Principal Software Engineer

In this role, you will: Leverage modern AI-assisted development practices and tooling to accelerate delivery while maintaining high code quality. Use AI in your daily coding and advocate to the team and customers an evolving state-of-the-art of how to do this. Demonstrate resiliency to experiment and try multiple AI approaches that may not work — because no one has tried them before. Provide mentorship and coaching to engineers in, and beyond, your team. Build AI‑powered product features using technologies such as large language models (LLMs), vector stores, and agentic workflows to improve security signal analysis and customer outcomes. Continuously improve engineering efficiency by leveraging AI tooling, automation, and documentation to streamline development and operational workflows. Own medium‑to‑large features end‑to‑end, including design, implementation, deployment, monitoring, and iteration in production environments. Develop software using languages such as TypeScript, JavaScript, React, and others Design, develop, and maintain backend services and APIs that support agentic workflows and platform capabilities Collaborate closely with PM, Design, and partner teams to design and develop scalable solutions Lead by example, adhering to engineering practices, raising the quality bar, and improving the team's response to customer incidents With minimal supervision, tests and explores various design options for a product/solution feature, outlining strengths and weaknesses of each option. Uses appropriate AI tools and practices across the software development lifecycle (SDLC) in a disciplined manner. Understands and applies security practices and establishes code invariants to model "security as code," ensuring each layer is independently secure, and minimizing risk with minimal supervision. Apply Security‑by‑Design and Responsible AI principles when building features that leverage AI to enhance threat detection and response capabilities. Contribute positively to team culture, demonstrating growth mindset, openness to feedback, and a collaborative approach in a fast‑paced, data‑driven environment. 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. Hands-on experience of building and operating LLM powered agentic systems in production, with direct ownership over quality, reliability, and iterations 6+ years of experience building production software using one or more modern programming languages such as AI LLM, agents, skills , C#, Java or Python. Demonstrated proficiency with AI-assisted software development tools and workflows (e.g. AI coding agents, LLM-powered development environments) Expertise in LLM and GenAI Application development. GitHub Copilot and Copilot Workspace — AI pair programming, CLI, and task-oriented development Prior experience using agentic plugins, agents, skills, hooks, etc. Prior experience building with Agent SDKs, large language models (LLMs), prompt engineering, or AI orchestration frameworks). Familiarity with agentic AI development patterns — multi-step reasoning, tool/function calling, retrieval-augmented generation (RAG), and human-in-the-loop workflows. Good product mindset with a track record of owning ambiguous problem spaces and driving them to high-quality outcomes Solid engineering fundamentals, including systems design, performance, and debugging in complex production environments Track record of designing, running, and optimizing evaluations for agentic systems, including tools, prompts, and agent loops Good understanding of Generative AI & software engineering fundamentals, data structures, and problem-solving. Ability to learn new technologies quickly and adapt to deliver customer and business impact. 6+ years of experience in cloud services or AI systems. Experience building and shipping AI features for world-class production systems. Good communication skills and ability to collaborate within a multi-disciplinary team. Proven experience as a Software Engineer delivering large-scale, production-quality systems. Proficient software engineering fundamentals: system design, algorithms, testing, debugging, and code review. Demonstrated ability to lead technical direction and mentor peers in a collaborative team environment. Comfort working in ambiguous, fast-moving problem spaces where practices are still being established.- Hands-on experience with AI-powered developer tooling and coding assistants, such as: Experience dogfooding, evaluating, and forming opinions on emerging AI developer tools, and translating those insights into team-wide practices.. Experience designing and building RESTful APIs or GraphQL services. Track record of high development velocity through effective use of AI coding assistants and automation Experience with database technologies (SQL, NoSQL)