Currently tracking 250 active AI roles, down 24% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$331k (avg $195k).
Microsoft has 521 active AI-related job listings. The majority of these roles are focused on agents, representing 37% of the total, followed by application and serving infrastructure. Engineering is the most frequent function, with a significant number of openings, and the United States is the primary hiring country. Frequent tech tags include agent orchestration, model serving, and LLM observability, suggesting a focus on operationalizing AI models. Over the last 30 days, Microsoft has added 280 new AI roles, a 157% increase compared to the previous 30-day period.
Microsoft currently has 343 active AI-related roles in our index. The most common open titles are: Principal Software Engineer (19), Senior Software Engineer (19), Software Engineer II (8), Principal Applied Scientist (7), Principal Data Scientist (4). Most positions are in Engineering and Research.
Microsoft's active AI hiring is concentrated in: agents (36%), application (21%), serving infrastructure (19%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Microsoft is hiring AI talent in: United States (308 roles), Canada (15 roles), Japan (8 roles), United Kingdom (7 roles).
Job postings at Microsoft most frequently mention: Computer Architecture, Python, Machine Learning, C#, C++.
In the past 30 days, Microsoft has posted 227 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Software Engineer - Identity Software Engineer role focused on building and deploying machine learning models and platforms for fraud detection and identity protection on Microsoft platforms. The role involves developing detections and blocking mechanisms against large-scale attacks, utilizing threat intelligence, and ensuring real-time protection for billions of users. It requires strong software engineering skills, experience with ML platforms, and a focus on quality, performance, and scalability. | ServeData | 7 |
| Senior Software Engineer The AI Core Infrastructure team is responsible for building and managing large-scale GPU management infrastructure and inference/training platforms for Microsoft's AI workloads. This Senior Software Engineer role focuses on fleet management, designing and developing core AI infrastructure services, and managing GPU clusters for LLM training and inference. |
| ServePost-train |
| 7 |
| Member of Technical Staff, Microsoft Robotics (Software Systems) This role focuses on the reliability, observability, and operational health of a production robotics platform that integrates humans, robots, and AI agents. It involves designing and operating observability infrastructure, incident response, deployment pipelines, secure cloud-to-edge communication, and capacity planning for robotics workloads. The role requires a strong background in SRE and systems engineering for both cloud and edge components. | ServeAgent | 7 |
| Software Engineering IC5 This role focuses on building and operating the foundational accelerated compute infrastructure for large-scale AI training and inference across Azure. It involves designing and developing GPU/CPU infrastructure, end-to-end observability systems, orchestration, and virtualization/container stacks to support AI workloads, optimizing for performance, reliability, and utilization. | Serve | 7 |
| Principal Software Engineer Principal Software Engineer role focused on building and scaling large distributed systems for search, recommendation, and AI services, specifically within the Bing IndexServe team. The role involves architecting and driving cutting-edge techniques like LLM, Ranking, and Index Serving on a massive scale (100K+ nodes), collaborating with ML/AI data scientists. The team aims to simplify the serving stack, improve relevance innovations with deep learning and LLMs, and build an agile, performant, stable, and efficient index serving platform that supports rapid implementation and iteration of relevance techniques and advanced AI toolsets. | Serve | 7 |
| Principal Software Engineering Manager - Substrate Efficiency This role leads a team focused on optimizing the inference efficiency of the M365 Copilot platform, which operates at massive GPU scale. The goal is to maximize throughput per GPU, reduce cost per query, and improve runtime performance for large-scale AI experiences. | Serve | 7 |
| Principal Technical Product Manager- Accelerator Optimization The Principal Product Manager will own the AMD inference platform optimization strategy for Azure AI services, focusing on performance, correctness, stability, compatibility, and release quality for AI models on AMD GPUs. This role involves defining product strategy, roadmaps, and execution, partnering with engineering and external vendors to ensure AMD is a first-class production platform for AI inference. | Serve | 7 |
| Principal Group Software Engineering Manager Principal Group Software Engineering Manager to own GPU fleet health, capacity intake and planning, and automated model deployment for M365 Copilot inference. This role involves leading teams, growing the organization, and building a control plane for capacity management at massive GPU scale. | Serve | 7 |
| Principal Performance Architect The Principal Performance Architect will develop and test SoC and IP models, analyze performance and bottlenecks for deep learning workloads, and prototype optimizations for AI accelerators. This role focuses on the performance and power efficiency of hardware infrastructure for AI workloads. | Serve | 7 |
