Principal Software Engineer, Security AI

Microsoft•Mountain View, CA

12h

About The Position

The Cloud & AI organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. Microsoft is one of the largest enterprise service companies in the world. Cloud Security is a team within Microsoft Cloud + AI and the Office of the CISO focused on protecting Microsoft’s cloud environment at scale. We are looking for a Principal Software Engineer, Security AI to help build AI-powered security systems for Cloud Security. In this experienced individual contributor role, you will lead the architecture, design, and delivery of production AI services that combine large language models, agentic workflows, retrieval-augmented generation, knowledge graphs, multi-modal signal processing, and rigorous evaluation frameworks. You will work at the intersection of distributed systems, applied AI, cloud security, and responsible AI to create platform capabilities that improve detection, investigation, response, and proactive risk reduction across Microsoft’s cloud environment. This is an opportunity to shape how AI transforms security engineering across one of the world’s largest cloud platforms. The ideal candidate is a hands-on technical leader who has built and operated production AI or ML systems, understands large-scale cloud services, and can turn ambiguous security problems into reliable, measurable, and trustworthy AI-driven solutions. You will collaborate with engineering, applied science, threat intelligence, security operations, product, and partner teams across Cloud + AI to deliver systems that are secure by design, operationally excellent, durable and grounded in measurable platform impact. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Requirements

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.
Candidates must be able to meet Microsoft, customer and/or government security screening requirements are required for this role.
These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

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.
Experience with Azure services, Azure AI, Azure OpenAI, Microsoft Defender, Sentinel, Kusto, Kubernetes, or large-scale telemetry and analytics systems.
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.

Responsibilities

Design, build, and operate AI-powered software services that support security engineering across Microsoft’s cloud environment.
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.