Senior Security Ai Risk Analyst Jobs

We are looking for an experienced Senior or Staff Engineer for our SRE, InfraSec team, to guide the security of our cloud-based infrastructure. As a Staff SRE, you will be very hands-on technically while also mentoring a small team of SREs. The InfraSec team collaborates closely with other engineering teams to ensure that our infrastructure adheres to the highest security standards. They build essential security infrastructure and implement controls that reinforce the platform’s security posture. This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions.This team is deeply involved in the technical aspects of security and the nuances of its actual implementation. This role can sit in our New York City, Austin, Seattle or San Francisco offices on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones. Responsibilities: Cloud Security Design and Implementation: Help lead the design and deployment of security solutions for cloud platforms (AWS, Azure, GCP), including network and compute security, identity management, and cloud security posture management (CSPM) Automation and Monitoring: Build automated solutions for real-time security monitoring, logging, and alerting in cloud environments. Leverage native cloud services and third-party tools for runtime security monitoring and anomaly detection Security Tooling: Evaluate, implement, and manage cloud-native security tools and platforms for endpoint security, identity management (IAM), and CSPM Qualifications: Experience: 6+ years of experience in SRE, infrastructure engineering or similar role, with a strong focus on security work, with ideally 2+ years in a senior or staff engineering role Security Mindset: A comprehensive understanding of all facets of cloud environment security, spanning from foundational OS networking laye

The Behavior AI team builds the AI-based anomaly detection behind Datadog's security products. Our models learn what normal looks like across the billions of logs, events, and telemetry records flowing through the platform every second, and they flag the behavior that does not fit, on every record, in real time, at a cost that makes sense at our scale. What we build does not ship to a single feature. The same models power detection across many of Datadog's security products at once, so the work has impact well beyond any one team. Large general-purpose models are too slow and too expensive to run in that path, so we take the opposite approach: small, custom models, designed for high-throughput stream processing and optimized to run cheaply on every record. We are hiring a Senior Applied Scientist to build these models from start to finish. You will contribute to designing the architecture, training at scale, and the optimization work that takes a model from training to running efficiently on production traffic. This optimization requires a deep understanding of the constraints imposed by both the software and the hardware, together with the applied mathematics to work within them: often it comes down to finding a mathematical reformulation that fits those constraints better, and that judgment can decide whether a model reaches production at all. The work involves a number of open questions. How do you obtain most of the quality of a large model from one that is far smaller and cheap enough to run on the full stream? Where is it worth trading exactness for speed, and how do you reason about the error you accept? How do you make a small model's outputs clear enough that the detection engineers and analysts who rely on it can trust what it reports? If these are the problems you want to work on, we would like to hear from you. At Datadog, we place value in our office culture: the relationships and collaboration it builds, and the creativity it bring

Job Overview: We are looking for a Senior GenAI Developer to design, build, and productionize agentic AI systems—LLM-powered agents that can plan, use tools, orchestrate workflows, and operate reliably under enterprise constraints. You will own key parts of the agent architecture (planning, tool use, memory, evaluation, safety/guardrails, and observability) and deliver end-to-end solutions across RAG, function/tool calling, multi-agent coordination, and scalable deployment. Key Responsibilities Design and implement agentic systems: single-agent and multi-agent architectures (planner/executor, supervisor-worker, routing, reflection, critique, task decomposition). Build robust tool-using agents: function calling, tool schemas, tool authorization, retries, rate limiting, and sandboxing. Implement RAG + memory patterns: retrieval strategies, hybrid search, context assembly, long-term memory, and grounding/citation behaviors. Develop workflow orchestration for agent execution (state machines/graphs), concurrency controls, and deterministic execution where possible. Productionize GenAI services: APIs, background jobs, streaming responses, caching, and cost/latency optimization. Establish agent evaluation: golden sets, simulation-based evals, LLM-as-judge with mitigations, task success metrics, regression testing. Build observability and safety: tracing, token/tool telemetry, anomaly detection, prompt injection defenses, data leakage prevention, policy enforcement. Collaborate with product, security, and platform teams to deliver enterprise-ready solutions and integrate with internal systems (data, identity, workflow). Mentor engineers, set coding standards, and contribute to architecture reviews and technical roadmaps. Required Qualifications 6+ years software engineering experience; 2+ years building LLM/GenAI systems in production. Strong programming skills in Python (required) and/or TypeScript/Node.js. H

