Staff Detection Engineer Jobs

P-940 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructure

Staff Software Engineer - Money Team P-940 At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure). As a software engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market. By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem. The impact you

P-940 (Position Location is open to both our Seattle & Bellevue offices.) At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark™, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructu

P-186 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Da

P-186 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. Modern data analysis employs sophisticated methods such as machine learning that go well beyond the roll-up and drill-down capabilities of traditional SQL query engines. As a software engineer on the Runtime team at Databricks, you will be building the next generation distributed data storage and processing systems that can outperform specialized SQL query engines in relational query performance, yet provide the expressiveness and programming abstractions to support diverse workloads ranging from ETL to data science. Below are some example projects: Apache Spark™ : Develop the de facto open source standard framework for big data. Da

P-150 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Our te

P-150 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, writing software in Scala/Java, building data pipelines (Apache Spark™, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform). Below are some example teams you can join: Data Science and Machine Learning Infrastructure: Build services and infrastructure at the intersection of machine learning and distributed systems. Our

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible. We are a leader in the development of innovative DNA sequencing instruments that transform the landscape of genomics. Our flagship products, such as the NovaSeq X and 6K series, drive scientific discoveries across healthcare and biotechnology. Join us and bring your expertise to products that make a difference globally. As a Staff Electrical Engineer in our Lifecycle Management team, you will be a technical leader responsible for overseeing the entire electrical-system lifecycle of our high-performance sequencing products — from New Product Introduction (NPI) through sustaining phases until end-of-life. You will lead and manage technical LCM projects end-to-end, guiding a sub-team of engineers while personally driving the most complex technical investigations. This role demands a dynamic, fast-learning, and highly flexible engineer who can manage component End-of-Life (EOL), drive supplier and design changes, and lead product improvements — all while adhering to our Standard Operating Procedures (SOPs), Work Instructions (WIs), and software/PLM platforms. Critically, you must be comfortable owning the High-Performance Compute (HPC) / Comput

AI Teammates are Asana’s flagship AI innovation - autonomous agents embedded directly into enterprise workflows that reason, act, and proactively drive work forward. The AI Teammates Platform (AITP) team owns the execution engine and platform layer that makes these AI Teammates effective, reliable, and scalable. We build the core systems behind agentic execution: model evaluation and rollouts, proactive detection of blocked work, execution quality infrastructure, tool orchestration, and the platform APIs that power AI across all of Asana engineering. Rather than building a monolithic feature, we build a composable foundation. If a Teammate reasons, acts, or autonomously improves - that’s us. We’re looking for an experienced Staff Software Engineer to drive the technical strategy, architecture, and execution for the AI Teammates Platform. You will bridge the gap between frontier AI capability and enterprise-grade software engineering, operating in close partnership with frontier model providers while building systems that scale to millions of users. If you are passionate about applied AI, agentic orchestration, high-reliability backend systems, and growing high-performing engineering teams, we’d love to hear from you! This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What You’ll Achieve Set the technical strategy for the AI Teammates execution engine, tool orchestration, and platform APIs within Asana, advocating for engineering-driven investments with a vision for keeping our systems flexible, reliable, and maintainable to meet customer needs now and in the future Drive the team to continually and hol

About the role Adobe’s Security Data Platform team builds and operates a petabyte-scale security data lakehouse that turns enterprise telemetry into trusted data for threat detection, investigations, compliance, and security analytics. As a Staff Security Data Engineer, you will own full-system designs and lead critical engineering initiatives across ingestion, storage, governance, orchestration, and data serving. This is a hands-on individual contributor role: you will write and review production code, build infrastructure, define test strategy, fix complex failures, and work with other engineers to deliver the architecture you help shape. You will partner with Security Operations, Threat Intelligence, Compliance, Security Engineering, and infrastructure teams to resolve technical tradeoffs and deliver reliable, cost-effective platform capabilities. Your impact will come through engineering delivery, sound architectural decisions, and helping others become stronger technical leaders. Help us evolve our team from petabyte scale toward exabyte scale! Core responsibilities Platform architecture and engineering Own end-to-end designs that shape the Security Data Platform’s fundamental architecture on Databricks and AWS, using Spark, Delta Lake, and Unity Catalog. Translate ambiguous needs into design proposals, implementation plans, and production capabilities. Build and evolve distributed batch and streaming pipelines for EDR telemetry, network logs, identity events, cloud audit logs, and new security data sources. Design for throughput, fault tolerance, replay, schema evolution, and sub-minute freshness where use cases require it. Write maintainable Python and SQL, develop complex platform features, and refactor unreliable code. Establish reusable engineering patterns, lead code and design reviews, and own test strategy and automation choices across pipelines and infra

