market, spanning more than 6 billion profiled devices, 800 million consumers, and 3 million businesses worldwide. Leading companies including FIS, GoDaddy, Intuit, Edward Jones, ZoomInfo, and Checkout.com rely on Sardine to secure and grow trust in their products. Our culture: We hire talented, self-motivated individuals with extreme ownership and high growth orientation. We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule. We're a remote-first team spread across time zones, so no office to report to - work from wherever helps you do your best work. Just a couple of things to keep in mind: pay is based on where you're located, and you'll need to keep a home base in the country you're hired in. So while we love the "coffee shop today, mountains tomorrow" life, this isn't a passport-optional, work-from-anywhere-on-Earth kind of remote - think flexible within your country, not borderless. Location: Remote - United States or Canada About the role: As a Machine Learning Engineer at Sardine, you'll own the systems that make real-time fraud detection possible. Our data science team builds custom models for our clients, you build and run the platform they deploy onto, and the low-latency serving path those models score on. Sardine scores millions of sessions in real time from hundreds of device and behavioural signals, inside a sub-250ms budget. That constraint shapes everything: how features are computed and served, how models are deployed and rolled back, how qu

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Principal Threat Researcher to join our team. This is a remote role, reporting to the Manager Threat Research in the Threat Research Team. As our Principal Threat Researcher, you will serve as the definitive subject matter expert on adversary behavior across Endpoint and Cloud environments. You will dissect, replicate, and outmaneuver sophisticated cyber attack techniques to understand exactly how they operate and how to defeat them. By translating complex threat research into concrete, scalable detection recommendations, you will act as the innovation driver for our defensive capabilities. In this pivotal role, your insights won't just live in a whitepaper—they will directly prioritize our engineering efforts, shape product strategy, influence vendor telemetry, and ensure robust, industry-leading protection for our entire customer base. What you’ll do (Role Expectations) Scope and continuously ref

**This role is primarily remote with the expectation of 1 day a month visit to the Cardiff office** At Veriforce, we help companies in high-risk industries keep their people, worksites, and supply chains safe and compliant. As a global leader in contractor and supply chain risk management, our SaaS platform simplifies contractor onboarding, credentialing, and compliance while providing powerful analytics and insights. Beyond software, we offer expert support, training, and consulting so our clients can operate with confidence. Together, we’re making workplaces safer every day. We're hiring an SDET to help deliver reliable, high-quality SaaS solutions at Veriforce. You’ll design and execute manual, automated, and performance tests, validate APIs and integrations, and embed testing into CI/CD pipelines. Leveraging AI/ML for smarter test coverage, you’ll identify issues early, drive continuous improvement, and ensure scalability and security. Collaborating with developers, DevOps, and stakeholders, you’ll play a vital role in delivering seamless, customer-focused solutions while mentoring team members and enhancing testing practices. Define and develop comprehensive test plans in collaboration with scrum teams. Design, document, and maintain functional, integration, security, and performance test cases. Perform manual testing, log defects in Jira, and collaborate with developers for resolution. Build and maintain automated test scripts Playwright. Validate APIs and data flows with tools such as Postman and SQL queries to ensure accuracy and integrity. Integrate automated tests into CI/CD pipelines (e.g., Jenkins, GitHub Actions, Azure DevOps) for continuous quality feedback. Apply AI/ML-driven testing for intelligent test generation, prioritization, anomaly detection, and predictive analytics. Conduct load, stress, and scalability testing to identify and resolve performance bottlenecks. Coordinate and facilitate UAT sessions with stakeholders to validate business requi

JLL empowers you to shape a brighter way . Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Reliability Engineer Overview JLL's Work Dynamics team is seeking a Reliability Engineer to support operations and maintenance of buildings, infrastructure, and equipment assets. Working in collaboration with the Engineering Services Reliability & Asset Management COE, this role implements strategic asset management plans integrating building automation, energy management, maintenance programs, and life-cycle asset management approaches. The position offers growth opportunities, potential to manage junior staff, and support toward globally recognized RAM qualifications. Essential Functions Asset Management Integrates data from BAS, fault detection diagnostics, maintenance programs, and capital planning to develop life-cycle analyses and repair-vs-replace recommendations. Executes site-level Asset Management & Reliability programs, conducts periodic equipment and system audits (safety, compliance, cost savings, energy conservation), and coordinates engineers, technicians, and third-party resources to deliver cost-effective improvements. Reliability Engineering Creates and manages PM task plans for continuous improvement and optimization. Ranks asset criticality using

