This role pays less than
52%
of similar roles. Most pay
$177,250–$254,750
— the shaded band above.
At the midpoint, this role pays about
$209k
versus about
$216k
for comparable roles.
Based on 240 similar postings.
Employer
About Microsoft
Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing
Microsoft currently has
599 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 564 roles with salary data.
Principal Software Engineer, Perception Platform and AI Systems will provide technical leadership for the evolution of the Perception Platform within Microsoft Security. This role focuses on defining architecture and engineering strategies for sophisticated Generative AI, Retrieval-Augmented Generation (RAG), memory, reasoning, and agentic or multi-agent systems. The engineer will build production-grade systems involving data ingestion, indexing, embeddings, and semantic search while establishing security guardrails against prompt injection and unauthorized access. Key responsibilities include designing identity and authorization architectures for AI agents and creating reliability, evaluation, and observability frameworks. Candidates should possess expertise in distributed systems, cloud platforms, and programming languages such as C, C++, C#, Java, Go, JavaScript, or Python. The role addresses the challenge of building secure, scalable, and compliant AI-powered experiences within security-sensitive enterprise environments by translating complex requirements into durable technical architectures.
What does a Software Engineer earn?
Median $196750 from 2245 postings across 146 companies.
Define the architecture and long-term technical strategy for enterprise AI platform capabilities including generative AI, RAG, and agent orchestration.
Architect production-grade RAG systems involving data ingestion, indexing, embedding, and retrieval evaluation.
Design enterprise AI memory and knowledge architectures that manage context while ensuring compliance and authorization.
Architect agentic and multi-agent systems supporting planning, reasoning, tool use, and failure recovery.
Define identity, authentication, and authorization architectures for AI agents in distributed workflows.
Establish security guardrails to protect AI systems against prompt injection, data exfiltration, and unauthorized access.
Create reliability, evaluation, and observability frameworks for distributed AI systems and model quality.
Provide technical leadership by driving architectural convergence and mentoring senior engineers across the organization.
What we're looking for
Bachelor's Degree in Computer Science or related field and 6+ years of technical engineering experience in languages like C, C++, C#, Java, Go, JavaScript, or Python.
Ability to pass Microsoft background and Microsoft Cloud background checks.
Master's Degree in Computer Science or related field and 8+ years of technical engineering experience (preferred).
Bachelor's Degree in Computer Science or related field and 12+ years of technical engineering experience (preferred).
Extensive experience architecting, building, and operating large-scale distributed systems, cloud services, or AI platforms in production environments (preferred).
Deep experience with Generative AI architecture, including RAG, semantic search, memory management, and safety guardrails (preferred).
Experience designing agentic/multi-agent systems and identity, authentication, and authorization architectures for autonomous systems (preferred).
Demonstrated ability to provide technical leadership, mentor senior engineers, and translate complex requirements into durable architectures (preferred).
Python
C#
Java
JavaScript
C++
C
Azure
Generative AI
Large Language Models
Agentic AI
Retrieval-Augmented Generation
Prompt Engineering
Copilot Studio
Power Platform
Azure AI Foundry
Distributed Systems
APIs
Observability
Computer Vision
Machine Learning
C++
Python
Linux
TensorRT
ONNX
PyTorch
TensorFlow
CUDA
Object Detection
Object Tracking
SLAM
Sensor Fusion
3D Geometry
Multi-view Geometry
Python
AI Infrastructure
Machine Learning
Cloud Platforms
Distributed Systems
SRE
Observability
System Design
SDKs
Automated Testing
Infrastructure Engineering
Generative AI
Python
Go
Java
C++
Kubernetes
OCI
LLM
Machine Learning
PyTorch
TensorFlow
Hugging Face
CI/CD
Microservices
Distributed Systems
Infrastructure Automation