Principal Software Engineer, Security AI

Develop AI-enabled workflows that help engineering and security teams analyze information, retrieve relevant context, summarize findings, and make faster, higher-quality decisions. Build scalable systems that use large language models, retrieval-augmented generation, embeddings, semantic search, knowledge graphs, and related AI techniques to support security scenarios. Create evaluation, measurement, and monitoring approaches that help assess AI system quality, reliability, safety, and effectiveness in production environments. Partner with engineering, applied science, product, security operations, and other teams to translate AI advances into practical, secure, durable and reliable platform capabilities. Incorporate responsible AI, privacy, security, and compliance considerations into the design, deployment, and operation of AI-powered systems. Contribute to production readiness for services, including architecture, APIs, reliability, scalability, observability, cost efficiency, incident response, and continuous improvement. Provide technical leadership through design documents, architecture discussions, code reviews, and collaboration with partner teams. Mentor engineers and help raise the engineering bar through thoughtful technical guidance, high-quality implementation, and operational excellence. Use data, telemetry, partner feedback, and operational learnings to continuously improve AI capabilities, system reliability, and platform impact. Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. These requirements include, but are not limited to the following specialized security screenings: Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related technical field, OR equivalent industry experience. 5+ years of hands-on experience building AI, machine learning, or large language model-enabled systems, including model or agent development, retrieval and knowledge systems, data pipelines, evaluation, safety, experimentation, and productionization in large-scale cloud environments. Experience designing reliable and scalable software systems with strong fundamentals in APIs, service architecture, data modeling, testing, debugging, observability, incident response, and secure software development. Experience building multi-agent systems, tool-use frameworks, orchestration layers, autonomous workflows, or AI copilots in production environments. Experience with vector databases, embeddings, semantic search, knowledge graphs, entity resolution, ranking, summarization, or context-grounding systems. Experience with LLM evaluation, responsible AI, model safety, hallucination mitigation, prompt injection defense, model monitoring, or AI governance controls. Experience with cloud security, security operations, threat detection, incident response, vulnerability management, identity and access systems, or security data platforms. Demonstrated ability to influence senior technical stakeholders, create durable architecture, mentor engineers, and deliver high-impact platform capabilities in ambiguous problem spaces. Strong communication skills with the ability to articulate technical tradeoffs, security impact, risks, and strategy to engineering leaders, partner teams, and cross-functional stakeholders.