Become a part of our caring community The Senior Full Stack Engineer Performs software engineering activities in all layers of the stack, from setting up the database to programming in the back-end and the appearance at the front-end. The Senior Full Stack Engineer work assignments involve moderately complex to complex issues where the analysis of situations or data requires an in-depth evaluation of variable factors. As Centerwell builds its AI engineering function from the ground up, we need a platform foundation strong enough to support everything that comes next. As Lead Full-Stack Engineer focused on platform and API engineering, you will design and build the service layer that connects AI capabilities, data systems, and product frontends—setting the standards for how services are built, secured, and operated across the team. You will work with meaningful architectural scope, making decisions that span API design, security patterns, and deployment practices. The platform you build will serve care teams and patients across hundreds of Centerwell clinics. If you want to build platforms that others build on—and do it in service of better primary care—this is the role for you. Key Responsibilities Platform and API Architecture: ** Design and lead development of core backend services, REST and GraphQL APIs, and service-to-service integrations that connect all layers of Centerwell's AI product stack. Security and Compliance by Design: ** Establish patterns for authentication, authorization, rate limiting, PHI access control, and audit logging. Ensure HIPAA compliance is embedded in platform design from day one—not bolted on after the fact. AI and LLM Integration Patterns: ** Define and implement reusable patterns for integrating AI capabilities into product

We built Bubble with a clear mission: to empower everyone to create software. Our AI visual development platform lets anyone, from first-time entrepreneurs to enterprise teams, take an idea from prompt to fully-functional, scalable app across web, iOS, and Android. With over 6 million users in more than 100 countries, Bubble is breaking down the barriers to entrepreneurship and innovation worldwide. Our Product Bubble is the only fully visual AI app builder that lets you vibe code without the code to go beyond prototypes and launch real apps to real users. Chat with AI when you want speed, edit directly when you want control. Bubble's visual editor lets you fine-tune any detail, from the design to privacy rules and programming logic, so you're never stuck, even if AI hits its limits. Everything you need comes built in: a unified web and native mobile editor, enterprise-grade hosting, security, database management, and automatic scaling that grows with your business. You can build just about anything on Bubble, and our community is living proof. Mailead grew a $10K investment into a $2M valuation, and Faceless.video went from zero to $1M+ ARR in under a year. People aren't just launching products on Bubble, they're building real businesses. See how Bubble builders are shipping apps that change industries, solve problems, and shape the future here: Inspiring builders, breakthrough apps . Why Join Bubble Now? The rise of AI-generated software has validated everything Bubble has been building toward for over a decade. But pure AI-generated code is fragile, hard to debug, and rarely production-ready. Bubble bridges that gap, combining the speed of AI with a structured visual platform that produces stable, scalable, secure software. The people who join Bubble right now will help define what that means for millions of builders around the world. If you've ever wanted to work on something that genuinely changes who gets to build, this is your moment. About the Team: We’re ex

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a skilled and innovative Senior AI Engineer – AI Product to join our ClickUp Engineering team. In this role, you will drive the development of intelligent, user-facing features that leverage the latest advancements in AI and large language models (LLMs). You will work closely with product, design, and engineering teams to deliver seamless, impactful AI-powered experiences that delight our users and differentiate ClickUp in the productivity space. This is a product-focused engineering role requiring deep expertise in AI, LLMs, and building scalable, production-ready applications. Key Responsibilities: Lead the design, development, and deployment of AI-powered features and products that directly impact ClickUp users. Collaborate with product managers, designers, and engineers to identify opportunities for AI-driven innovation and translate user needs into technical solutions. Integrate and orchestrate multiple LLMs and AI models to deliver robust, context-aware, and personalized user experiences. Prototype, test, and iterate on new AI features, leveraging user feedback and data to drive continuous improvement. Ensure the reliability, scalability, and performance of AI-powered features in production environments. Stay at the forefront of AI research and product trends, incorporating the latest advancements into ClickUp’s product roadmap. Address AI privacy, security, and compliance challenges, ensuring responsible and ethical use of AI in user-facing applications. Mentor and guide other engineers in best practices for building AI-powered products. Qualifications: Proven exper

Who We Are HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless. We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work. Join us as we reinvent work, so people everywhere can do their best work. About The Role The AI team is building cutting-edge solutions that bring the power of AI directly to edge devices while seamlessly integrating with cloud infrastructure. We are looking for a Senior Software Engineer to design and develop high-performance, scalable services to support AI workloads across edge and cloud environments. What You Might Do Design, build, and maintain services that power AI-driven applications, ensuring scalability and performance. Develop APIs and microservices that facilitate seamless integration between cloud-based AI models and edge devices. Optimize data pipelines and storage solutions for real-time AI inference and processing. Implement security and privacy best practices for distributed AI systems. Work closely with AI researchers, infrastructure engineers, and frontend developers to deliver end-to-end AI-driven solutions. Build and optimize an agent orchestration runtime that enables tool use, memory management, and multi-step reasoning across LLMs, APIs, and edge-connected systems. Develop robust logging, monitoring, and alerting systems to ensure system reliabilit

