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Staff Ai Security Engineer Jobs

3,415 active opportunities · Updated for October 2026

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Explore current staff ai security engineer jobs. Use filters to narrow by work mode, employment type, experience and date posted.

SA
Scale AI
📍 San Francisco• Full-time• From $302.4K/yr
21 days ago

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

sqlawsgcp
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SA
21 days ago

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

pythonawsrest
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About the Role REMOTE IN INDIA We're looking for a software engineer to build the Kubernetes-native control plane that provisions and runs our GPU inference fleet. You'll design a manifest-driven API where the inference team declares what they need, whether that's a cluster, a model deployment, or a capacity change, and our controllers handle the reconciliation, provider/runtime selection, and lifecycle management underneath, so the inference team never has to know or care which specific serving stack, scheduler, or hardware pool is doing the work. You'll also build the systems that keep the fleet efficient, not just running, including defragmentation and rebalancing logic that consolidates scattered workloads back into contiguous capacity, and scheduling/bin-packing improvements that push GPU utilization up without hurting latency. The core value we're after is decoupling the people building on top of the platform from the operational and runtime complexity underneath, while squeezing more usable capacity out of the same hardware. You'll build the controllers, reconciliation loops, and self-service surface (API/CLI, not tickets) that make that decoupling real, plus the event-driven health, remediation, and utilization systems that keep it running and efficient without a human in the loop. Strong candidates have hands-on experience with Kubernetes controller/CRD patterns, have built or operated a platform API that abstracts multiple backends behind one interface, understand GPU scheduling and capacity efficiency (fragmentation, bin-packing, right-sizing), and think about GPU infrastructure as software to be engineered. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine

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O
16 days ago

About the Team Consumer Monetization builds the experiences and systems that power how customers purchase and pay for OpenAI products. Our scope spans purchasing flows, payments, subscriptions, and billing, along with the shared capabilities that support new products, offers, and distribution channels. We own both customer-facing experiences and the underlying platforms that power them. We partner closely with Product, Design, Growth, Data Science, and engineering teams across OpenAI to make purchasing effective and reliable, and new offerings easier to launch and monetize. About the Role We’re looking for experienced Staff+ engineers to evolve the payments, billing, and subscription capabilities that support OpenAI’s growing product portfolio. You’ll tackle problems where correctness, reliability, and flexibility are essential: supporting new billing requirements, managing the billing lifecycle, synchronizing state across internal systems and external providers, and enabling new products and commercial models. Your work may span several areas based on your expertise and team priorities: Billing and monetization capabilities: Extend billing capabilities and improve integrations and state consistency across systems to support new products and business models. Subscriptions: Orchestrate purchases, renewals, plan changes, cancellations, and recovery, ensuring customers are charged correctly and receive the right benefits. Payments: Expand payment capabilities through processor integrations, routing, and broader payment-method coverage. Risk and integrity: Partner with risk and integrity teams to integrate controls into purchasing flows, reducing abuse while protecting legitimate customer experiences. You’ll help set technical direction while remaining hands-on in implementation and delivery. This is an opportunity to solve complex engineering problems at scale, connect architecture decisions to customer and business outcomes, and help other engineers take on broader ow

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A
Amplitude
📍 San Francisco• Full-time
21 days ago

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Team DevX owns engineering velocity at Amplitude: build systems, CI/CD, developer environments, and internal tooling. We're building a software factory: automated workflows that remove manual bottlenecks from how engineers ship code. The Role We're looking for a Staff Software Engineer – DevX (Hybrid – San Francisco) who bridges infrastructure and application thinking and can accelerate how the whole team develops, tests, and ships in the cloud. You'll set architecture for our developer platform, lead our software factory work, and push our development model toward cloud-first workflows. This is a high-leverage, low-oversight role. You'll own initiatives end to end, from an ambiguous problem to production, and set technical direction for a foundational team. What You'll Do Cloud development platform: Unify and scale our existing loca

ci/cdgitai
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M
Mongodb
📍 Palo Alto• Full-time• From $151K/yr
1mo ago