| Senior Software Engineer - AI Frameworks Senior Software Engineer role focused on optimizing large language model (LLM) deployment on Microsoft's MAIA AI accelerators and GPUs. The role involves building software across the stack, including PyTorch, inference systems (vLLM, SGLang), and performance-critical runtime/kernel components. Responsibilities include architecting tensor computation primitives, extending PyTorch for custom accelerators, improving inference stacks, and optimizing kernels for LLM inference and training workloads. | Serve | 7 |
| Senior Applied Scientist This role focuses on building and scaling Azure's next-generation Model Router, which involves optimizing and deploying LLMs at a global scale. The responsibilities include applying advanced concepts to product needs, working with large-scale computing frameworks for model improvement, deploying and evaluating models in production, and monitoring their performance over time. The role also involves collaboration with product groups, mentorship, and documentation. | ServeShip | 7 |
| Senior Software Engineer - AI Frameworks Senior Software Engineer on the AI Frameworks team at Microsoft, focusing on developing AI software that enables running AI models across various devices and hardware. The role involves hands-on software design and development in C/C++ for large-scale model training and inference on novel AI hardware, requiring a strong engineering background and the ability to solve complex technical problems. | Serve | 7 |
| Applied Scientist II The Applied Scientist II will design, develop, and ship AI models into the Teams media stack, focusing on real-time conversation products like Teams. This role involves building end-to-end ML systems, from data cleaning and feature engineering to model training, evaluation, and deployment, with an emphasis on optimizing for performance and memory, and updating deployed models based on A/B testing. | ServePost-train | 7 |
| Principal Software Engineer - Performance Tooling The Principal Software Engineer - Performance Tooling role focuses on optimizing the performance of AI models, particularly LLMs, across various hardware platforms (GPUs, CPUs) and software layers. This involves benchmarking, debugging, profiling, and optimizing for large-scale training and inference to reduce deployment time and hardware footprint, contributing to the efficiency of AI services like Azure OpenAI. | Serve | 7 |
| Senior Software Engineer - Performance Senior Software Engineer focused on optimizing the inference performance of large language models (LLMs) like those from OpenAI, running on various hardware including GPUs and custom Microsoft silicon. The role involves benchmarking, debugging, and optimizing performance to enable efficient deployment at scale for major Microsoft products and Azure services. | Serve | 7 |
| Principal Software Engineer Principal Software Engineer for Microsoft AI's Copilot Discover team, focusing on backend platform for agentic vertical content generation, AI model serving, data ingestion, caching, and serving. Powers content across Microsoft products for over 1B customers. Requires strong distributed systems, cloud storage, and data processing experience. | ServeAgent | 7 |
| Principal Silicon Performance Architect This role focuses on optimizing the performance of AI inference workloads by exploring micro-architectural innovations and validating end-to-end performance. The Principal Silicon Performance Architect will own performance modeling, analysis, and simulation infrastructure, working closely with chip, system, and software architects to drive data-backed design decisions for improved throughput, latency, and efficiency. | Serve | 7 |
| Senior Software Engineer - Performance Tooling Senior Software Engineer focused on performance tooling for AI frameworks, enabling large-scale training and inference of LLMs on various hardware. The role involves benchmarking, debugging, profiling, and optimizing performance for models like OpenAI's LLMs, aiming to reduce deployment time and hardware footprint. | Serve | 7 |
| Senior Software Engineer - Azure Translator & Language AI Team Senior Software Engineer to work on Azure Translator and Language AI services, focusing on building and scaling large-scale AI systems for natural language processing. | Serve | 7 |
| Principal Software Engineer The Azure AI Inferencing team is seeking a Principal Software Engineer to lead the architecture and design of a large-scale, high-throughput, low-latency model-serving platform for Azure OpenAI generative models, supporting billions of requests daily. The role involves end-to-end ownership of solution quality, cross-team collaboration, incident response, and championing security, privacy, and Responsible AI. | Serve | 7 |
| Principal Software Engineer - CoreAI Principal Software Engineer to build and scale the core serving systems, request routing, and distribution for all LLMs across Microsoft and Azure customers. The role focuses on delivering inference capabilities reliably, efficiently, and with ultra-low latency for a wide range of AI-powered product experiences. | Serve | 7 |
| Senior Product Manager - Foundry Inferencing & Training (CoreAI - multiple roles) Senior Product Manager for Microsoft's Foundry Inference & Training team, focusing on product strategy and execution for AI model platforms. The role involves owning product strategy for AI model training, inference, experimentation, and platform enablement, evolving model offerings, driving developer-facing experiences, and defining efficiency metrics. Collaboration with engineering, data science, finance, and go-to-market teams is key, with a focus on solutions for regulated environments. | Serve | 7 |
| Principal Software Engineer Principal Software Engineer to design and build a Postgres-based database for modern, AI-native, agent-driven workloads within Microsoft Fabric. The role involves innovating on query planning, execution, and storage layers to support high-performance data access for next-generation applications, leveraging open storage formats and engines. | Serve | 7 |