Who We Are At MongoDB, we are building the future of data platforms with MongoDB Atlas; our fully managed, multi-cloud database service. The Infrastructure Security (InfraSec) team sits within Site Reliability Engineering (SRE) in the CTO organization. We are an engineering team dedicated to building the security infrastructure, primitives, and reusable controls that protect MongoDB Atlas across AWS, Azure, and Google Cloud (GCP). InfraSec operates on a preventative, enabling model: rather than acting as a manual approval gatekeeper or compliance auditor, we develop automated guardrails and platform capabilities. We integrate security directly into the platform runtime, CI/CD, and Infrastructure-as-Code (IaC) workflows so engineering teams can operate securely at scale without friction. This role can be based out of our New York City office or remotely in the eastern or central timezone. What You’ll Do Harden hosts and containerized workloads using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups) and eBPF-based tooling (Cilium, Tetragon) Secure containerized infrastructure across multi-cloud environments via RBAC, network policies, admission controls (Gatekeeper), and runtime threat detection. Build and manage automated services for Cloud Security Posture Management (CSPM), workload identity, vulnerability management, and access controls across AWS, Azure, and GCP Write production-quality code and leverage Infrastructure-as-Code (Terraform) to version, test, and deploy security controls as code Build real-time security monitoring, logging, and alerting systems to detect anomalies and track security posture at Atlas scale Lead initiatives across their full lifecycle; from threat modeling and architectural design to implementation, rollout, and long-term production reliability What We’re Looking For Minimum Qualifications: 5+ years in SRE, Infrastructure Engineering, or Cloud Security Engineering Strong coding skills in Go (Golang), Python, C, C++, or R

Who We Are At MongoDB, we are building the future of data platforms with MongoDB Atlas; our fully managed, multi-cloud database service. The Infrastructure Security (InfraSec) team sits within Site Reliability Engineering (SRE) in the CTO organization. We are an engineering team dedicated to building the security infrastructure, primitives, and reusable controls that protect MongoDB Atlas across AWS, Azure, and Google Cloud (GCP). InfraSec operates on a preventative, enabling model: rather than acting as a manual approval gatekeeper or compliance auditor, we develop automated guardrails and platform capabilities. We integrate security directly into the platform runtime, CI/CD, and Infrastructure-as-Code (IaC) workflows so engineering teams can operate securely at scale without friction. This role can be based out of our New York City office or remotely in the eastern or central timezone. What You’ll Do Harden hosts and containerized workloads using Linux security mechanisms (AppArmor, SELinux, seccomp, cgroups) and eBPF-based tooling (Cilium, Tetragon) Secure containerized infrastructure across multi-cloud environments via RBAC, network policies, admission controls (Gatekeeper), and runtime threat detection. Build and manage automated services for Cloud Security Posture Management (CSPM), workload identity, vulnerability management, and access controls across AWS, Azure, and GCP Write production-quality code and leverage Infrastructure-as-Code (Terraform) to version, test, and deploy security controls as code Build real-time security monitoring, logging, and alerting systems to detect anomalies and track security posture at Atlas scale Lead initiatives across their full lifecycle; from threat modeling and architectural design to implementation, rollout, and long-term production reliability What We’re Looking For Minimum Qualifications: 5+ years in SRE, Infrastructure Engineering, or Cloud Security Engineering Strong coding skills in Go (Golang), Python, C, C++, or R

Banking hasn't changed much in decades. We're changing that. One product at a time. Lunar is a Nordic challenger bank building the future of financial life with AI at the core. Our engineers, designers, and product people work on problems that actually matter. Making money simpler, smarter, and more rewarding for a million of registered users across the Nordics. Fully licensed and founded in 2015, with offices in Copenhagen, Aarhus and Stockholm. We move fast, we build with purpose, and we're just getting started. As our new Fraud Specialist you'll join the FCP Operations team based in Copenhagen, reporting to the Fraud Team Lead, working to protect our customers and keep their money safe. What will you do? Monitor and analyse transactions to identify and act on suspicious activity before it causes harm. Handle fraud cases end-to-end — investigating, documenting, and resolving with care and precision. Collaborate with teams across Lunar to share insights and strengthen our fraud detection capabilities. Stay close to emerging fraud trends and financial crime typologies, applying what you learn in your day-to-day work. Balance security with a great customer experience, making sure protection never comes at the cost of usability. What are we looking for in you? Some experience with fraud, financial crime, or a related field — whether through work, studies, or a strong interest in the space. An analytical mindset with an eye for patterns and anomalies. Clear and structured communication skills — you can explain complex situations simply, both in writing and in conversation. Comfort working in a fast-moving environment where priorities can shift and no two cases are the same. Fluency in Danish or Swedish and English (both spoken and written). Benefits and perks 4 days in the office. We're a team that builds together, thinks together, and moves together. Showing up is part of how we work. State of the art equipment. The newest computer, monitor, mouse, and keyboard. We wa

