Principal Software Engineer role focused on building foundational platforms for intelligent agents and generative AI systems. Responsibilities include developing large-scale, cloud-native systems for agent deployment, execution, tool integration, fine-tuning, training, observability, evaluation, and optimization in production. The role operates at the intersection of distributed systems, AI infrastructure, and developer platforms, requiring strong systems thinking and architectural decision-making for systems demanding high performance, reliability, security, and compliance.

Research intern role focused on building advanced LLM agents with memory, tool use, and multi-agent collaboration, and driving efficiency in LLM applications through context engineering, adaptive inference, and system optimization.

Principal Researcher focused on expanding AI capabilities, efficiency, and safety through innovations in foundation models and learning agent platforms. The role involves developing self-improving, adaptive agents for dynamic enterprise environments, integrating pre-training, post-training, RL, multi-agent collaboration, and deployment. Key responsibilities include research on recursive self-improvement, continual learning, human-AI collaboration, and building robust evaluation frameworks and synthetic data pipelines.

Research Scientist focused on agentic AI, developing self-improving, multi-agent systems that learn through interaction. The role involves research on recursive self-improvement, adaptive coordination, continual learning, human-AI collaboration, and autonomous skill acquisition. It spans the research-to-deployment spectrum with a focus on building evaluation frameworks and synthetic data pipelines, and refining architectures for scalability. The work is grounded in foundation models and learning agent platforms, with potential for product impact and publication.

Seeking a Principal Applied Scientist to research and develop novel AI agents, focusing on agentic systems, multi-step reasoning, and tool use. This role involves pushing the boundaries of AI agent capabilities and contributing to impactful AI products.

This role focuses on the applied science foundation for observability in AI agents and multi-agent systems running at scale. It involves developing and applying scientific methods, evaluation frameworks, and measurement systems to understand, benchmark, diagnose, and improve agent-based systems in production. The role addresses unique observability challenges of AI agents, such as non-deterministic execution and emergent behaviors.

Research Intern position focused on advancing agentic model capabilities, including reasoning, tool use, and interaction across text and visual environments. The role involves developing novel training algorithms, exploring synthetic environments, multi-agent training, and scaling laws, with a focus on foundational models and modern architectures. The internship offers a chance to publish findings and potentially ship AI technologies in products.

Research intern role focused on advancing Generative AI and LLM technologies, specifically in foundation models and agentic systems. The work involves developing, improving, and exploring LLMs and Multimodal AI models, with research areas including reasoning, orchestration, multi-agent systems, and evaluation.

Senior Principal Researcher at Microsoft Research AI Frontiers focused on pushing the boundaries of agentic AI, including large language and multimodal models, reasoning, and multi-agent systems. The role involves leading research, developing training methodologies, curating datasets, designing evaluation frameworks, and prototyping new agentic capabilities, with opportunities for publication and real-world impact.

This role focuses on building and evolving the core orchestration and intelligent systems that power Microsoft's enterprise Copilot, a large-scale AI assistant for Microsoft 365. The work involves advancing model training, developing model-driven features from concept to production, and enhancing the orchestrator for improved reasoning, speed, and multi-modal/agentic capabilities. The goal is to ship cutting-edge AI technology impacting hundreds of millions of users.

Product Manager for Agentic AI team, focusing on next-generation agentic AI products that reason, plan, and act across applications, the web, and the OS. The role involves translating AI research into scalable products for Copilot, Bing, Edge, M365, and Azure, with a focus on shipping 0-to-1 agentic products.

Research Software Engineer focused on Generative AI and agentic applications within Microsoft Research's AI Frontiers lab. The role involves developing, improving, and exploring capabilities of AI models and agentic systems, with a focus on creating reliable digital workers that can execute entire workflows and collaborate with humans and other agents. Key areas include enhancing agent reasoning, improving robustness, reimagining workflows for an agent-native world, and creating end-to-end experiences.

Research intern to investigate, propose, implement, and evaluate new approaches in LLMs, Multimodal AI, Reinforcement Learning, Conversational AI, and AI Agents for OneDrive and SharePoint. Will conduct experiments, develop AI models, design evaluation metrics, build datasets, and deliver models for content understanding and use across various modalities. Focus on applying scientific methods to real-world problems in content and collaboration.

Research role focused on creating LLM models for general purpose capabilities and products, with a focus on agentive applications and advancing AI towards controllable, safety-aligned superintelligence. Responsibilities include developing new training methods, data collection, evaluation, and building user-facing features.

Research intern role focused on developing new LLM memory representation and orchestration systems, including advanced RAG and embedding techniques, for enterprise and consumer applications.

