Principal Software Engineer - AI Safety and Security
- Compensation
- Not disclosed
- Location
- United States, Washington, Redmond
- Work setup
- Onsite
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 6+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience, including significant ownership of distributed data, platform, or security products with
Nice to have
- 2+ years of experience working on modern AI systems, such as copilots, agent-based products, LLM applications, agent orchestration and tool use, embeddings, vector databases, retrieval-augmented gener
- 2+ years of experience big data engineering, such as Spark, Kusto, data lakes, batch and streaming pipelines, data quality, performance tuning, and cost and reliability trade-offs.
- Demonstrated success designing and delivering complex production systems in ambiguous, cross-functional environments, identifying and addressing security and privacy risks in complex production system
- Proven coding, system design, written communication, and technical leadership skills.
- End-to-end technical ownership of complex platforms, data, security, or AI products.
- Hands-on experience with alerting, triage, investigation, threat hunting, or incident response.
- Experience leading security and privacy architecture reviews, applying threat-modeling and secure-by-design principles, and translating review requirements into implementable designs.
- Deep understanding of agentic systems, tools, memory, embeddings, and AI system failure modes.
- Experience with cloud-native distributed platforms, infrastructure as code, CI/CD, and technologies such as Azure Data Factory, Databricks, Kubernetes, or equivalent systems.
- Demonstrated record of mentoring and influencing engineers, researchers, product leaders, and partner organizations without direct authority.
Full description
Overview
AI systems are rapidly becoming more capable, autonomous, interconnected, and embedded in products people depend on. As models gain memory, tools, identity, and the ability to act across systems, new risks can emerge through long-running interactions, coordinated agents, and behavior spanning accounts, products, and time—often beyond what any individual product or runtime control can see. Within the Artificial Generative Intelligence Security (AeGIS) team, the AI Safety Platform (AISP) is Microsoft's shared AI observability, detection, investigation, and hunting platform built for this new landscape. We connect fragmented activity across Microsoft's AI estate and turn it into reusable detections, investigation-ready evidence, threat intelligence, and customer protection.
We are looking for a hands-on Principal Software Engineer for a deeply consequential technical builder role at the intersection of cybersecurity and generative AI. You will lead through code and ideas: defining detailed architectures, building large-scale data and detection systems, working through security and privacy reviews, and partnering with cross-company leaders, product engineers, applied scientists, threat hunters, and incident responders from early exploration through production operation. The ideal candidate is deeply curious about how AI systems work, how they break, and how to make them safer and more robust.
We are a mission-driven, collaborative team that leans into uncertainty, learns quickly, and builds on one another's ideas. Our people bring a wide range of backgrounds, disciplines, and life experiences, and we believe that diversity makes both our engineering and our judgment stronger. We want someone energized by technically fascinating problems and by the responsibility to protect users at the scale of some of the world's most widely deployed AI platforms.
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.
Responsibilities
- Lead the design and implementation of shared platform capabilities: guide architecture and technology decisions, establish reusable engineering patterns, write critical production code, and unblock complex technical work across teams.
- Build and evolve company-wide AI observability and monitoring systems that enable attack reconstruction, automated detection, evaluation, threat hunting, and investigation, using modern agentic development tools and AI-assisted coding workflows to prototype, evaluate, and iterate rapidly.
- Design detection infrastructure for attack signatures, pattern matching, behavioral anomaly detection, model-assisted analysis, and emerging research techniques. Apply emerging AI security research to detection, evaluation, observability, and safer implementation patterns.