Applied Risk Standards Specialist Jobs

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role We are looking for a Staff Cryptography Engineer to help lead SoFi’s enterprise readiness for post-quantum cryptography and long-term cryptographic resilience. This role sits within our Security Assurance organization and will partner closely with security, engineering, infrastructure, product, and business stakeholders to assess, modernize, and strengthen cryptographic controls across the enterprise. This is a highly cross-functional and strategic role. The ideal candidate brings deep applied cryptography expertise, strong engineering and architecture judgment, and the ability to drive complex security initiatives in ambiguous environments. You will help build SoFi’s cryptographic inventory, identify where cryptographic keys, protocols, algorithms, certificates, and libraries are used, and guide teams through the implementation of quantum-resistant and crypto-agile solutions. What you’ll do Lead efforts to assess and improve SoFi’s enterprise cryptographic posture, with a focus on post-quantum cryptography preparedness and crypto-agility. Build and maintain an inventory of cryptographic assets, including keys, certificates, algorithms, protocols, libraries, services, and business-critical systems. Partner with product, engineering, infrastructure, cloud, and security teams to identify cryptographi

The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Evaluation & Annotation team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: AI model evaluation both offline and online, designing tooling and processes around human annotation, and establishing the standard around synthetics and AI generated datasets. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Manage and grow the Evaluation & Annotation team, directly managing 4-6 engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: A Software Engineer at heart with a previous experience leading software engineering teams, as a tech lead or people manager Excellent leader with strong interpersonal skills, and the

The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI , LLMObs and all our AI research . As an engineering manager for the Training & Serving team, you’ll join a new and fast growing team and organization. You will support building and scaling the team, define our technical vision and help shape the roadmap. Your team will lead the charge on multiple critical technical challenges: distributed training of foundation models, serving at scale, designing the user experience. You’ll work closely with sister teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org and with Datadog infrastructure & tooling teams to build out systems from the ground up. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Manage and grow the Training & Serving team, directly managing 10+ engineers Define our technical roadmap in alignment with AI platform goals and the Applied AI team roadmap. Work with our core platform teams to tailor Datadog's storage, infrastructure and data pipelines to our needs Create a strong team culture aligned with our engineering standards and our customer focus Participate in hands-on work: Code reviews, design reviews and some coding Who You Are: Previous experience (1+ years) leading software engineering teams, as a tech lead or people manager Strong technician with a mix of backend, data engineer and infrastructure experience who is interested in remaining a hands-on leader Excellent leader with strong

The Detection Platform organization is responsible for helping customers identify, understand, and act on issues across their environments through alerting, event intelligence, and autonomous detection capabilities. As Director, Detection Platform, you will lead a group of engineering managers and teams responsible for foundational alerting infrastructure, event management, monitor creation experiences, and AI-powered detection systems. This role sits at the center of Datadog’s efforts to evolve how customers detect, investigate, and respond to operational issues at massive scale. You will partner closely with Product Management, Applied Science, Design, and Engineering leaders to shape the future of detection and observability experiences for Datadog customers while leading a growing organization of engineers. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Lead a multi-team engineering organization responsible for alerting, event management, monitor creation experiences, and autonomous detection capabilities. Define and execute the technical and organizational strategy for the Detection Platform while aligning stakeholders across Engineering, Product, Design, and Applied Science. Drive innovation in AI-powered detection, anomaly identification, and signal generation that helps customers proactively identify and resolve issues. Scale highly available platform systems that process hundreds of millions of evaluations while maintaining reliability, performance, and operational excellence. Develop and mentor engineering managers and technical leaders, fostering a culture of execution, collaboration, and technical rigor. Champion customer-centric product thinking by balancing platform investments with intuitive user experiences and measurable customer

As Engineering Manager for Threat Detection, you will lead a high-performing team that powers Datadog's detection program. Threat Detection is the organization responsible for keeping Datadog ahead of an evolving threat environment: closing coverage gaps faster, raising the bar on signal quality, and shipping detections that hold up under the scale and complexity of cloud-native infrastructure. Your team will combine direct detection expertise, platform engineering, and applied AI to ship detections at a pace and scale traditional rule-writing alone cannot match. Examples of what your team will work on include detection-authoring agents, the detection platform that powers every rule in production, coverage analysis, alert triage and response automation, and the evaluation infrastructure that holds these systems to a high bar of fidelity. Detection authorship is a shared responsibility across the organization, and your team will contribute both by building the systems that scale our authoring capacity and by writing detections directly when their domain expertise is the right tool. You will partner closely with our Security Incident & Response Team (SIRT), Cyber Threat Intelligence (CTI), AI Engineering teams, and Datadog's broader Security organization. This is a high-impact leadership role: you will grow a team of security and software engineers responsible for building and executing our detection and AI strategy. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead the strategy, roadmap, and execution of Datadog Security's shift to AI-accelerated detection and response. Drive development of high-fidelity detections as a shared responsibility across the organization, ensuring your team's systems and direct contributions raise the bar on coverage and

