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.
Currently tracking 250 active AI roles, down 24% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $65k–$331k (avg $195k).
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 |
|---|---|---|
| Member of Technical Staff, Senior Applied AI Engineer Senior Applied AI Engineer role focused on building and shipping LLM-powered assistant features and agentic systems. Responsibilities include designing and developing conversational flows, retrieval pipelines, and multimodal interactions using prompt architectures and orchestration logic. The role also involves building evaluation frameworks, running hillclimbing loops for continuous improvement, and developing internal tools for experimentation and debugging. Integration with product surfaces and building lightweight ML components are key. The team operates with startup energy in a fast-moving AI environment. | AgentEval Gate | 8 |
| Principal Software Engineer - CoreAI Model Inference & Serving Principal 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 |
| 8 |
| Principal Software Engineer, CoreAI This role focuses on building and optimizing high-performance runtime systems for large-scale LLM inferencing, specifically for OpenAI chat and multimodal AI models. The engineer will be responsible for systems-level optimization, microservice design, and ensuring the latency, throughput, cost, and reliability of AI inference pipelines. | Serve | 8 |
| Principal Applied Science Manager This role is for a Principal Applied Science Manager at Microsoft Bing's RAI Defensives team. The primary focus is on managing a team to research and ship state-of-the-art Deep Learning (DL) based NLP models for web-scale services, specifically for detecting harmful queries and content to ensure customer safety and a positive user experience. The role involves people management, technical leadership, and delivering reliable, scalable distributed services. | Ship | 8 |
| Member of Technical Staff, Senior Applied AI Engineer, Image Generation Senior Applied AI Engineer focused on building and shipping image generation capabilities for AI assistants and productivity tools. This role involves model development, training, fine-tuning, evaluation, and production deployment, with a strong emphasis on integrating LLMs and delivering customer-facing features. | ShipPost-train | 8 |
| MTS - AI Platform Engineer This role focuses on building and optimizing AI Agents with world-class orchestration and inference layers. The engineer will develop secure and performant AI Platform services that power products like Copilot, working collaboratively with researchers and other engineers to create next-generation AI products and services. The emphasis is on shipping high-quality, well-tested, secure, and maintainable code within a fast-paced development cycle. | Agent | 8 |
| Applied Engineer II Applied Engineer II role focused on developing and integrating AI technologies, including foundation models, prompt engineering, RAG, and multi-agent architectures. The role involves fine-tuning models, evaluating behavior, building prototypes, and deploying solutions into production, with a strong emphasis on responsible AI and ethical considerations. | AgentPost-train | 8 |
| Principal Technical Program Manager - Applied Science Principal Technical Program Manager for the OneDrive and SharePoint Applied Science team, focusing on driving high-ambition applied research in areas like agentic AI, retrieval, and content understanding to reshape knowledge management within Microsoft 365. The role involves shaping strategy, managing complex science-heavy initiatives, and ensuring scientific advancements translate into product and platform impact, with a focus on enabling invention at scale and influencing organizational direction. | AgentEval Gate | 8 |
| Research Intern - AI Safety and Security Research intern position focused on LLM safety and security, involving research into protecting LLMs from malicious inputs and using LLMs for computer security. The role involves collaboration with researchers and contributing to research publications. | Post-trainAgent | 8 |
| Member of Technical Staff - Prompt Engineer This role focuses on prompt engineering for an AI companion, aiming to create empathetic and collaborative user experiences. Responsibilities include designing prompting techniques, establishing frameworks for social and ethical navigation, and creating evaluations for AI behavior. The role requires experience with chain-of-thought prompting, scaled implementation of prompted systems, and evaluation design. | Agent | 8 |
| MTS - Platform Engineer (Tools) The role focuses on designing and optimizing AI Agents and their orchestration layers for Copilot and other AI-powered experiences. It involves building robust systems for multi-model/multi-service workflows, pushing inference performance for low-latency execution, and enabling agents to securely and efficiently call APIs and services. The ideal candidate has backend or ML systems expertise at the intersection of product and inference, building scalable and reliable AI platforms. | AgentServe | 8 |
| Senior Applied Scientist Senior Applied Scientist with expertise in NLP, deep learning, and Ads recommender systems to design and implement ML models for relevance systems across Microsoft Ads and Shopping (Bing, Copilot). The role focuses on enhancing ad relevance and optimizing user experiences, operating end-to-end for ads and shopping products. | Ship | 8 |
