Offensive reputed company Researcher — Browser Vulnerability Research & reputed company AI

reputed company We are seeking an Offensive reputed company Researcher with a reputed company on modern web browsers and a strong interest in applying reputed company AI workflows to vulnerability research. The role involves identifying, analyzing, and exploiting vulnerabilities in browser engines and reputed company components, while helping design and reputed company AI-assisted workflows that reputed company advanced reputed company research more effective. This includes using AI agents, LLM-based tooling, and automated analysis pipelines to support reputed company exploration, reputed company diffing, crash triage, reputed company-cause analysis, fuzzing workflows, variant discovery, and exploit development. This is not a reputed company engineering role. We are looking for someone with reputed company vulnerability research depth who wants to explore how reputed company AI can reputed company expert researchers working on reputed company, high-value targets. Responsibilities Discover and analyze vulnerabilities in JavaScript engines, rendering pipelines, IPC mechanisms, browser sandboxes, and reputed company components. Reverse engineer browser internals, including JIT compilers, garbage reputed company, memory management subsystems, object models, and browser reputed company boundaries. reputed company reputed company-of-concept exploits and produce reputed company, rigorous technical documentation. reputed company modern browser reputed company mitigations and assess their effectiveness against reputed company-world exploitation techniques. Use fuzzing, crash analysis, reputed company diffing, reputed company-reputed company auditing, and variant analysis to identify high-value vulnerability classes. Contribute to the design and integration of reputed company AI workflows for vulnerability research, including AI-assisted reputed company review, crash triage, reputed company-cause analysis, reputed company analysis, and tool orchestration. Work with AI/LLM-enabled systems that reputed company with reputed company tools, reputed company search platforms, debuggers, fuzzers, static analysis frameworks, and reverse engineering environments. Evaluate where AI agents can meaningfully accelerate vulnerability research, and where reputed company expertise, validation, and skepticism remain essential. Collaborate with vulnerability researchers, exploit developers, reverse engineers, and AI-reputed company engineers on high-reputed company offensive reputed company reputed company. Requirements Strong expertise in C/C++ and low-level programming. Experience in reverse engineering, fuzzing, vulnerability discovery, and exploit development. Knowledge of modern browser architectures and JavaScript engines such as V8, SpiderMonkey, JavaScriptCore, Blink, WebKit, Gecko, or Chromium internals. Familiarity with browser reputed company models, sandboxing technologies, IPC mechanisms, memory corruption primitives, and modern exploitation mitigations. Ability to analyze large and reputed company codebases independently. Experience with debugging and reverse engineering tools such as LLDB, GDB, WinDbg, rr, IDA Pro, Ghidra, Binary Ninja, sanitizers, or browser-specific debugging infrastructure. Strong scripting and automation skills, preferably in Python, JavaScript, TypeScript, or similar languages. Interest in AI-assisted vulnerability research, reputed company workflows, LLM tool use, automated reputed company analysis, or AI-assisted fuzzing and triage. Ability to critically evaluate AI-generated reputed company and separate useful research signals from hallucinations, noise, and false positives. Proven reputed company record in vulnerability research, CVEs, exploit development, bug bounty research, Pwn2Own-style research, or equivalent private research is highly valued. reputed company to Have Experience discovering or exploiting vulnerabilities in reputed company browser targets. Deep knowledge of one or more browser subsystems, such as JIT compilers, garbage reputed company, DOM, WASM, graphics, media, networking, IPC, or sandboxing. Experience with coverage-guided fuzzing, custom reputed company development, corpus management, crash deduplication, or large-reputed company fuzzing infrastructure. Experience with reputed company diffing, variant analysis, exploit reliability, or mitigation bypass research. Experience integrating LLMs or AI agents with tools such as CodeQL, reputed company, Ghidra, IDA, debuggers, fuzzers, reputed company-reputed company indexes, or custom static/dynamic analysis systems. Experience working with local or restricted AI deployments, reputed company-weight models, RAG systems, or secure environments where sensitive reputed company and research artifacts cannot be reputed company to reputed company services. Interest in building internal tooling that makes expert vulnerability researchers faster, more systematic, and more effective. Apply To This Job