Staff+ Software Engineer, Product Sandboxing

About the Role The Backend Platform team is the backbone of Perplexity’s product reliability, scalability, and performance, enabling every product and AI team to build with confidence. This high‑impact group builds and maintains critical infrastructure, including backend systems for authentication, authorization, real-time data flows, service orchestration, and sandboxing, to ensure fast, reliable, and secure user experiences. By setting rigorous standards for code quality, uptime and performance, the Platform team ensures everyone at Perplexity can innovate at speed on top of a robust, well-architected foundation. Key Responsibilities Lead the design and implementation of our sandboxing platform to safely execute untrusted and user‑generated code while meeting strict performance and reliability requirements. Define and extend our RBAC and authorization primitives, ensuring they scale with new product capabilities and enterprise controls. Own key backend services involved in authentication and encryption flows (including BYOK‑related pieces), partnering with Security and Infra on defense‑in‑depth. Set the technical bar for backend platform design and operations, driving best practices in reliability, observability, and incident response for always‑on systems. Partner with product and AI teams to define clear platform interfaces, SLAs, and integration patterns so new features can reliably build on shared backend capabilities. Provide technical leadership across the backend platform area, mentoring other engineers and making long‑term architectural decisions that keep the foundation simple, secure, and evolvable. Qualifications Experience designing and building backend systems that run in production (typically 4+ years for mid-level, more for senior and staff). Strong system design skills, with a track record of creating efficient, reliable, and scalable architectures. Hands-on experience with modern infrastructure (for example AWS, Kubernetes, and related cloud techn

RDQ226R605 This role can be based remotely anywhere in the United States. About Databricks Databricks is the data and AI company. More than 12,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. About the Team The Agentic Security Engineering team is a horizontal, shared services engineering team that makes every Databricks security function AI-native — building the AI agents, "personas," and shared platform that security teams across the org (Detection & Response, Threat Intelligence, Vulnerability & Product Security, Red Team, GRC, and Continuous Monitoring) build on to operate at machine speed, safely and reliably. We leverage AI to transform how security is done. The Role As Staff Security Software Engineer , you own a major technical workstream designing and shipping production-grade AI agents and the platform capabilities that power them, with reliability, observability, and safe-by-default security as first-class requirements. You set the standards for how agents are built and operated and co-build with partner security teams. Example use cases you'll enable, led by AI threat detection at scale (alert triage and false-positive reduction, fleet-scale anomaly detection), extend to threat hunting, vulnerability management, product security, red team/offensive testing, and GRC/assurance use cases. The Impact You Will Have Agentic Security Engineering Architecture Design, ship, and operate production AI agents/personas that security teams depend on, starting with AI threat detection at scale. Build and harden the shared platform so any security team can ship agents safely and reliably — i.e., sandboxing, scoped least-privilege identity, obs

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 AI Platform & Agentic Apps team builds the agent platform behind every AI agent at Robinhood. Today it gives a growing number of engineers and employees an AI teammate that ships code, queries data, and runs operational workflows on their behalf. We're building toward the same platform powering the agents millions of customers interact with directly, in real time. These agents don't just answer questions — they're designed to take real action across carefully curated meta harnesses. This is agentic AI at real scale, in a regulated financial environment, and it will change how Robinhood works! As a Staff Machine Learning Engineer on the AI Platform & Agentic Apps team, you will design and build the harness that every agent at Robinhood runs on. A critical part of the role is making those agents trustworthy at scale: trajectory-level evals that measure how an agent reasons and acts, and action guardrails — permission models, approval gates, and sandboxing — built as platform primitives that other teams adopt. You'll be a technical anchor on a growing, high-caliber team, collaborating with product, infrastructure, and fellow ML engineers to take ambitious ideas from

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As Engineering Manager for the Agent Execution group , you'll lead more than 10 engineers who build foundations for AI agents to run safely and effectively across GitLab. You'll give the group clarity, remove obstacles, and help teams move quickly while protecting what matters. You'll contribute to design reviews on sandboxing and agent observability, work alongside staff engineers, and use modern AI coding tools and agent harnesses in your work. What you’ll do Lead the Agent Tools, Agent Observability, and Runner Execution teams across frontend, backend, and AI engineering, with each team anchored by a s

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Product Engineering at Decagon builds all aspects of the platform our customers use to create, operate, and improve their AI agents. We turn work that currently requires an engineer into product that a CX team can run themselves. This team is core to how Decagon scales. The frameworks we build support every agent we have in production, each with its own workflows, data, and constraints. We build the agents too, and that’s what keeps the platform honest: a failure mode we debug in production becomes a guardrail, an eval, or a piece of tooling that catches it everywhere. Our agents run for companies like Hertz, American Airlines, and Notion across chat, voice, email, and SMS. About the Role You’ll design and build the systems that let customers configure, train, test, and monitor sophisticated AI agents with confidence. That means strong engineering underneath, and abstractions on top that hold up across different use cases without forking per customer. You’ll work day to day with prod

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Product Engineering at Decagon builds all aspects of the platform our customers use to create, operate, and improve their AI agents. We turn work that currently requires an engineer into product that a CX team can run themselves. This team is core to how Decagon scales. The frameworks we build support every agent we have in production, each with its own workflows, data, and constraints. We build the agents too, and that’s what keeps the platform honest: a failure mode we debug in production becomes a guardrail, an eval, or a piece of tooling that catches it everywhere. Our agents run for companies like Hertz, American Airlines, and Notion across chat, voice, email, and SMS. About the Role You’ll design and build the systems that let customers configure, train, test, and monitor sophisticated AI agents with confidence. That means strong engineering underneath, and abstractions on top that hold up across different use cases without forking per customer. You’ll work day to day with prod