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Our Senior Applied AI Engineer builds and operate production-grade AI systems that extract meaning from large-scale unstructured document collections, enabling enterprise data discovery classification, and governance. This role owns the full lifecycle of graph intelligence solutions — from problem definition and data modelling, to building and enriching knowledge graphs, and deploying ML- and LLM-assisted analytics in production. The focus is on semantic and contextual analysis of unstructured data to uncover relationships, patterns, and insights that support AI safety, security, and compliance requirements. WHAT YOU'LL DO Design, build, and deploy graph-based AI solutions, combining knowledge graphs , LLMs, and ML models applied to large-scale unstructured data Define and own data pipelines that extract, transform, and enrich entity relationships into production-grade knowledge graphs Integrate LLMs and ML models into text processing pipelines for classification, embedding generation, document similarity, and semantic analysis Design, deploy, and operate graph and vector databases to support retrieval, reasoning, and analytics Optimize models and inference pipelines for production constraints including latency, throughput, cost, and infrastructure Deploy, monitor, and iterate on ML systems in production environments ensuring reliability and continuous integration Drive architectural decisions and tech

SonicWall is a cybersecurity forerunner with more than 30 years of expertise and is recognized as a leading partner-first company, ensuring our partners and their customers are never alone in the fight against cybercrime. With the ability to build, scale and manage security across the cloud, hybrid and traditional environments in real-time, SonicWall provides relentless security against the most evasive cyberattacks across endless exposure points for increasingly remote, mobile and cloud-enabled users. With its own threat research center, SonicWall can quickly and economically provide purpose-built security solutions to enable any organization—enterprise, government agencies and SMBs—around the world. For more information, visit www.sonicwall.com or follow us on Twitter , LinkedIn , Facebook and Instagram . Position Summary We are hiring a Software Dev Engineer to design, build, test, and deploy AI-powered applications. You will work across the full application lifecycle — from architecture and implementation through automated testing, CI/CD deployment, and production monitoring — building features that put large language models and agentic tooling to work inside SonicWall's internal systems. This is a hands-on engineering role for someone with 6–8 years of professional software development experience who is comfortable owning services end to end: writing production-quality code, integrating LLM and agentic APIs, standing up reliable data and retrieval pipelines, and shipping through a disciplined test-and-release process. You will collaborate closely with senior engineers, product stakeholders, and platform teams to turn requirements into dependable, well-tested applications. Key Responsibilities Develop AI applications: Design and build features and services that use LLM and agentic capabilities — prompting, tool/function calling, retrieval-augmented generation (RAG

NVIDIA pioneers computer graphics, gaming, AI, and accelerated computing. We are looking for a Senior Solution Architect with full-stack software engineering experience to join our team and play an important role in developing Sales AI applications. This position offers the opportunity to design, build, and evolve solutions that bring generative AI and intelligent workflows into everyday sales experiences. You will work across the application stack and collaborate with Product, AI and machine learning, Data, Security, Solution Architecture, and Engineering teams to deliver secure, reliable, and scalable solutions used globally. What you’ll be doing: Collaborate with application teams to design, develop, and maintain scalable full-stack solutions for enterprise sales workflows. Guide technical solutions across front-end, back-end, APIs, data services, integrations, and cloud infrastructure. Translate product requirements and business needs into secure, maintainable solutions and intuitive user experiences. Integrate generative AI models, AI services, APIs, retrieval systems, and agentic workflows into production applications. Design application architectures that support performance, availability, observability, security, scalability, and long-term maintainability. Lead technical design discussions, compare implementation approaches, make informed architecture decisions, and evaluate emerging technologies. Improve engineering practices for testing, code quality, continuous integration and delivery, monitoring, documentation, and production readiness. Investigate complex issues and develop solutions that improve reliability and user experience. Mentor engineers, share technical knowledge, and contribute to engineering standards and collaborative team practices. What we need to see: <