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in the US or can be based out of any of our US offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent tool's

The Agent Research and Tooling team, part of MongoDB's AI Builder Experience organization, owns the platform layer around agents: how teams author, distribute, evaluate, monitor, and improve agent skills and agent behavior. We are hiring a software engineer to build and maintain the tooling, evaluation systems, and quality gates behind MongoDB's agent skills. This is a software engineering role at the intersection of developer tooling, applied AI, and software quality. You will take loosely defined agent and tooling problems, break them into workable plans, and ship durable internal systems: command-line tools, reusable libraries, evaluation harnesses, and CI workflows. This role is open to remote work in Canada or can be based out of any of our Canada offices. What you'll do Build and maintain agent skills and the infrastructure to validate, evaluate, publish, and maintain them Design evaluation datasets and workflows that compare agent behavior against a baseline and produce actionable quality signals Build agent metrics and observability: skill selection and routing, success and failure outcomes, tool calls, latency, and token usage Design safety and quality gates for agent-authored content: rule packs, static analysis, confidence thresholds, structured verdicts, and bounded suppression Create CLIs, libraries, and MCP integrations that other repositories adopt and that run in local development and CI Integrate tooling into GitHub Actions and other CI workflows, including secrets, annotations, exit codes, and artifacts Build code-generation quality checks, such as anti-pattern catalogs and linting for AI-generated MongoDB code Investigate real failures such as nondeterministic results, false positives, and unsafe generated guidance, and turn them into reusable improvements Collaborate with engineers, security partners, and product teams; communicate trade-offs, risks, and ownership across teams Examples of the problems you'll solve How can tests verify an agent to

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma is seeking a versatile and experienced Machine Learning / AI Engineer to join our growing AI team, working at the intersection of applied machine learning, infrastructure, and product innovation. Whether you’re building intelligent search systems, crafting scalable data pipelines, or enhancing AI-powered creativity tools, your work will drive user productivity, shape new product experiences, and advance the state of AI at Figma. You’ll collaborate closely with engineers, researchers, designers, and product managers across multiple teams to deliver high-quality ML-driven features and infrastructure. This is a high-impact, cross-functional role where you’ll shape both foundational systems and user-facing capabilities. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Design, build, and productionize ML models for Search, Discovery, Ranking, Retrieval-Augmented Generation (RAG), and generative AI features. Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows. Collaborate with AI researchers to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance. Work with product engineers to define and deliver impactful AI features across Figma’s platform. Partner with infrastructure engineers to develop and optimize systems for training, inference, monitoring, and deployment. Explo

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! Figma is a data-driven organization, and Data Platform builds the foundation that makes that possible. The platform powers everything from core business metrics and product analytics to the applied AI and experimentation systems that teams across the company rely on to build and make decisions. In this role, you'll lead engineers across Data Platform through their next phase of scale, setting technical direction, growing the team, and partnering broadly across the company. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you’ll do at Figma: Lead and grow a team of engineers building and operating Figma's data platform, owning delivery, technical direction, and team health Set the roadmap and technical strategy for your sub area, and provide hands on technical leadership where the team needs it Drive the reliability, scalability, and forward strategy of the platform as adoption grows across the engineering and product organization Hire, grow, and coach engineers and tech leads, raising the bar and building a healthy, inclusive, high-performing team Partner with Data Science, Product, Finance, and Engineering to identify the highest-leverage priorities and drive alignment Make sound build versus buy decisions, including evaluating and managing platform vendors where it makes sense Keep delivery predictable while balancing near-term execution with long-term platform investment We'd love to hear from you if you have: 3+ years managing engineers

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. Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust. Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions. This role is ideal for someone who is technically versatile, energized by variety, and wants to see th

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. Lyft is a global company that connects people to transportation to change the way we live and get around our communities. Our drivers and passengers entrust Lyft with their personal information and travel details to get where they are going and expect us to keep that data safe. Lyft's Privacy team is composed of engineers and analysts dedicated to ensuring appropriate data protections are applied to our drivers' and passengers' data. Our goal is to make privacy the default setting for our internal engineers and our customers. We help design architectures, build a scalable data platform, and define policies to reduce the exposure of user data and ensure appropriate privacy and security protections are applied across the company. We are looking for a highly motivated, collaborative, team-focused and technically strong Software Engineer to join our Privacy team. As a member of this team, you will design and build systems that make privacy the default at Lyft. Every day, you'll partner with engineering, product, legal, and compliance stakeholders on high-impact projects — from building data redaction pipelines to enabling users to exercise their privacy rights to deploying data management systems across a diverse set of Lyft services. You'll bring strong engineering instincts, a passion for privacy, and the ability to lead large projects from idea to execution. Responsibilities: Write well-crafted, well-tested, readable, and maintainable code Promote appropriate tech and engineering best practices Partner with teams across Lyft on organizational privacy initiatives Partner with senior engineers to design, build, and maintain systems that enhance privacy across the organization Independently lead tasks from idea to execution Participate in code reviews to ensure code quality and distribute knowledge Parti