LilEngine is leading the Lakehouse, a company-strategic effort to make Apache Iceberg a first-class citizen in Spotify's data ecosystem. We're building it in close collaboration with Google, on open standards, so that different kinds of data are queryable the same way and teams can bring the right engine, from BigQuery to Dataflow to Trino, to the job. The work has two parts. Hecate enables Iceberg for the Parquet datasets that already exist across Spotify, so teams get the benefits without rewriting their data. Alongside it, we're building the foundations of a new Lakehouse architecture that lets workflows write Iceberg tables natively. We're shipping the MVP this cycle, and you'll help shape what comes next. We also own BigQuery for all of Spotify. Thousands of engineers, data scientists and pipelines depend on it every day, which puts us on the critical path for storing, finding and querying data. We're judged on reliability, cost efficiency and how quickly we unblock users when something breaks. This backend role sits where open table formats, cloud data warehouses and processing engines meet. What You'll Do Build and evolve the lakehouse: Help build the foundations that let data workflows read and write Iceberg tables directly, from this cycle's MVP to a production-grade platform. Drive adoption: Help migrate data pipelines from across Spotify onto the new stack, making the move as painless as possible through tooling, standards and hands-on support. Own BigQuery at Spotify scale: Manage reservations and capacity, build monitoring and anti-pattern detection, and develop tooling like the BigQuery MCP server so teams can use BigQuery well. Keep the platform healthy: Take part in a weekly support rotation and shared on-call. You'll debug production issues that span storage formats, catalog APIs, Kubernetes reconciliation, GCP IAM and BigQuery internals,

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Senior Software Engineer on the Overseer team within FinHub in the Platform group, you'll build and scale the real-time integrity layer that enforces financial correctness across every Coinbase fund flow. Overseer makes the rules that must always hold between systems explicit, detects violations in seconds rather than quarterly reconciliations, and works with every team at Coinbase that moves money. You'll own workstreams end-to-end, from designing correctness models with partner teams to operating detection systems in production, contributing directly to the platform that keeps billions of transactions accurate and trustworthy. What You'll Do: Build and scale real-time invariant enforcement systems across Coinbase's fund flows, contributing to the core detection engine, invariant framework, and onboarding tooling that partner teams rely on Own workstreams end-to-end, from designing correctness models with partner teams through production operation, ensuring new fund flows are covered by Overseer's integrity guarantees Develop AI-powered guardrails including predictive consistency models that flag deviations at initiation and proactive invariant discovery that surfaces coverage gaps before incidents occur Partner with teams across FinHub, Payments, and Trading to design and implement correctness contracts for new and existing fund flows, translating financial ru

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Staff Machine Learning Engineer, Identity Verification As a Staff Machine Learning Engineer on the Identity Verification team within the Platform group, you'll own the ML systems that determine whether a person, document, and capture session are legitimate. Every signup, account recovery, and high-risk action at Coinbase depends on these models. You'll lead the technical strategy for IDV ML end-to-end, from architecture through production enforcement, protecting the integrity of millions of accounts. What you'll do: Own the full IDV ML stack, including document authenticity models, 1:1 and 1:N face-match, liveness detection, presentation-attack detection, and deepfake/injection detection from feature pipeline through threshold tuning and production enforcement. Build identity-graph systems using GNNs that cluster accounts sharing biometric, device, and document signals to detect synthetic-identity rings and coordinated fraud at onboarding. Develop behavioral and device-intelligence models for capture-session anomaly detection, bot-vs-human classification, and device-fingerprint-based risk scoring at real-time latency. Drive vendor ML strategy by benchmarking external models against a Coinbase-owned evaluation set, designing dynamic routing logic across providers and geographies, and building the in-house evaluation layer that catches regressions befo

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Senior Machine Learning Platform Engineer on the ML Platform team within the Platform group, you'll build the foundational infrastructure that powers feature engineering, model training, and model serving across Coinbase. The platform you build supports fraud detection, user personalization, and blockchain analysis. You'll own critical systems spanning stream processing, distributed training, and highly available inference services, directly shaping how ML scales across the company. What You'll Do: Own the design and reliability of ML inference infrastructure serving both predictive models and LLMs, maintaining high availability and low latency at scale. Build and optimize low-latency streaming pipelines that deliver fresh, high-quality feature data to production ML models. Drive improvements to distributed training infrastructure, enabling ML engineers to process large data volumes efficiently. Develop observability tooling to monitor data quality entering models and detect degradations impacting model performance. Mentor junior engineers on building production-grade software, raising the team's engineering standards over time. Required Skills and Experience: 5+ years of industry experience as a software engineer, with demonstrated ownership of distributed systems in production environments. Built and operated low-latency data or ML infrastructure (stream