| Member of Technical Staff -Platform Engineering Manager This role is for a Platform Engineering Manager at Microsoft, focusing on building and scaling the AI platform services that power Copilot, Microsoft's personal AI assistant. The role involves managing a team to develop APIs for finetuning, deployment, and core Copilot experiences, collaborating with AI researchers and product teams to bring AI products to life. The focus is on high-performance, secure, and scalable backend systems for consumer-facing AI products. | Serve | 7 |
| ML - Principal Software Engineer Principal Software Engineer role focused on building high-performance software for AI capabilities across Windows & Devices. The role involves architecting and building code for deploying ML models at scale, optimizing edge execution, and guiding system-level decisions for inference, memory, power, and security. It requires defining ML infrastructure strategy and has preferred experience in architecting ML inference pipelines for LLMs, local model integrations, and hardware-aware optimizations. | Serve | 7 |
| Member of Technical Staff, Full Stack - ML Efficiency & Observability - MAI Superintelligence Team Full Stack Engineer on the MAI Superintelligence Team focused on ML Efficiency & Observability, building capacity management portals and visibility into model performance for ML researchers and executives. The role involves designing and developing features for user interfaces, integrating with backend APIs for training frameworks, and contributing to internal tooling and infrastructure. | Serve | 7 |
| Principal AI Network Architect This role focuses on the network architecture for AI accelerator platforms, specifically for high bandwidth and low latency networks critical for AI GPU clusters. The Principal AI Network Architect will evaluate, design, and optimize the network stack from hardware to software kernels, influencing Azure product roadmaps and working with state-of-the-art networking labs. The role requires deep expertise in networking technologies and familiarity with AI model execution pipelines. | Serve | 7 |
| Principal Software Engineering Manager Principal Software Engineering Manager to lead a team focused on improving the efficiency, scalability, reliability, and cost of the core infrastructure powering Microsoft 365 Copilot experiences. The role involves acting as a coach, guiding technical design, driving performance optimizations in collaboration with research teams, and ensuring the health and availability of live services. | Serve | 7 |
| Principal Software Engineer Principal Software Engineer to advance ad-serving infrastructure, focusing on performance, efficiency, and scalability of next-gen model serving and inference platforms for Ads. Designs and optimizes high-performance serving systems and GPU inference frameworks for deep learning and LLM workloads. | Serve | 7 |
| Senior Principal Engineering Manager Lead and grow a team building and operating world-class research compute infrastructure, including large-scale GPU clusters and agentic development tools, for Microsoft Research globally. | Serve | 7 |
| Senior Software Engineer--Backend--Microsoft Copilot Senior Software Engineer for Microsoft Copilot's backend platform, focusing on scaling AI services, integrating AI models, and providing tools for engineers. Requires strong backend and cloud infrastructure experience. | Serve | 7 |
| Principal Product Manager/Architect - Foundry Inference Platform (CoreAI) The Principal Product Manager/Architect will define and guide the technical architecture of Microsoft Foundry, an AI inferencing platform focused on reliability, scalability, and efficiency for large-scale GPU fleets. The role involves setting product direction for reliability, GPU fleet efficiency, capacity management, and engaging with strategic customers. Success metrics include platform reliability, GPU utilization, and customer outcomes. | Serve | 7 |
| Senior Software Engineer - CoreAI Model Inference & Serving Senior Software Engineer role focused on building and scaling the AI data-plane for LLM inferencing across Microsoft and Azure. The role involves designing, coding, and shipping core serving systems, smart routing, and request distribution for a wide range of LLMs, aiming for reliability, efficiency, and ultra-low latency. | Serve | 7 |
| Principal Software Engineering--Backend--Microsoft Copilot This role focuses on building and scaling the backend platform for Microsoft Copilot, integrating with AI models and empowering Copilot teams. The engineer will design, develop, and maintain performant and secure AI Platform services, ensuring reliability, scalability, and performance. The role requires experience with public cloud infrastructure, containerization, and production software development. | Serve | 7 |
| MTS - Platform Engineering Manager This role is for a Platform Engineering Manager at Microsoft AI, focusing on building and scaling the AI platform services that power Copilot. The role involves managing a team to develop secure, performant APIs for finetuning and deploying core AI experiences, collaborating with various teams, and ensuring high-quality code delivery in a fast-paced consumer-facing environment. | Serve | 7 |
| Principal Software Engineer, CoreAI This role focuses on building and operating the foundational GPU accelerated infrastructure for large-scale AI training and inference across Azure. It involves designing systems for GPU management, scheduling, isolation, and sharing, as well as optimizing performance, reliability, and utilization of GPU fleets. The role also requires driving end-to-end platform features, including observability and diagnostics, and influencing platform architecture. | Serve | 7 |