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. Lyft is a global company that connects people to transportation to change the way we live and get around our communities. Our drivers and passengers entrust Lyft with their personal information and travel details to get where they are going and expect us to keep that data safe. Lyft's Privacy team is composed of engineers and analysts dedicated to ensuring appropriate data protections are applied to our drivers' and passengers' data. Our goal is to make privacy the default setting for our internal engineers and our customers. We help design architectures, build a scalable data platform, and define policies to reduce the exposure of user data and ensure appropriate privacy and security protections are applied across the company. We are looking for a highly motivated, collaborative, team-focused and technically strong Senior Software Engineer to join our Privacy team. As a member of this team, you will design and build systems that make privacy the default at Lyft. Every day, you'll partner with engineering, product, legal, and compliance stakeholders on high-impact projects — from building data redaction pipelines to enabling users to exercise their privacy rights to deploying data management systems across a diverse set of Lyft services. You'll bring strong engineering instincts, a passion for privacy, and the ability to lead large projects from idea to execution. Responsibilities: Design, build, and maintain systems that enhance privacy across the organization Independently lead large projects from idea to execution Advocate for user privacy throughout the organization, consulting engineering teams throughout the software development lifecycle and escalating potential privacy concerns Write well-crafted, well-tested, readable, and maintainable code Participate in code reviews to ensure code quality

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Relevance & Personalization (R&P) team is Airbnb's matching intelligence engine — a talented team of ML engineers, applied researchers, and technical program managers who connect guests to the right listings across every surface and help hosts compete and thrive in our marketplace. We work at the intersection of search ranking, recommendations, personalization, and generative AI, and we're building toward a future where Airbnb feels less like a search engine and more like a knowledgeable travel companion that understands your needs across your entire trip journey. The Difference You Will Make: As Product Manager for Relevance & Personalization, you will help set the strategy and drive execution for some of Airbnb's highest-leverage AI systems. You'll own the roadmap and shape how personalization works across the guest journey, and help define how we close the feedback loop for hosts. You'll partner with engineers, researchers, designers, and cross-functional teams to ship systems that directly drive bookings, guest satisfaction, and host success — at global scale. A Typical Day: Define and drive the roadmap for Airbnb's relevance and personalization platform — from natural language query understanding to multi-turn, context-aware discovery experiences Make prioritization calls that balance multiple competing objectives: guest experience, host success, revenue, fairness, and marketplace health Partner with ML engineers and applied researchers to shape model strategy, evaluation frameworks, and experimentation design Align cross-functional partners — Guest, Host,

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join The Quality Platform team is at the heart of Airbnb’s mission to deliver a seamless, high-quality experience for millions of hosts and guests. We don’t just find bugs — we build the systems that prevent them. Our team sits at the intersection of Quality Engineering, Infrastructure, and Applied AI . We are evolving how software quality is built by integrating LLMs, intelligent automation, and data-driven systems into the testing lifecycle. You will join a high-impact group of engineers focused on building AI-powered quality systems that scale across one of the world’s most complex codebases. The Difference You Will Make As a Software Engineer , you will play a key role in building and evolving AI-native quality workflows across Airbnb. You will design systems that apply AI directly to the testing lifecycle , helping developers and quality engineers build, validate, and ship high-quality software at scale. In this role, you will: Build AI Agents for the Testing Lifecycle: Design and implement AI agents that support developers and quality engineers across the testing lifecycle — from test case generation and evolution to automation and maintaining test coverage as the codebase changes. Advance AI-Native Quality: Move beyond traditional automation by building systems that continuously adapt test coverage based on code changes and system behavior. Improve Developer and QE Productivity: Identify bottlenecks in testing and CI/CD workflows, and solve them through intelligent automation that reduces manual effort and accelerates feedback loops. Integrate AI into Engineering Workflows: E

Role Description As a Principal Engineer at Dropbox, you will own company critical, loosely defined technical problems with multi year impact, operating at the intersection of technology, product, business strategy, and applied AI. You will define long term technical direction for customer facing experiences used by millions, identifying where AI meaningfully improves customer value and translating evolving business context and industry advances into durable, multi area strategies and roadmaps that shape how Dropbox builds, scales, and innovates, while remaining hands on in software development where it provides the greatest leverage. Your influence will span organizations, setting foundational architecture, driving execution standards, and aligning senior technical and product leaders across boundaries. You will lead the responsible introduction and adoption of AI across product capabilities and engineering workflows, bring clarity to the most complex decisions, institutionalize engineering excellence, and contribute directly through critical design, prototyping, and code reviews. In return, you will operate as a trusted technical partner to senior leadership, shape systems and platforms including AI powered foundations that define Dropbox’s future, and act as a company level technical strategist, advancing Dropbox’s mission to create a more enlightened way of working. Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here . Responsibilities Own and drive technical outcomes across multiple teams and organizations, delivering company critical customer and business impact at scale. Define long term technical strategy and partner with senior Product and Engineering leaders as the technical owner for the most important company objectives. Tackle the most ambiguous and far reaching technical and product problems, shaping w