We’re looking for a Software Engineer to help shape AI governance for developer tooling at Coder. This role sits on our AI Governance team, which builds and maintains two enterprise-grade components of Coder's AI governance stack. AI Gateway is a centralized LLM gateway that sits between coding agents and providers such as OpenAI or Anthropic, providing organizations with audit trails, token tracking, cost control, and centralized authentication. Agent Firewall wraps those agents with default-deny network policies, controlling which domains and methods they can reach inside workspaces. This team works across the full stack - from Go backend and React frontend, to integrating with LLM provider APIs. Day to day, you'll be shipping features, hardening security boundaries, collaborating with enterprise customers on real-world policy needs, and contributing to Coder's open-source ecosystem. What you'll do here Design and build product features that push the standard for remote development in self-hosted environments Create and improve upon popular open source projects that integrate with VS Code, JetBrains, and other developer tools Champion best practices to both internal team members and external contributors Collaborate with Product and Design teams at Coder, as well as with partners like JetBrains, to execute key product integrations Document the design, implementation, and operations of systems for knowledge sharing within the team Work alongside Customer Success teams to support Coder’s enterprise user base Work with cutting-edge AI technologies to create seamless, painless developer experiences Rapidly iterate from prototype to implementation in a highly adaptive, reactive team environment What we're looking for 3+ years of full-stack experience writing code in a professional setting, with 1+ year(s) writing Go (ideally in current or most recent position) Proficiency in building distributed systems in Go Excellent verbal and written communication skills Exceptiona

PagerDuty (NYSE:PD) is a leader in Digital Operations Management. In an always-on world, organizations of all sizes trust PagerDuty to help them deliver a perfect digital experience to their customers, every time. Teams use PagerDuty to identify issues and opportunities in real time and bring together the right people to fix problems faster and prevent them in the future. Over 13,000 organizations (including 60 of Fortune 100) rely on PagerDuty to succeed with Digital Transformation, Cloud Migration, and DevOps Modernization. Notable customers include GE, Cisco, Genentech, Electronic Arts, Cox Automotive, Netflix, Shopify, Zoom, DoorDash, Lululemon and more. We are expanding rapidly as a platform for Digital Operations Management using AI/ML and Automation and growing our adoption by Development, IT, Customer Service, Security, and other teams across the organization. About the role PagerDuty’s Operations Cloud runs on a platform that ingests billions of signals and turns them into real-time action for thousands of customers. We’re looking for a Senior AI/ML Engineer who lives at the intersection of two disciplines: large-scale distributed systems and applied AI. In this role you will design and ship AI systems that run in production at PagerDuty’s scale — powering Incident Management AI Agents, event intelligence, and the LLM-powered capabilities embedded across our platform. You’ll own the full lifecycle, from framing the problem to serving reliably at scale. We are looking for a candidate who is genuinely passionate about building with modern AI — LLMs, agents, and retrieval — but grounded in the realities of building resilient, high-throughput systems. What you’ll do Design and build AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time event streams, from problem framing through production deployment and monitoring. Architect and own the systems behind them: agent and prompt orchestration, retrieval pipelin

At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 Role Overview: We are seeking a skilled and experienced Senior AI Engineer – AI Platform to join our ClickUp Engineering team. In this role, you will play a critical part in both building the core AI platform and directly applying large language models (LLMs) to deliver intelligent features across ClickUp. You will focus on backend systems that enable scalable, reliable, and secure AI-powered capabilities, while also working hands-on with LLMs to solve real user problems and drive product innovation. Key Responsibilities: Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models. Apply LLMs and other AI technologies directly to build and enhance ClickUp’s intelligent features, working closely with product and engineering teams to deliver impactful solutions. Build and maintain robust APIs and backend systems that enable seamless integration of AI-powered features into ClickUp’s core platform. Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance of AI services in production. Integrate with multiple LLM providers (e.g., OpenAI, Anthropic, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost. Drive the adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence. Optimize platform performance, scalability, and cost-efficiency, leveraging cloud-native technologies and distributed systems. Stay curre

Location Details: Remote - Canada (BC or ON) At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands. Join our team GoDaddy is expanding its data and AI capabilities while strengthening the governance, security, privacy, and compliance foundations needed to support responsible growth. As data usage and AI adoption accelerate, we are building scalable governance and control frameworks that enable innovation while maintaining strong accountability, audit readiness, and regulatory compliance. As the Senior Technical Program Manager - Data, AI Governance and SOX Compliance , you will lead cross-functional programs that improve data governance, AI governance, access accountability, and SOX compliance across the business. Partnering with engineering, data, security, finance, legal, audit, and compliance teams, you will drive strategy, execution, and operating mechanisms that make governance and controls visible, scalable, and embedded into daily operations. This is a high-impact role for a program leader who thrives in ambiguous environments. They can influence various interest groups and are passionate about helping teams move faster. They focus on growing transparency, strengthening controls, and boosting confidence in managing data, AI, and compliance risks. What you'll get to do... Lead complex, cross-functional programs spanning data, AI, security, compliance, audit, and finance, driving initiatives from problem definition through rollout, adoption, and measurable business outcomes. Develop and manage program plans, governance

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Job Description/ Responsibilities: Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production. Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow. Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data Technology Eva