| Principal Product Manager Principal Product Manager for Search & AI team, focusing on next-generation agentic AI products. The role involves defining vision and execution for generative experiences across search, chat, and other agentic applications, empowering users to accomplish complex tasks. Responsibilities include roadmap definition, turning model capabilities into product features, working with cross-functional teams, and using evaluation methods for product quality and safety. The role emphasizes driving DAU growth through product strategy, distribution tactics, and partnerships. | Agent | 8 |
| Senior Researcher - Machine Learning - Microsoft Research Senior Researcher in Machine Learning within Microsoft Research's Health Futures organization, focusing on advancing AI for biomedicine and life sciences discovery. The role involves designing, implementing, and evaluating novel AI methodologies, including post-training, inference-time optimization, and interpretability techniques. | Post-trainServe | 8 |
| Senior Applied AI Engineer Senior Applied AI Engineer for the Customer Service Applications Team, focusing on developing and integrating AI technologies, including foundation models, prompt engineering, RAG, graphs, and multi-agent architectures, into Microsoft products. The role involves fine-tuning models, evaluating their behavior, building prototypes, contributing to production deployment, and translating research into scalable, impactful solutions. Emphasis on responsible AI practices and leveraging AI for real-world customer service outcomes. | AgentPost-train | 8 |
| Member of Technical Staff, High Performance Computing Engineer - MAI SuperIntelligence Team This role focuses on building and scaling the high-performance computing (HPC) infrastructure required for training frontier AI models and powering AI products like Copilot. The engineer will design, operate, and maintain large-scale HPC environments, including schedulers, GPU compute, storage, and networking. Responsibilities include developing automation, supporting researchers and engineers, and troubleshooting cluster issues. The role requires experience with on-premise or cloud HPC clusters, high-scale training clusters, and public cloud infrastructure. | Data | 8 |
| Research Intern - AI Safety & Reliability for LLM Systems Research intern to study LLM-based assistants' behavior with incomplete information, focusing on uncertainty awareness, responsible reasoning, and robustness for enterprise AI systems. | Agent | 8 |
| Applied Researcher 2/ Senior Applied Researcher Applied Researcher role focused on post-training code specific models and agentic research for developer tools like Github Copilot. The role involves building and managing ML experiments, creating datasets, and collaborating with product teams to apply and advance LLM approaches for software engineering, including RAG and evaluation, with opportunities to ship AI advancements to millions of developers. | Post-trainAgent | 8 |
| Senior Researcher - Machine Learning for Life Sciences - Microsoft Research Senior Researcher in Machine Learning for Life Sciences at Microsoft Research, focusing on advancing AI for biomedicine and life sciences discovery. The role involves designing, implementing, and evaluating novel AI methodologies, including post-training, inference-time optimization, interpretability, and experimental design. It also requires application-specific benchmarking, interpretation of deep learning models on biological data, and developing approaches for inference-time optimization. | Post-trainServe | 8 |
| Research Intern - Applied Speech Research Research Intern role focused on applied speech research within the Health and Life Sciences group at Microsoft. The internship involves leveraging AI and speech technologies to improve healthcare outcomes and operations, with a focus on speech recognition, synthesis, and understanding. The role is for PhD candidates in Computer Science or related STEM fields. | Post-train | 8 |
| Research Intern - Agentic Programming Research Intern role focused on agentic programming, involving building agentic workflows and ML models for software engineering tasks, within a PhD program context. | Agent | 8 |
| Member of Technical Staff - Principal Platform Engineer, Copilot Memory and Personalization This role focuses on building and scaling large-scale AI systems for Copilot memory and personalization, leveraging technologies like RAG, embeddings, retrieval, and ranking. The engineer will be responsible for designing and implementing these systems, collaborating across product groups, and ensuring system reliability and performance. | Agent | 8 |
| Senior Researcher - AI & Society - Microsoft Research Senior Researcher at Microsoft Research focusing on the intersection of AI systems and society, with an emphasis on sociotechnical approaches to AI evaluation, responsible AI in industry, and AI safety. The role involves interdisciplinary research, collaboration with industry teams, and a strong publication record. | Eval Gate | 8 |
| Research Intern - Applied Sciences Group Research intern to investigate Small Language Model (SLM) architectures and techniques, such as recurrent transformers and universal transformers, for maximizing LLM throughput with limited cache on hardware targets like SoCs, GPUs, or NPUs. Will involve model training at scale using Azure compute and collaboration with a multidisciplinary team. | Post-trainServe | 8 |
| Senior Researcher - GPU Performance Applied Research role focused on hardware/software codesign for GPU kernel optimizations to improve efficiency of Large Language Models and Generative AI inference. Involves designing, implementing, and optimizing GPU kernels, researching novel optimization techniques, and profiling performance. | Serve | 8 |
