Engineering Manager Linux Team Jobs

Principal/Senior Technician, Global Engineering Labs — Fab 10W, Singapore. Apply via Workday.

Principal/Senior Technician, Global Engineering Labs — Fab 10W, Singapore. Apply via Workday.

Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. About the Role We are actively looking for a talented software engineer to join the Infrastructure team with a focus on improving Engineering Productivity, specifically our Bazel and C++ infrastructure. Example projects include optimizing Bazel, extending and onboarding services to Bazel, improving C++ support through Bazel and our entire infrastructure. This will have a cross-company impact allowing engineers to quickly iterate locally on microservices and firmware. We are committed to a thriving in-office culture. This role requires you to be onsite at our HQ in San Mateo, CA (with flexibility to work from home). What You'll Do Make every engineer’s day-to-day productive and enjoyable! Define engineering tooling roadmap Own Kubernetes deployment and development tooling Build various software and hardware testing frameworks Provide technica

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 We're experts in data, working to make it cost-effective, understandable, and trustworthy. We build pipelines processing billions of events a day and are stewards of canonical data warehouses and datasets delivering products for Stripe Users while embedding with teams to build their data products. We're experts in using the Stripe Data Platform and to scale we lead the data culture and data education to enable product teams to own their data. We invest in AI Data Ops to scale incident handling and serve as an escalation path for data incidents to minimize their impact. The Data Engineering Solutions team works closely with product teams delivering trustworthy data, backend code, and innovative AI tools, platforms, and services for data. What you'll do We're looking for a person who drives the Data Engineering Solutions Team in solving high-impact, cutting-edge data problems. The ideal candidate is someone who has built data pipelines for large-scale volume, is deeply knowledgeable of Data Engineering tools including Airflow, Spark, Kafka, and Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other Stripe teams to understand their use cases and unlock new capabilities. • Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success • Partner with our recruiting team to attract and hire top talent. • Deliver cutting-edg

About the Team The Safety Systems org is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Safety Engineering team builds the platforms and tools that make OpenAI’s models safe to use in the real world. We partner closely with researchers, product teams, and policy to turn safety ideas into reliable, scalable systems: measuring risk, enforcing safeguards, and continuously improving how models behave in production. Our work sits at the intersection of product engineering, data, and AI, and directly shapes how millions of people experience OpenAI’s technology. About the Role We’re looking for a self-starter engineer who loves building products in an iterative, fast-moving environment—especially internal tools that unlock real-world impact. In this role, you’ll build full-stack tooling for our Safety Systems teams that directly improves the safety and reliability of OpenAI’s models, including in sensitive areas like mental health and other vulnerable-user protections. Your work will increase the team’s velocity in identifying and fixing safety issues and help tighten the feedback loop between policy, data, and the model training cycle. In this role, you will: Own the end-to-end development of internal tools that help improve the safety of OpenAI’s models (with a focus on areas like mental health and other vulnerable-user protections) Partner closely with Safety Systems researchers, engineers, and model policy creators to understand workflows, pain points, and requirements—and translate them into durable product solutions Build full-stack experiences to support core model policy workflows, such as labeling and inspecting data, analyzing and reviewing failure cases, and surfacing insights for iteration Optimize internal applications f

Engineer, Product & System Engineering (Media Health Manufacturing), Heterogenous Integration - High Bandwidth Memory — Fab 10A, Singapore. Apply via Workday.

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Data Engineering team builds and maintains the foundational datasets that power decision-making across Robinhood. We design reliable, scalable data systems that support product analytics, growth strategy, financial reporting, experimentation, and machine learning. The team partners closely with Product, Engineering, Data Science, and Finance to ensure accurate, well-modeled data is available to teams across the company. Our work directly influences how Robinhood measures performance, improves customer experience, and scales its products. As a Senior Data Engineer, you will design, build, and evolve core datasets that track product performance and company-wide metrics. You will develop scalable data pipelines that ingest application events and database snapshots into our data lake, ensuring high data quality and reliability. You’ll collaborate with application engineers to improve data generation patterns and with analytics teams to design intuitive, well-documented data models. This is an opportunity to shape the technical foundation that supports data-informed decisions across the organization! This role is based in our Menlo Park, CA office, with in-person attend

WHO WE ARE Edmentum is a dynamic educator and student-focused company dedicated to tech-enabled learning solutions. Our goal is to ensure that all students have access to flexible learning environments and educators have the tools they need to support their students. We are on a mission to create innovative, proven learning technology, partnering with educators to ignite student potential. We are a Remote First organization with a strong commitment to excellence, innovation, and customer satisfaction. What You'll Do As our Automation Engineering Director, you'll lead Edmentum's enterprise capability for workflow automation, internal tooling, business alerting, and low-code and no-code enablement. You'll define the roadmap, design and build the highest-impact solutions yourself, and stand up the standards, governance, and enablement model that let teams across the company scale automation safely. You'll bring AI into the toolkit where it sharpens what automation can do, while keeping solid engineering at the core. You'll partner with Business Systems, Data, Technology, RevOps, Customer Success, Support, Product, and Finance to find where automation can reduce manual effort, sharpen operating visibility, and unlock new ways of working. This is a hands-on builder role with a thought-leadership mandate: you'll be a multiplier, coding when it matters, coaching when it counts, and setting the patterns that make adoption safe and repeatable. If you love turning ambiguous problems into durable, well-engineered solutions, this is your platform to shape how Edmentum works. In this role you will: Define and execute the enterprise roadmap for automation, internal tools, business alerting, and citizen-development enablement, applying AI where it adds value. Design and build workflow automations, integrations, dashboards, and internal tools that interact with Salesforce, ADO/Jira, data platforms, and other enterprise systems. Establish standards for development, QA, release, moni

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director, Platform Engineering Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Role Summary Director, Platform Engineering At Mastercard, the pace of change across technology, AI, and the nature of work requires that we constantly push the boundaries for the technologies in building and operating infrastructure and applications globally. The Director, Platform Engineering is a critical technology and engineering leadership role within Operations Automation Program accountable for advancing our infrastructure and platform automation strategy through innovation and effective problem-solving. This role focuses on analyzing, coding, and delivering software an

Senior Data Scientist, AI Engineering — Dublin, Ireland. Apply via Workday.

Technical Lead, GenAI & Automation Engineering (Risk Engineering) — McLean, VA. Apply via Workday.

Director, Software Engineering & Architecture - FreeWheel — IL - Chicago, 350 N. Orleans St 1300N. Apply via Workday.

Lead Data Scientist, AI Engineering — Dublin, Ireland. Apply via Workday.

Senior Data Scientist, AI Engineering — Dublin, Ireland. Apply via Workday.

Vice President, Software Engineering — Pune, India. Apply via Workday.