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible. Summary The Staff Data Engineer is a seasoned, hands-on engineer who designs, builds, and scales data products on our cloud lakehouse, powering analytics, reporting, and AI/ML across Illumina. We are looking for someone with strong proficiency in Python, SQL, and data modeling, a solid understanding of distributed systems and system design who has built and scaled data products on modern cloud platforms such as Databricks and Snowflake. This is a hands-on, senior individual-contributor role with end-to-end ownership and leadership spanning multiple domains such as Supply Chain, Manufacturing and Quality, including mentoring engineers on our global (India-based) team. Responsibilities Partner across business, AI, and platform teams translating domain needs (e.g., SAP, Manufacturing, Quality) into well-modeled, governed and scalable data products. Design, build, and scale end-to-end data products on Databricks (and interoperating with Snowflake) — from ingestion through curated, analytics-ready datasets following a medallion (Bronze/Silver/Gold) architecture. Develop reusable frameworks, libraries, and

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Job / Role Summary The Staff Engineer owns defined Realtime Defect Analysis (RDA) scope within NAND Technology Development, developing and sustaining advanced defect detection and inspection strategies that accelerate learning, improve yield, and support technology transfer to manufacturing. This role leads defect analysis, inspection recipe and sampling optimization, excursion containment, and cross-functional issue resolution. The position collaborates with Process Integration, Yield, Data Science, Global Manufacturing, and equipment suppliers to strengthen process monitoring, standardize Best Known Methods, and align inspection capability with future NAND technology nodes. Main Responsibilities Own the site-level RDA strategy and annual roadmap aligned with NAND Technology Development nodes. Lead analysis of experimental and production flows to detect, classify, and trend systematic and random defects. Establish, track, and report program health metrics, including baseline he

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. The Package Health Analyst will contribute to the development and execution of package health monitoring, simulation, and characterization activities. This role involves hands-on engineering work in DFT, data analysis, and reliability testing to ensure robust packaging solutions Key Responsibilities Package Health Metrics & Monitoring Define quantitative package health metrics Develop detection mechanisms and monitoring dashboards for continuous health assessment. Perform electrical and mechanical characterization of packages. Inline Defect Characterization Implement real-time defect detection and classification (critical vs. non-critical). Conduct next-level characterization for critical defects and integrate findings into predictive models. Advanced Analytics & Knowledge Base Perform correlation and causation studies between process variables, defect patterns, and reliability outcomes. Build and maintain a structured knowledge base for package health learnings to enable NPI handover and future technodes. End-to-End Traceability </

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 are looking for software engineers to help build safety and oversight mechanisms for our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and support user well-being. This role focuses on the data foundations that make that work possible: the pipelines, stores, and governance controls that our detection, evaluation, and review systems are built on, deployed across AWS, GCP, and Azure. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies. The systems you build sit underneath decisions with real consequences for customers and for people affected by model misuse, and much of the data moving through them is sensitive. Correctness, retention discipline, and access control are core engineering requirements here rather than things bolted on afterward. You will also design for portability from the outset, because these systems run in customer-managed and third-party environments you do not fully control. Key responsibilities Build and operate the data platform that powers Safeguards, including ingestion and processing pipelines, warehouses and other data stores, and the schemas and interfaces that detection and review systems depend on Keep Safeguards systems running day to day and hold a high operational bar that serves both safety and customers, while reducing the manual effort needed to sustain it Own data governance and integrity, including retention and access controls, privacy-preserving handling of sensitive data, lineage, and correctness guarantees

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Engineering owns cost visibility and optimization across Affirm's cloud and AI infrastructure. We're the team that tells the business what it's spending, why it's changing, and what to do about it — from AWS resource waste and tagging strategy to the newer frontier of AI/LLM spend across the company's growing set of AI tools. We treat cost anomalies with the same rigor as production incidents: we've built a severity framework (mirroring Affirm's SEV0–3 incident model but mapped to dollar impact) with defined detection sources, TTD/TTR metrics, and escalation paths, and we operate a clear RACI with partner orgs — we own visibility and alerting, and partner teams own remediation (at times we may dig in deep and own remediation too!), so accountability never gets diffuse. As a Staff Cost Engineer, you'll operate at the intersection of finance, infrastructure, and data engineering — designing the tooling, automation, and processes that scale cost governance across a fast-growing multi-cloud and multi-AI-vendor footprint. You'll set technical direction for the team, influence cost strategy with infra and platform leaders across the org, and turn ambiguous "why did spend spike" questions into durable systems and self-service tooling. We're a small, high-leverage team — you'll have outsized influence on how Affirm thinks about cost. What You'll Do · You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects. · You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed. · You will act as a force-multiplier for your team th