| Senior Applied Scientist Senior Applied Scientist to design and implement state-of-the-art machine learning models and algorithms for Microsoft Ads and Copilot, impacting millions of users and advertisers. Responsibilities include the full modeling lifecycle from data strategy to evaluation, focusing on scalable solutions for ad relevance and user experience. | Ship | 8 |
| Applied Scientist - Core AI Speech Research role focused on developing and industrializing novel speech algorithms, including integrating speech with LLMs for multimodal modeling, and applying these models to real products with continuous monitoring and evaluation. | Post-train | 8 |
| Principal Software Engineer Principal Software Engineer to architect and implement an agentic auto-bidding platform for digital advertising, leveraging AI, machine learning, and large-scale distributed systems to optimize bids in real-time across Microsoft's marketplaces. The role involves defining requirements for AI-driven capabilities, building data validation frameworks, ensuring operational excellence, and exploring emerging AI techniques like multi-agent systems. | Agent | 8 |
| Principal Applied Scientist Principal Applied Scientist role focused on the future of AI for Developers, leading research projects from inception to product integration. The role involves building and training state-of-the-art models, applying LLMs to software engineering tasks (including RAG and evaluation), and collaborating with product teams to scale and improve AI projects. The role also involves creating new datasets and managing large-scale ML experiments. | ShipData | 8 |
| Research Intern - AI Evaluation and Alignment Research Intern role focused on advancing the quality, reliability, and evaluation of LLM-based systems by exploring new ML methods for AI assessment and alignment. Responsibilities include co-developing research projects, implementing ML approaches (training/fine-tuning), and developing evaluation frameworks. Requires PhD enrollment in a technical field and hands-on LLM experience. | Eval GatePost-train | 8 |
| Principal Applied Scientist Principal Applied Scientist role focused on building and shipping AI agentic applications and predictive models for Viva Engage. The role involves end-to-end delivery of ML capabilities, including problem framing, data handling, modeling, evaluation, experimentation, deployment, and monitoring. Emphasis is on production-viable solutions, leveraging LLMs and generative AI for knowledge discovery, moderation, recommendations, and enhancing user experiences. The position requires hands-on coding in production environments and driving measurable product impact. | AgentServe | 8 |
| Senior AI Software Architect Senior AI Software Architect role focused on optimizing AI model performance and enablement on Maia hardware, involving PyTorch, quantization, parallelization, and inference pipelines. | Serve | 8 |
| Research Intern - Security, Privacy and AI Research intern to conduct threat modeling for LLM-enabled agentic designs, develop formal security frameworks, and produce security proofs and empirical validations. Deliverable within 12 weeks. | AgentEval Gate | 8 |
| Principal Software Engineer The Principal Software Engineer will work on an auto-bidding platform for digital advertising, leveraging AI, machine learning, and large-scale distributed systems. The role involves designing and building an agentic bidding platform that processes billions of auction events daily, optimizing bids in milliseconds. Responsibilities include defining requirements for agentic AI-driven bidding capabilities, architecting the next-generation platform, building data validation frameworks, driving operational excellence, developing experimentation frameworks, adopting new technologies, mentoring engineers, and exploring emerging AI techniques like multi-agent systems. | Agent | 8 |
| Senior Applied Scientists and Principal Applied Scientists (Multiple Positions) - Copilot Tuning Seeking Senior/Principal Applied Scientists to fine-tune LLMs on tenant data for M365 Copilot, creating task-specific agents and solutions. Role involves writing training pipelines, designing experiments, implementing inference solutions, and shipping models to customers. Focus on advancing LLM capabilities in an enterprise context. | Post-trainServe | 8 |
| Applied Scientist II / Senior Applied Scientist - Responsible AI (CoreAI) The role focuses on building and scaling Responsible AI service components, specifically involving supervised fine-tuning of LLMs with RLHF, conducting evaluations, and developing agent adversarial evaluations and safety mitigations. The goal is to enable customers to use AI responsibly and securely. | Post-trainAgent | 8 |
| Principal Machine Learning Engineer Principal Machine Learning Engineer for Health Futures team focused on accelerating training of generative models, advancing model capabilities, and optimizing training/evaluation/inference pipelines for health and life sciences applications. | Post-trainServe | 8 |
| Principal Applied Scientist (Multiple Positions) - MSAI Office of CTO This role focuses on designing and developing LLMs and underlying subsystems for enterprise AI products, specifically within Microsoft 365 Copilot. It involves tailoring models to product scenarios, collaborating with research and engineering teams, and building custom LLMs and architectures for GenAI applications. The role requires a strong understanding of AI/ML product cycles and the ability to deliver solutions from ideation to shipping. | ShipPost-train | 8 |