About Voyage AI Team at MongoDB Voyage AI team in MongoDB is building a best-in-class, general-purpose, domain-specific, and fine-tuned embedding models and rerankers to enable accurate, efficient unstructured data search and retrieval for RAG, recommendation, semantic search, and more. It is backed by a strong team of AI researchers from Stanford, MIT, Berkeley, Princeton, and CMU, who have conducted over five years of cutting-edge research on training embedding models. Voyage AI was acquired by MongoDB recently, and is now integrating the SOTA embedding models with MongoDB's data platform to create powerful end-to-end solutions. We are looking to speak to candidates who are based in Palo Alto for our hybrid working model. Position Overview We are seeking a Staff Research Scientist to join our team and contribute to the development of next-generation AI models. This position offers a unique opportunity to work on challenging problems at the intersection of machine learning research and practical deployment of large neural networks. This role can be based out of our Palo Alto office, or remotely in the United States. Responsibilities Conduct cutting-edge research in artificial intelligence, from frontier LLMs to embedding models and rerankers Innovate in next-generation information retrieval and LLM agent paradigm Collaborate closely with other research scientists and research engineers as well as peers across the organization Qualifications PhD degree in Computer Science or related field A track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications in top venues Strong background in machine learning, deep learning, and natural language processing Experience building complex neural networks for language and visual understanding Capable of conducting rigorous empirical studies to validate theoretical results Excellent leadership, problem-solving, and communication ski

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N
Nuro
📍 Mountain View• Full-time• From $193.9K/yr
1mo ago

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Our software team is growing, and we are looking for talented engineers to join us and be instrumental to one of the following areas: Data Platform, Simulation, and Technical Infrastructure. Data Platform: The Data Platform serves as a comprehensive management system for Nuro AI Driver's data, labels, and metrics, facilitating seamless access functionality. The team focuses on data annotation across various domains, including 2D/3D perception, mapping, behavior trajectory, and language/text. It also handles data ingestion and mining, employing methods such as heuristics and embedding search. Additionally, the platform supports the autonomy evaluation infrastructure by providing detailed introspection. Simulation: The Simulation team builds the simulator that allows us to develop and test our autonomous driving technology in a virtual setting. We work on the core simulator and simulation frameworks, sensor simulation, scena

pythonci/cdmachine learning
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F
Fin
📍 Dublin• Full-time
1mo ago

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Play an active role in hiring, mentoring and career development of other engineers Raise the bar for technical standards, performance, reliability, and operational excellence Identify areas

sqlrestmachine learning
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F
Fin
📍 England• Full-time
1mo ago

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey – from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk for one single system that is designed to meet the needs of modern day support teams. Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Driven by our core values, we push boundaries, build with speed and intensity, and relentlessly deliver incredible value to our customers. What's the opportunity? Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. What will I be doing? Play an active role in hiring, mentoring and career development of other engineers Raise the bar for technical standards, performance, reliability, and operational excellence Identify areas

sqlrestmachine learning
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O
16 days ago

About the Team Consumer Monetization builds the experiences and systems that power how customers purchase and pay for OpenAI products. Our scope spans purchasing flows, payments, subscriptions, and billing, along with the shared capabilities that support new products, offers, and distribution channels. We own both customer-facing experiences and the underlying platforms that power them. We partner closely with Product, Design, Growth, Data Science, and engineering teams across OpenAI to make purchasing effective and reliable, and new offerings easier to launch and monetize. About the Role We’re looking for experienced Staff+ engineers with deep iOS or Android expertise and demonstrated experience contributing beyond mobile to frontend web or backend development. You’ll shape and build purchasing and subscription experiences across mobile applications, web, and supporting product APIs. The work spans improving conversion, performance, and reliability, building reusable components, and enabling new product launches. You’ll combine product judgment with technical depth to set direction, lead initiatives across teams, and remain hands-on through implementation and delivery. Approximately 50% of the work will initially be native mobile development, with the remainder across web and product APIs. We’re looking for engineers who enjoy working across the stack and have concrete examples of doing so professionally. Depth in either iOS or Android is required; experience in both is not required. This role is based in San Francisco, with three days per week in the office. In this role, you will: Architect and build purchasing and subscription experiences across native mobile, mobile web, and supporting product APIs. Partner with Product, Design, and Growth to identify customer needs, prioritize improvements, and shape technical direction for purchasing experiences. Improve conversion, performance, and reliability through experimentation, product analytics, and customer insights

