Principal AI Engineer

Role

Principal AI Engineer on Microsoft Security NEXT setting multi-year strategy and roadmap for AI-first security experiences and the underlying platform. Lead zero-to-one incubation R&D through MVP and private preview, then drive one-to-many platformization and scale to GA, providing hands-on technical leadership across architecture, data, and model layers.

Key Responsibilities

• Define technical vision, strategy, and roadmap for AI-native incubation initiatives and align stakeholders across Security Copilot, Defender, Sentinel, Entra, Purview, Azure AI Foundry, and Microsoft AI.
• Lead 0→1 R&D through MVP/private preview and drive 1→N platformization and scale to GA, balancing quality, latency, reliability, cost, and safety.
• Prototype in code, review designs and PRs, define APIs/data contracts, and build well-architected systems with evaluation frameworks to de-risk complex systems.
• Set strategy for LLM vs classical ML use, retrieval/RAG design, grounding, model routing/fallbacks, and safety guardrails to meet customer outcomes and SLOs.
• Ensure Responsible AI, privacy, security guardrails, safety reviews, abuse prevention, compliance, and incident readiness are integrated from day one.
• Lead and mentor v-teams, engage with enterprise customers and field teams to co-design solutions and drive adoption, and communicate program status and strategy to executives with hands-on demonstrations.

Required Qualifications

• Bachelor’s degree in Computer Science or related technical field AND 6+ years technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, OR equivalent experience.
• Hands-on coding and prototyping ability; experience in technical design reviews and PRs.
• Ability to meet Microsoft and customer/government security screening requirements (Microsoft Cloud Background Check).

Preferred Qualifications

• Master’s degree AND 8+ years engineering experience, OR Bachelor’s AND 12+ years, OR equivalent experience.
• 6+ years driving complex, cross-functional initiatives and 3+ years working with ML/AI systems (LLMs/GenAI, retrieval/RAG, model serving, experimentation platforms, data pipelines) including evaluation metrics and improving model quality.
• Experience shipping cloud services or platforms at scale (multi-tenant, high-throughput) and security domain expertise (threat detection/response, SIEM/SOAR, identity, endpoint, cloud security).
• Experience with GenAI/LLM techniques and tooling (prompt engineering, retrieval/vector stores, agents/tool use, content safety/guardrails, offline/online eval frameworks, vibe coding).
• Strong program leadership, stakeholder management, communication, and mentoring skills.

What Makes a Great Principal AI Engineer Here

• Model-literate and pragmatic: choose the right blend of LLM, deterministic/rules-based, or classical ML approaches and hybridize with retrieval, caching, routing, and fallbacks to meet SLOs and cost targets.
• Evaluation-obsessed: define metrics and datasets, build eval harnesses, and require measurable improvements before broad rollout.
• Zero-to-one builder and one-to-many integrator: turn ambiguous ideas into MVPs and lead GA platformization with durable API/SDK contracts and cross-team coordination.
• Customer-back and outcome-focused: translate defender/admin workflows into specs, land adoption, and iterate based on feedback and telemetry.

Security & Screening

• This role requires passing Microsoft background checks and recurring Microsoft Cloud background checks as a condition of employment.

Compensation

• Typical U.S. base pay range for this role: USD $139,900 - $274,800 per year. Different ranges apply for certain locations (example: San Francisco Bay area and New York City metropolitan area USD $188,000 - $304,200 per year).