Detection And Mitigation Engineer Jobs

About the Role: Tubi is one of the largest free streaming platforms in the US, serving a large-scale streaming audience across Web, iOS, Android, Roku, Fire TV, Apple TV, and game consoles. Quality at this scale isn't a checkbox — it's a competitive advantage. We're looking for an Automation Engineering Manager to lead the team responsible for building and operating Tubi's multi-platform test automation infrastructure. You will own the strategy, tooling, and execution quality across our client surfaces — from video playback and ad delivery to content discovery and onboarding. This role is for a hands-on technical leader who can set direction, influence cross-functional roadmaps, and stay close enough to the code to guide architecture, review critical implementation decisions, and unblock complex technical issues. You will build a team that ships reliable automation at speed — and you will help the team move toward AI-native automation practices: fluent in AI tooling, proactive about applying it, and disciplined about using it responsibly. This is a hybrid role based out of either our San Francisco or Toronto office. You must be willing to travel to either location at least 2 days a week. What You'll Do: Test Strategy & Quality Planning Define and own Tubi's multi-platform automation strategy — covering Web, iOS, Android, CTV (Roku, Fire TV, Apple TV, Smart TVs, game consoles), and API layers. Establish testing standards, coverage targets, and quality gate policies across the CI/CD pipeline to protect release confidence and production reliability. Design specialized test strategies for business-critical scenarios: video playback (HLS/DASH), ad insertion, content recommendation surfaces, and user authentication flows. Use AI-assisted analysis (e.g., failure pattern clustering, test gap detection) to continuously improve test strategy based on real production signal and defect trends — not gut instinct. Automation Framework & Infrastructure Lead the

Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. As an Engineering Manager, Data, you will lead a multidisciplinary team of ML engineers, data scientists, and data engineers driving some of Truecaller's most strategic initiatives. Your team will be responsible for advancing the trust graph, compounding intelligence, communication experiences, fraud detection, federated learning, calling, search, and the AI Assistant, technologies that sit at the core of Truecaller's strategy. This role combines deep technical leadership with people management: you will define the technical direction across an applied ML stack, foster the growth and well-being of a highly specialized team, and transform a research-driven roadmap into reliable, production-ready systems. What you'll do: Lead, grow, and retain a high-performing team of ML engineers, data scientists, and data engineers, investing deliberately in each person's development and career path. Set technical direction for the core intelligence behind Truecaller’s calling and search intelligence, along with the real-time serving and data platforms that support them. Own team planning, prioritization, and delivery, balancing near-term product commitments against long-term platfo

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Drive the quality strategy for our innovative enterprise storage platform, ensuring zero-downtime resilience across physical hardware and cloud environments like Cloud Block Store and CloudSnap. In this engineering leadership role, you will scale systems testing, feature interoperability, and test automation for mission-critical global applications. Partnering directly with cross-functional development, support, and escalation teams, you will champion a customer-first quality model. This position elevates overall product reliability while shaping how cutting-edge software resilience is delivered at scale. WHAT YOU'LL DO Define & Execute Quality Strategy: Own end-to-end system test designs with a focus on large-scale feature interoperability to guarantee zero-downtime performance across enterprise and cloud environments. Build High-Impact Automation & Tooling: Design and deploy automated test workflows and triage tooling to accelerate defect detection, drastically reducing execution friction across thousands of automated test suites. Simulate Real-World Customer Workflows: Replicate complex customer deployment architectures to validate real-world fault tolerance and overall resilience against failure domains. Drive Root-Cause Resolution: Partner directly with escalation and support engineering teams to analyze and resolve complex defects, utilizing customer feedback loops to eliminate quality gaps. Lead Agi

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Drive the mission-critical quality strategy for the industry’s most innovative, high-performance storage array platform. In this pivotal engineering leadership role, you will scale systems testing, feature interoperability, and test automation to ensure zero-downtime resilience for global enterprise applications. Partnering directly with cross-functional development, support, and escalation engineering teams, you will champion a customer-first quality model across physical hardware and cloud-native environments (Cloud Block Store, CloudSnap). This position elevates product reliability and shapes how cutting-edge software resilience is delivered at scale. WHAT YOU'LL DO Define & Execute Quality Strategy: Ownership of end-to-end system test designs, focusing on feature interoperability at scale to guarantee zero-downtime performance across enterprise and cloud environments. Build High-Impact Automation & Tooling: Design and deploy automated test workflows and triage tooling to accelerate defect detection, drastically reducing execution friction across thousands of automated test suites. Real-World Customer Simulation: Replicate complex customer deployment architectures and enterprise application workflows to validate real-world resilience, fault tolerance, and resilience against failure domains. Root-Cause Resolution & Continuous Improvement: Partner directly with escalation and support teams to reproduc

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. Design and productionize models rather than just prototype them, including