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O
16 days ago

About the Team Consumer Monetization builds the experiences and systems that power how customers purchase and pay for OpenAI products. Our scope spans purchasing flows, payments, subscriptions, and billing, along with the shared capabilities that support new products, offers, and distribution channels. We own both customer-facing experiences and the underlying platforms that power them. We partner closely with Product, Design, Growth, Data Science, and engineering teams across OpenAI to make purchasing effective and reliable, and new offerings easier to launch and monetize. About the Role We’re looking for experienced Staff+ full-stack engineers to shape purchasing experiences and monetization capabilities across OpenAI products. You’ll work across web experiences, product APIs, and shared components, combining strong product judgment with technical depth. The work ranges from improving checkout conversion and performance to enabling new pricing models, offers, and ways for customers to purchase our products. You’ll help identify opportunities, turn ambiguous goals into concrete technical plans, and lead initiatives from exploration through launch. As patterns emerge across products, you’ll develop reusable capabilities that make future launches faster and more consistent. This is a hands-on technical leadership role with substantial ownership over architecture, implementation, and product outcomes. This role is based in San Francisco, with three days per week in the office. In this role, you will: Architect and build purchasing experiences end to end, from frontend interactions through the product APIs and backend integrations that support them. Improve checkout conversion, performance, and reliability through experimentation, product analytics, and customer insights. Develop shared checkout components and monetization capabilities that support new products, pricing models, offers, and distribution channels. Partner with Product, Design, Growth, and Data Science to

REMOTEartificial intelligenceai
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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 DevX team's mission is to build and operate the core developer infrastructure at Robinhood. Our team owns and scales the systems that thousands of engineers rely on daily, partnering with software developers across the company to make development fast, reliable, and cost-efficient. We are a team that takes pride in technical excellence, platform reliability, and building tools that have an outsized impact on engineering velocity across the entire organization! As a Staff Software Engineer on the DevX team, you will serve as a technical leader for our build and developer infrastructure, driving the strategy and execution of the systems thousands of engineers depend on every day. Your work will span our build systems, CI pipelines, and remote development environments, ensuring engineers can code, test, and build with speed, safety, and reliability at scale. You will collaborate with engineering teams across Robinhood to eliminate developer friction, raise the bar for engineering productivity, and shape the long-term direction of our developer ecosystem. This is a high-visibility opportunity to set new standards of engineering efficiency and mentor the next generation of in

pythonvueaws
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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 builders and sharp problem-solvers who are wired to deliver great outcomes. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. The DevX team’s mission is to build and operate the core developer infrastructure at Robinhood. Our team owns and scales the systems that thousands of engineers rely on daily, partnering with software developers across the company to make development fast, reliable, and cost-efficient! As a Staff Software Developer, you will act as a technical leader for our build and developer infrastructure, driving the strategy and execution of the systems thousands engineers depend on every day. Your work will span our build systems, CI pipelines, and remote development environments, ensuring engineers can code, test, and build with speed, safety, and reliability at scale. In this role, you will collaborate with teams across Robinhood to eliminate developer friction and raise the bar for engineering productivity. This is a high-visibility leadership opportunity to shape our developer ecosystem and set new standards of engineering efficiency! This role is based in our Toronto, ON office(s), with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. What you’ll do Architect the long-te

pythonawsci/cd
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Lyft
📍 San Francisco• Full-time
1mo ago

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks. Responsibilities Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries. Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes Drive collaboration and coordination with cross-functional teams

pythonmachine learningai
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S
1mo ago

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. Our Data Analytics and AI org (DAA) is actively seeking a Staff Analyst, GTM Analytics to contribute to building our framework to monitor health of business through metrics analysis. Examples of deliverables include building new assets, QBR, performance and ROI analysis and deep dive. You'll be part of a global team transforming GTM data into actionable intelligence, driving real-time ROI optimization across international markets. This role combines technical expertise with strategic leadership to deliver impactful insights that directly influence our go-to-market strategy and business growth. Working with stakeholders in EMEA, you'll champion data-driven decision making and advance our mission of revolutionizing B2B GTM analytics practices. IN THIS ROLE YOU WILL: Be a Strategic Partner to Leadership: Partner with GTM executives to align analytics initiatives with global business objectives — driving QBRs, shaping investment decisions, and proactively surfacing insights that move the business, not just inform it. Turn Data into Business Outcomes: Go beyond reporting to influence pipeline generation, conversion optimization, and campaign ROI — presenting complex analytical findings to executive stakeholders with clarity and impact. You measure success by decisions changed, n

pythonsqlai
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