| Senior Software Engineer--Infra-Microsoft Copilot The role focuses on building and scaling the backend platform for Microsoft Copilot, including integrations with AI models and tools for engineering teams. The engineer will design, develop, and maintain performant and secure AI Platform services, ensuring reliability, scalability, and performance. This involves working with public cloud infrastructure, containerization technologies, and production software release. | Serve | 7 |
| Principal Product Manager Principal Product Manager for Azure AI Foundry and Azure ML, shaping strategy for AI/ML and GenAI platforms including training, deployment, monitoring, and governance. Focuses on developer-centric AI platforms enabling organizations to build, deploy, and operate AI systems at scale. | ServePost-train | 7 |
| Product Manager II - Foundry Model Inference (CoreAI) Product Manager II for Microsoft Foundry, focusing on the AI-first application stack, model serving platform, and generative AI development. The role involves defining product offerings, identifying quality improvement opportunities, tracking metrics, and collaborating with engineering and go-to-market teams to deliver integrated solutions for customers, including those in highly regulated industries. | Serve | 7 |
| Principal Researcher - Systems & Networking - Microsoft Research Principal Researcher in Systems and Networking with a focus on AI-driven methods for systems innovation, performance, efficiency, and scalability. The role involves developing new methodologies, collaborating with cross-functional teams, and publishing research findings. | Serve | 7 |
| Principal Researcher - Cloud and AI Infrastructure - Microsoft Research Principal Researcher at Microsoft Research focused on advancing cloud and AI infrastructure architecture, and chip design using AI technologies. The role involves investigating hardware trends, designing and optimizing hardware components, conducting simulations, developing prototypes, and collaborating with cross-functional teams to integrate intelligent systems across computing layers. | Serve | 7 |
| Firmware Engineer Firmware Engineer role focused on designing, developing, and debugging firmware for Azure's custom AI accelerator silicon. This involves working across silicon, hardware, and software teams to enable advanced AI workloads and support data center deployment. | Serve | 7 |
| Member of Technical Staff, Site Reliability Engineer (HPC) - MAI SuperIntelligence Team The role is for a Site Reliability Engineer (SRE) focused on High Performance Computing (HPC) infrastructure for AI model training and inference. The engineer will ensure the reliability, availability, and efficiency of large-scale distributed AI systems, including GPU clusters, and will be involved in monitoring, automation, incident management, and security. | Serve | 7 |
| Member of Technical Staff, HPC Operations Engineering Manager This role manages a team of Site Reliability Engineers responsible for the reliability and efficiency of large-scale distributed AI infrastructure, specifically for training, fine-tuning, and serving generative AI models. The focus is on leading operations, observability, automation, incident management, and security within hybrid cloud/on-prem CPU+GPU environments, collaborating closely with ML engineers and platform teams. | ServePost-train | 7 |
| Software Engineer Software Engineer role focused on building and scaling the inferencing cloud for Large Language Models and GenAI Services within Azure CoreAI Platform. The role involves designing, building, and operating large-scale engineering systems for AI models. | Serve | 7 |
| Senior Software Engineer Senior Software Engineer role focused on designing, developing, and optimizing Azure's High Performance Computing and AI Platform (HPC/AI) virtual machines. This involves deep technical work on hardware/software interactions, device virtualization, and performance analysis of GPU workloads for large-scale AI training and inference. The role contributes to the underlying platform software and its exposure as an Azure service, with opportunities to work on upper layers of Azure infrastructure. | Serve | 7 |
| Research Intern - AI Systems and Tools Research Intern role focused on developing AI systems and tools, particularly developer tools for Microsoft's custom Maia AI hardware. This involves working on profilers, debuggers, performance analysis tools, and simulators to enable efficient execution of AI models on AI accelerators. The role collaborates with AI researchers, hardware teams, and AI compilers teams, and involves work on device firmware, host software, and integration with AI/ML frameworks. | Serve | 7 |
| Senior Software Engineer This role focuses on designing and developing next-generation networking infrastructure for large-scale AI training and inference in Azure Cloud. The engineer will work on high-performance, low-latency, and low-jitter communication frameworks, optimizing scalability and reliability for distributed AI workloads. | Serve | 7 |
| Principal Software Engineer Principal Software Engineer role focused on designing, developing, and optimizing networking infrastructure for large-scale AI training and inference in Azure Cloud. The role emphasizes high performance, low latency, and reliability for distributed AI workloads, working with AI accelerators and advanced networking technologies. | Serve | 7 |
| Senior Software Engineer The role focuses on designing and building cutting-edge networking infrastructure for large-scale AI training and inference in Azure Cloud. The goal is to enable breakthroughs in AI by delivering unmatched computational power, scalability, and reliability, with a focus on high performance, low latency, and minimal jitter for distributed AI workloads. | Serve | 7 |