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: The Automation Engineer is responsible for designing, developing, and maintaining security automation solutions that enhance detection, response, workflow efficiency, and operational consistency across Operational Security. Working under the Automation Lead, this role builds high-quality SOAR playbooks, integrations, scripts, AI-assisted workflows, and orchestration pipelines to reduce manual workloads and support the Autonomic Security Operations (ASO) model. What you'll be doing: Core Responsibilities Automation Engineering & Development Develop SOAR playbooks, workflows, and automations for alert triage, enrichment, containment, and remediation. Build scalable, reusable automation components, scripts, and integrations. Implement high-quality scripting using Python, PowerShell, and REST APIs. Ensure appropriate version control, QA, testing, and documentation of automation artefacts. Maintain reliability of automations by monitoring performance, exceptions, and system behaviour. Platform Integration & Tooling Engineering Integrate SOAR with SIEM, EDR, TIP, cloud-native secur

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Scale's internship is not a side project. Interns own real, shipped work on the same roadmaps as full-time engineers, with mentorship from world-class talent and a culture that values ownership, speed, and truth-seeking. Many of our interns return as full-time Scaliens. Example Projects Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing billions of complex tasks Develop new AI infrastructure products to visualize, query, and explore Scale data Requirements A graduation date in Fall 2027 or Spring 2028 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Available for a Summer 2027 internship (May/June start dates) in San Franci

About the Role: We are looking for a Senior DevOps Engineer to join our DevOps team at K Health. You will own and evolve the infrastructure underpinning a healthcare AI platform serving patients and enterprise health system partners. This is a high-ownership role: you will architect and operate cloud environments across K Health and its enterprise partners, lead complex infrastructure migrations, drive disaster recovery programs, and help build the next generation of AI-powered operations tooling. You will also mentor junior engineers and collaborate closely with product and engineering teams across the company. This is a hybrid role based in New York City (4 days/week in office) and includes participation in a daytime on-call rotation. What you will do: Own the design, implementation, and evolution of our GKE-based Kubernetes infrastructure across K Health and enterprise partner environments. Build and maintain our Terraform modular infrastructure library, including reusable modules with automated testing, across GCP, Cloudflare, and AWS. Architect, build, and maintain GitLab CI/CD shared pipeline templates used by all engineering teams (build, test, security scanning, deployment). Own and maintain self-hosted infrastructure software running in-cluster, including GitLab, ArgoCD, Langfuse, DependencyTrack, NGINX Ingress, and others. Implement and support security and compliance controls across infrastructure and the software supply chain - secrets management, pipeline secret detection, container scanning, SOC2 and HIPAA. Drive disaster recovery readiness: design failover scenarios, author runbooks, and lead periodic DR tests. Lead development of AI-powered operations tooling and agentic infrastructure. Monitor, troubleshoot, and improve production system reliability; respond to incidents during on-call shifts. Mentor junior DevOps engineers and establish team-wide engineering standards. What we are looking for: 5+ years of experience in DevOps, platform engineering,

SonicWall is a cybersecurity forerunner with more than 30 years of expertise and is recognized as a leading partner-first company, ensuring our partners and their customers are never alone in the fight against cybercrime. With the ability to build, scale and manage security across the cloud, hybrid and traditional environments in real-time, SonicWall provides relentless security against the most evasive cyberattacks across endless exposure points for increasingly remote, mobile and cloud-enabled users. With its own threat research center, SonicWall can quickly and economically provide purpose-built security solutions to enable any organization—enterprise, government agencies and SMBs—around the world. For more information, visit www.sonicwall.com or follow us on Twitter , LinkedIn , Facebook and Instagram . We are seeking an experienced Principal Software Engineer to lead the architecture, development, and evolution of a large-scale malware analysis and cybersecurity platform. This role will own the end-to-end technical architecture across Python-based analysis pipelines, message-driven job orchestration systems, Windows VM sandbox environments, and web-based interfaces. The ideal candidate brings deep expertise in software engineering, malware analysis, and distributed systems, with a proven ability to take ownership of complex legacy platforms and drive modernization initiatives. You will lead the design and implementation of advanced detection capabilities, including behavioral analysis, malware sandboxing, machine learning-based classification, and support for new file types, while ensuring platform scalability, reliability, and performance. This position requires strong hands-on development skills in Python with Linux-based production environments, messaging architectures such as RabbitMQ, virtualization technologies, and cloud-native deployment practices. As the technical leader for the platform,

