Staff Software Engineer - Detection Platform (GoLang)

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 The Core Change Management group is responsible for the systems that let every Stripe engineer ship code, configuration, and infrastructure changes safely and at high velocity. You will be embedded primarily on the Service Deployments team — the owners of Stripe's end-to-end code deployment platform — with regular collaboration with the Resource Automation and Feature Deployments teams. What Makes This Role Compelling You own the foundation of how Stripe ships software. The deployment platform sits in the critical path of every engineer's workflow at Stripe. The decisions you make affect thousands of deploys per day across hundreds of services, directly determining how fast and safely Stripe's product evolves. Technically rich, architecturally active. The team is executing several concurrent platform transformations: containerizing host-based services at scale, adding intelligent multi-service deploy pipelines, extending real-time anomaly detection to earlier stages of traffic shifts, and rebuilding deployment event infrastructure on top of a durable message bus. This is not maintenance work — the architecture is in motion. Broad surface area, real ownership. You will span the full stack from container scheduling and deployment orchestration business logic to the developer-facing internal platform UI. The problems are multi-layered: reliability, developer experience, performance, and safety all at once. Your judgment prevents incidents.

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 . Coinbase's Developer Infrastructure - Test team exists for one reason: every Coinbase engineer should get fast, reliable test signals so the company can test and ship faster. As AI accelerates the pace of code generation, test infrastructure is becoming a critical path for how quickly Coinbase delivers value to customers. As a Staff Software Engineer on the Platform team, you'll set the technical direction for how Coinbase tests and ships software, owning the systems that turn testing into a speed advantage instead of a bottleneck. What you'll do: Define and own the technical strategy for test infrastructure across Coinbase engineering, with feedback speed as a core design constraint. Build and operate core test infrastructure services, including test orchestration, smart test selection, sharding, flaky-test detection, and test result analysis. Drive measurable improvements in test feedback speed and signal reliability so engineers can ship with confidence and without reruns. Own systems end to end, including architecture, observability, SLOs, and on-call operations. Partner with engineering teams across Coinbase to identify bottlenecks and turn them into platform improvements. Mentor engineers, raise technical standards, and shape how the organization approaches test infrastructure. Required Skills and Experience: 10+ years building and operating production so

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 Staff Software Engineer to join our team. This is a Hybrid role, reporting to the Sr. Manager, Software Engineering in the Zscaler Digital Experience (Core Intelligence and Data) department. You will join the team responsible for building the world’s largest cloud security platform, helping us enhance services and increase our global footprint. You will play a pivotal role in enabling organizations worldwide to harness speed and agility through a cloud-first strategy, leveraging our multitenant architecture that serves over 15 million users. What you’ll do (Role Expectations) Own agentic troubleshooting framework, framing high-impact use cases, designing workflows and playbooks, and building processes for all products Evaluate and integrate state-of-the-art GenAI advances to deliver reliable and cost-efficient production features, utilizing LLMs, various machine learning models, data processing, fi

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world's leading data platforms. This is a rare opportunity to define the future of AI-native observability. We are hiring a Staff Frontend Software Engineer on the AI Products team, the team responsible for the most transformative, customer-facing AI capabilities at Observe. You won't just ship features here; you'll set the technical direction for how AI agents, real-time integrations, and developer tooling come together to fundamentally change how engineers operate production sy

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years, fueled by incredible technology and amazing people. Today, we're using the power of AI to define the next era of computing, with our GPU acting as the brains of computers, robots, and self-driving cars. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. NVIDIA is hiring a Staff Engineer to build the company's Enterprise Data Governance platform. This platform spans sensitive-information protection, governed data access across every collaboration and content system at NVIDIA, and the knowledge infrastructure that makes our enterprise AI trustworthy and accurate. What makes this role genuinely hard is the tension at its core: AI agents need broad, deep access to enterprise knowledge to be useful, while export controls, legal constraints, and security policy demand precise, auditable access control. Getting both right, across dozens of systems and one of the most complex enterprise environments in the industry, is the problem this team is solving. We are looking for technically strong engineers across the senior to principal level who thrive on hard infrastructure problems and want to own work that is central to how NVIDIA operates at scale. What You Will Be Doing: Sensitive Information Protection Own the roadmap for sensitive-information detection and remediation, working with Finance, Legal, and Security to define classification models, remediation workflows, and reporting that leadership can trust. Evaluate and integrate ML-based classification approaches to detect sensitive content across unstructured data at scale, and iterate on precision and recall as the data landscape evolves. Governed Dat

Join Adobe Security Engineering and help build the ML and generative AI capabilities that protect Adobe, our products, and our customers. Our team sits where cybersecurity, large-scale data, and AI meet, building models for anomaly detection, threat detection, investigation, and security analytics across some of Adobe's largest datasets. As a Staff Machine Learning Engineer, you'll design, build, and scale production ML systems spanning deep learning, behavioral modeling, embeddings, and agentic AI. You'll write code, train models, run experiments, and help shape the architecture the broader team builds on. You'll also partner closely with data, platform, and security engineers across Adobe. The Challenge Architect end-to-end ML systems for high-volume security data, turning experiments into reusable capabilities. Own the ML lifecycle, from feature engineering through training, deployment, monitoring, and retraining. Build LLM and agentic AI capabilities for security investigation, including retrieval-augmented generation. Design evaluation frameworks that measure model quality and help analysts trust and validate results. Work with data and platform engineers to scale pipelines and resolve system bottlenecks together. Mentor engineers and help guide technical direction through design reviews and hands-on collaboration. What you bring Experience running production ML systems from early experimentation through sustained operation at scale. A strong background training models with PyTorch and transformers, including behavioral modeling and anomaly detection. Comfort with distributed compute like Spark, cloud platforms like AWS, and MLOps tools like MLflow. Experience building with LLMs or generative AI, along with evaluating how they behave in production. Strong Python and SQL skills, and solid software engineering habit