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Security is a primary competency at Coinbase, and the Threat Intelligence team within Security Operations keeps a watchful eye over every aspect of it. As a Senior Onchain Investigator, you'll own end-to-end onchain investigations into the threat actors targeting Coinbase and the crypto ecosystem. You'll cluster illicit wallets, fuse OSINT with onchain evidence, and turn findings into detections, blocks, and decisions that protect customers and products. This role leads investigation methodology for the team, not just individual cases. What you'll do: Own complex onchain investigations into threat actor infrastructure, scam networks, exploits, and related abuse targeting Coinbase and Base Drive clustering and attribution of illicit actors using blockchain analytics, OSINT, and internal data, then operationalize results into Vertex Synapse and downstream controls Build OSINT and onchain analysis pipelines, queries, and dashboards that automate detections and scale investigative capacity across the team Lead post-incident reviews and root cause analyses to identify gaps and recommend enhancements to controls, detection, and overall security posture Partner with product, engineering, and risk teams to embed threat and abuse mitigation strategies into the product development lifecycle from ideation to launch Lead new investigative techniques, teach them across Sec

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . This is a 12-week internship during summer 2027. You'll join the People Analytics team within our People Success Function. This team provides intelligence and tools that empower leaders to make key people decisions and drive business value. You'll support analyses across the employee lifecycle, help streamline reporting processes, and contribute to solutions that measure the impact of complex People programs. What you'll do: Analyze People data across the employee lifecycle to identify trends and surface actionable insights for leadership Apply AI tools to accelerate data exploration and enable self-service access to insights for stakeholders Prototype AI-driven workflow automations for recurring reports, anomaly detection, and data-quality checks Support ad hoc data requests by building and maintaining spreadsheets and dashboards Partner with stakeholders to improve dashboard navigation, access, and self-service reporting Collaborate with team members to develop executive presentations that translate data into clear narratives Required Skills and Experience: Currently pursuing a degree or certificate in an analytical discipline (e.g., data science, statistics, I/O psychology, business analytics, or related field). Demonstrated experience analyzing and manipulating data using spreadsheets (Excel, Google Sheets) with the ability to translate findings into action

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As an Infrastructure Lead on the Exchange team within Institutional , you'll own the network infrastructure, deployment, and operational tooling behind a unified trading platform that runs across cloud and on-prem/colocated venues. This team powers the systems that let the world's largest financial institutions trade across markets with speed, depth, and trust. You'll keep latency-sensitive, multi-node trading environments fast, reliable, and easy to build on, shaping trading infrastructure from the ground up with the ownership of a startup and the reach of Coinbase. What you'll do: Own, operate, and optimize resilient, ultra-low-latency networks and physical data-center infrastructure supporting institutional trading, market data, and exchange connectivity across cloud and on-prem environments, including racking, cabling, cross-connects, and vendor coordination. Design and maintain routing, traffic-segmentation, and multicast market-data architectures using BGP, OSPF, VRFs, PIM, IGMP, and high-availability platforms such as Arista MLAG, Cisco vPC, and VRRP. Deploy and operate firewalls and secure connectivity across Fortinet and Palo Alto platforms, including IPsec VPNs, SSL VPNs, and third-party connections. Drive observability and operational excellence through SNMP, gRPC telemetry, latency and packet-loss analysis, microburst detection, and network automation usi

Banking hasn't changed much in decades. We're changing that. One product at a time. Lunar is a Nordic challenger bank building the future of financial life with AI at the core. Our engineers, designers, and product people work on problems that actually matter. Making money simpler, smarter, and more rewarding for millions of people across the Nordics. Fully licensed and founded in 2015, with offices in Copenhagen, Aarhus and Stockholm. We move fast, we build with purpose, and we're just getting started. As our new (Senior) Data Scientist you'll join our team based in Aarhus, reporting to Eugene, our Senior Engineering Manager, working to bring data and machine learning into how we prevent fraud, manage risk, and grow the business. What will you do? Design, build, and deploy machine learning and statistical models across fraud detection, transaction monitoring, loan risk assessment, customer risk scoring, and sales and lead generation Build and operate experimentation and evaluation frameworks — using tools like MLflow and Metaflow — with strong test sets and benchmarks across projects Dive into data analysis and feature engineering to keep pushing model performance further Partner closely with data engineers, analysts, and business stakeholders to define requirements and turn insight into decisions Document models, methodologies, and results clearly, and bring the latest ML and GenAI advances into how Lunar builds What are we looking for in you? Experience developing and deploying machine learning models in a production environment Proficiency in Python and relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) Experience with cloud-based ML platforms such as AWS SageMaker or Kubeflow Solid grounding in machine learning, statistical modeling, and data analysis techniques — experience in financial services or another regulated industry is a plus Strong problem-solving and communication skills, with the ability to translate technical concepts into business in