| Member of Technical Staff, Applied Scientist Applied Scientist role focused on building advanced Copilot features like Deep Research and Web artifact generation. Responsibilities include architecting and implementing LLM-powered systems, leading evaluation efforts, designing data pipelines for prompt engineering and fine-tuning, and training content classifiers. Requires experience with LLMs, production-quality Python code, and a Bachelor's degree with related experience. | AgentPost-train | 8 |
| Research Intern - Microsoft Teams (PhD) Research intern role at Microsoft Teams focusing on AI-driven innovation in collaboration and communication technologies. Projects may involve AI agents, conversation intelligence, meeting efficiency, and user experience, with a strong emphasis on privacy, security, and accessibility. The role involves applying research methods to real-world challenges in digital collaboration. | AgentPost-train | 8 |
| Member of Technical Staff, Compute Orchestration & Scheduling - MAI Superintelligence Team This role focuses on building and optimizing the compute orchestration and scheduling layer for large-scale AI model pretraining, utilizing Kubernetes and Ray. It involves workload placement, scaling, reliability, and developer experience, with a direct impact on AI model development and deployment infrastructure. | PretrainServe | 8 |
| Member of Technical Staff - Data Research Engineer - MAI Superintelligence Team Seeking Data Research Engineers to join the Multimodal team, focusing on designing and curating high-quality datasets for next-generation foundation models across vision, language, and audio. The role involves developing data collection strategies, improving dataset quality, analyzing data-driven model behaviors, and building tools for dataset auditing, all within the context of responsible AI practices. | Data | 8 |
| Member of Technical Staff - Post Training - MAI Superintelligence Team This role focuses on the post-training of large language models (LLMs) to improve their capabilities in areas like reasoning, instruction following, math, code, and tool use. The responsibilities include data collection, building evaluations, and applying advanced reward modeling and RL techniques. The goal is to advance the state-of-the-art in LLM performance and contribute to the development of superintelligent AI systems. | Post-train | 8 |
| Member of Technical Staff, Developer Experience - MAI Superintelligence Team This role focuses on building and optimizing the infrastructure and developer experience for large-scale ML model training and inference, specifically for Microsoft's AI assistant, Copilot. The responsibilities include improving CI/CD pipelines, developing training tools, enhancing cloud infrastructure, and managing model hosting systems for inference and data generation. The role aims to accelerate iteration and improve the quality of AI models powering innovative products. | ServeData | 8 |
| Research Intern - AI/ML Numerics & Efficiency Research Intern role focusing on ML systems, numeric precision, data types, and compute technologies for AI workloads at Azure scale. The role involves investigating model efficiency through low-precision formats, quantization, ML kernel development, and benchmarking. It aims to inform decisions on compute platforms, acceleration strategies, and system-level optimizations for training and inference of large-scale models. | Serve | 8 |
| Member of Technical Staff, LLM Inference - MAI Superintelligence Team This role focuses on building and maintaining tools and systems for LLM inference, optimizing compute efficiency, and enabling researchers to run models for various tasks. It involves working with inference frameworks, GPU kernel programming, and distributed systems to improve model performance. | Serve | 8 |
| Research Intern - AI Systems & Architecture Research internship focused on AI systems and architecture, investigating performance modeling, architectural analysis, and emerging inference mechanisms for large-scale AI workloads. The role involves analyzing hardware, software, and model interactions, developing performance models, and prototyping new inference techniques. | Serve | 8 |
| Principal Applied Scientist This role focuses on building and improving AI agent platforms, specifically the Agent Performance team within Azure AI Platform. The core responsibility is to integrate scientific advancements, particularly RL techniques like RLHF, into production-ready features for AI agents. The role involves monitoring, evaluating, optimizing, and enabling self-improvement of these agents, bridging the gap between research and product. | AgentPost-train | 8 |
| Research Intern - STAC, NYC (Sociotechnical Alignment Center) Research Intern position at Microsoft's Sociotechnical Alignment Center (STAC) focusing on evaluating AI systems, particularly generative ones. The role involves applying measurement theory from social sciences and statistics to assess risks, capabilities, and performance. Collaboration with Fairness, Accountability, Transparency, and Ethics in AI (FATE) researchers is expected. The internship emphasizes theoretical and methodological approaches to advance AI system evaluation. | Eval Gate | 8 |
| Research Intern - LLM Acceleration Research intern focused on accelerating large language models (LLMs) by optimizing performance on custom architectures, involving computer architecture and parallel programming. | Serve | 8 |