Lead Principal Security Software Engineer

Work You’ll Do Lead the technical direction of AI-powered vulnerability detection and automated remediation initiatives across Oracle. Design and build AI systems that discover, explain, prioritise and help remediate software vulnerabilities throughout the software development lifecycle. Lead development of agentic workflows that coordinate LLMs with static analysis techniques. Drive architecture for scalable AI platforms supporting autonomous and human-in-the-loop security analysis. Develop AI-assisted code repair capabilities that generate, validate and refine secure software fixes. Build evaluation frameworks that measure AI effectiveness, accuracy, precision, recall and remediation quality. Design orchestration, planning, validation, memory and recovery mechanisms for complex AI agents. Collaborate with security researchers to translate novel vulnerability research into AI capabilities. Build maintainable, production-quality software platforms used by engineering teams across Oracle. Lead architecture reviews, technical design and code reviews while mentoring software engineers and AI researchers. Partner with cloud engineering, product security and developer platform teams to integrate AI security capabilities into engineering workflows. Communicate technical strategy, AI roadmap and architectural decisions to senior technical leadership. What You’ll Bring A Bachelor’s or Master’s degree in Computer Science, Electrical Engineering or a related field, or equivalent practical experience. 12 or more years of experience in software engineering, security engineering, application security, systems software or a related discipline. Experience leading complex AI-enabled engineering projects from concept through production. Strong software engineering background with experience building large-scale, maintainable software systems. Experience designing AI-assisted or agentic systems using large language models. Experience integrating AI into developer tools, security tooling or engineering workflows. Strong understanding of software vulnerabilities, secure coding practices and application security principles. Experience applying binary analysis, reverse engineering, static analysis or dynamic analysis to software security problems. Experience designing evaluation methodologies for AI systems, including quality, safety and reliability metrics. Experience building production AI systems including orchestration, planning, validation, observability and continuous improvement. Experience working with Python and one or more systems programming languages such as C, C++, Rust or Java. Experience integrating AI systems with development platforms, APIs and existing engineering tooling. Strong architectural judgement and experience designing scalable engineering platforms. Demonstrated ability to mentor engineers and provide technical leadership across multidisciplinary teams. Excellent written and verbal communication skills. Legal authorisation to work in Australia without sponsorship. Nice to Have Experience working in a large cloud or enterprise software company. Experience building or extending binary analysis, reverse engineering or program analysis tools. Experience with compiler internals, LLVM, intermediate representations or static analysis frameworks. Experience with coverage-guided fuzzing platforms such as AFL++, libFuzzer, Honggfuzz or comparable systems. Experience analysing compiled binaries across architectures such as x86, x64 and ARM. Experience with architectures such as MIPS or RISC-V would also be valuable. Experience with symbolic execution, concolic execution, taint analysis or dynamic instrumentation frameworks. Familiarity with vulnerability classification and scoring frameworks such as CWE, CVSS, CAPEC or MITRE ATT&CK. Experience building AI systems for automated code generation or code transformation. Experience building AI systems for vulnerability detection, secure code review or automated remediation. Experience evaluating LLMs for security tasks using benchmarks and automated evaluation pipelines. Experience with retrieval-augmented generation (RAG), tool calling, agent frameworks or multi-agent systems. Experience fine-tuning or adapting foundation models for software engineering or cybersecurity tasks. Experience developing AI safety, guardrails and validation mechanisms for autonomous engineering systems. zExperience analysing operating systems, kernels, hypervisors, firmware, compilers or other low-level software. Demonstrated contributions to the security community through published CVEs, open-source projects, technical publications, conference presentations or significant security research. What We’ll Give You The opportunity to work with a highly skilled and diverse global team. A flexible, hybrid working environment. Exposure to complex, large-scale and cutting-edge systems. The resources of a global technology leader combined with the agility and close collaboration of a small engineering team. Opportunities to work with advanced software assurance, AI and security technologies. Extensive training and professional development opportunities. Competitive benefits and company perks. An organisation filled with smart, enthusiastic and motivated colleagues. The opportunity to make a significant impact on the security of Oracle products and services.