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Technical Architect: Company Description Okta is the leading independent identity partner. We enable organizations to securely connect the right people and technologies, providing identity solutions that protect workforce and customer identities across a rapidly evolving technology landscape. The P0 Threat Research organization operates at the intersection of adversary research, threat hunting, detection engineering, data science, and product innovation. Our mission is to understand modern adversaries better than anyone else and make that knowledge actionable for our customers and products. Position Description Architect, Threat Research will help define and drive the technical vision for Okta's threat research efforts. This role is focused on understanding how modern adversaries operate, developing new methodologies for discovering and analyzing attacker behavior, and translating that research into actionable outcomes for our customers and products. Initial areas of emphasis include identity, cloud, SaaS, AI, and other emerging technologies, but success in this role is rooted in deep threat research expertise and the ability to rapidly develop expertise in new technologies and attack surfaces. The Architect will serve as a senior technical leader within the Threat Research organization. This individual will work closely with threat researchers, threat hunters, detection engineers, data scientists, product teams, engineering teams, and other senior t

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Fraud Data team at Plaid builds the machine learning systems that power Plaid’s fraud detection products, leveraging insights from across Plaid’s network to help identify and stop fraud before it happens. Our team works across the full data science and machine learning lifecycle—from discovering new signals and experimenting with models to deploying and optimizing them in production. We continuously learn from real-world model performance and customer feedback to improve our systems and develop new ways to protect customers and consumers from evolving fraud threats. As a Senior Machine Learning Engineer on Plaid's Fraud Data team, you will develop models that improve fraud detection for our customers. You will identify predictive patterns in Plaid's network data and lead projects from initial experiments through model deployment and ongoing improvement. Investigate fraud patterns and model errors to identify new signals, improve detection, and expand coverage across customers and use cases. Develop training datasets and predictive features, addressing challenges such as incomplete labels, class imbalance, data leakage, and changing fraud behavior. Design, train, and tune model

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners. As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features. Responsibilities: Work at the intersection of product analytics, machine learning, and fraud a

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s unique network data to identify and stop fraud before it happens. The team owns the full ML lifecycle—from feature pipelines and model training to production serving and monitoring—building reliable, scalable systems that deliver high-quality fraud detection as we grow to support hundreds of customers. As a Senior Machine Learning Engineer, you will own the development of high-performance feature computation and online inference pipelines that power production machine learning systems at scale. You’ll build robust observability, monitoring, and automated debugging capabilities, while leveraging AI-assisted tools to investigate complex system behavior and maintain high reliability. You’ll partner closely with ML Infrastructure, Data Science, and Product teams to execute critical technical initiatives and deliver scalable, high-impact ML solutions. Responsibilities: Build and scale machine learning systems that power a rapidly growing fraud detection product in a fast-paced environment. Solve complex technical challenges at the intersect

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group, spanning Incident Managers, Investigators, Forward Deployed Security Engineers, and Data Scientists, neutralizes active attacks, gathers requirements for operational tooling, and leads incidents. The team works directly with impacted merchants to resolve incidents and policy abuse rapidly. Operating primarily across Eastern, Pacific and Western European time zones, these team members regularly coordinate with global stakeholders across the world. What you’ll do In this role, you will play a critical part in safeguarding our financial ecosystem by investigating high-risk accounts, identifying complex fraud patterns, performing post-incident analyses, and driving cross-functional improvements to scale fraud detection. Building on these core operational duties, you will leverage your fraud, abuse, or product trust experience to improve incident response capabilities across Stripe by managing the entire fraud and abuse incident response process, developing response plans, leading workstreams, and serving as incident commander to ensure timely resolution. Furthermore, you will conduct gamedays to pressure-test response processes, drive proactive improvements, and help automate response workflows using agentic approaches ensuring we neutralize threats with speed

We are seeking a Senior Software Engineer with strong infrastructure expertise to design, build, and operate the next generation of our enterprise Observability, Automation, and AI-driven Reliability Platform. This role will build highly scalable distributed systems and platform services spanning Storage, Compute, Network, VMware, OpenShift, and bare-metal infrastructure. The engineer will help transform infrastructure operations from reactive monitoring and manual remediation to proactive, predictive, and AI-driven autonomous operations. What You Will Be Doing: Design, build, and operate distributed software platforms for enterprise observability, telemetry, automation, and infrastructure reliability at large scale. Develop reusable platform services, APIs, automation frameworks, and control planes that enable self-service, reduce operational toil, and automate infrastructure operations across multiple engineering teams. Build scalable telemetry and event-processing systems spanning metrics, logs, traces, events, topology, and alerts, with the performance and efficiency to process billions of infrastructure signals. Build intelligent and AI-native reliability capabilities, including agentic workflows for anomaly detection, forecasting, root-cause analysis, automated debugging, and closed-loop remediation. Drive technical architecture and engineering direction across Storage, Compute, Network, and Platform domains, solving complex and ambiguous problems that span multiple teams. Engineer for production at scale, with strong focus on software quality, scalability, security, performance, observability, maintainability, and operational readiness. Provide technical leadership and mentorship, influence engineerin