Senior Researcher focused on advancing state-of-the-art in agentic systems and ecosystems, including building agent-native ecosystems, developing advanced agentic capabilities through post-training methods, creating novel human-agent interaction techniques, and developing evaluation benchmarks and tooling for agents. The role emphasizes outcome-driven innovation, collaborative innovation, problem-solving, decision-making, and the scientific method, with a strong publication policy and potential for shipping AI technologies.

Research intern role focused on advancing agentic model capabilities, including reasoning, tool use, and end-to-end workflow execution across text and visual environments. The role involves research in reinforcement learning, novel training algorithms, synthetic environment creation, multi-agent training, and scaling laws, with a focus on foundational models and various data modalities. The internship aims to contribute to cutting-edge research and potentially ship AI technologies in products.

Research Intern position focused on building reliable, safe, and efficient AI agents. The role involves exploring formal verification, reliability, safety, intelligent task handling, secure execution, and efficiency optimization for AI agents. It is a research-focused role within Microsoft Research, aiming to tackle complex challenges in AI agent systems.

Senior Software Engineer role focused on building LLM-powered data engineering experiences and infrastructure for Microsoft Fabric, utilizing Apache Spark. The role involves implementing agentic workflows, scalable LLM-backed data features, and defining evaluation strategies for LLM features, while applying Responsible AI practices.

Principal Software Engineer on the Azure Artificial Intelligence Core team, responsible for designing, building, and maintaining AI systems powering large-scale multimodal workloads. This role involves end-to-end ownership from API interfaces to inference backends, with a focus on safety, real-time audio interaction, image/video generation, and benchmarking/optimizing LLM performance. Collaboration with OpenAI and internal teams is key.

Principal Product Manager to define and drive the strategy for Vertical Knowledge Agents that combine structured data, licensed content, and AI grounding to deliver insights across Copilot, MSN, and Bing. The role involves influencing agent architecture, ranking frameworks, and multimodal UX, partnering with AI research and engineering to ship agentic experiences, and championing Responsible AI.

Senior Applied Scientist to lead the development of machine learning and generative AI systems for conversational commerce experiences within Microsoft Copilot. This role focuses on product discovery, ranking, personalization, and reasoning, involving LLM-based systems, RAG, tool orchestration, and addressing quality/trust challenges. The role also involves defining evaluation frameworks and partnering with product/engineering teams to deliver low-latency experiences.

Applied Scientist II on the Core Search and AI team (Bing) to build the next generation of search using large language models at scale. Responsibilities include developing retrieval, ranking, and relevance systems, refining RAG pipelines, and translating research into production deployments. Requires experience with ML systems for search/ads/recommendation and LLMs.

Product Manager for an Agentic Platform within Microsoft's Engineering Systems (ES365) team. This role focuses on building and scaling the agentic platform, including orchestration, developer tools, and governance, for use by thousands of Microsoft developers. The PM will define product vision, strategy, and metrics, work closely with engineering, and leverage AI tools in their daily work to improve developer efficiency and enable AI-assisted workflows across large codebases.

ML Engineer for Microsoft Office AI team to build core platforms and experiences integrating LLMs into Office applications. Responsibilities include developing intelligent features, deploying AI solutions on Azure, and productionizing ML models at scale, focusing on agentic systems and their underlying infrastructure.

Principal Software Engineer at Microsoft CoreAI, focusing on building SDKs, UI, and agentic experiences for generative AI applications. The role involves defining, architecting, and developing agent platform services and developer experiences, enabling customers to build, deploy, evaluate, and manage intelligent agents at scale. Key responsibilities include leading API, SDK, CLI, and UI development, and owning architecture decisions for agent orchestration, knowledge integration, tool calling, and multi-turn conversations.

Senior Software Engineer role focused on building and evolving large-scale, cloud-native systems for the end-to-end lifecycle of intelligent agents. This includes secure enterprise deployment, governed tool integration, model fine-tuning, training workflows, and production observability, evaluation, and optimization.

Principal Solutions Architect role focused on architecting and delivering complex, high-impact AI and cloud transformation programs for enterprise customers. This involves designing AI platforms, LLM/SLM-based services, and digital agents, while also providing technical leadership and executive advisory. The role emphasizes end-to-end solution architecture, governance, and delivery excellence, with a focus on Microsoft Azure and generative AI technologies.

This role is for a Principal Technical Program Manager (TPM) focused on building runtime defenses for agentic AI systems like Copilot. The TPM will own the end-to-end delivery of security capabilities such as misuse detection, adaptive guardrails, and containment mechanisms. The role requires translating ambiguous threat models into shippable, operable defenses in a scaled AI product, operating at the intersection of security engineering, AI research, and platform systems. It emphasizes direct technical execution and making complex systems land in production under adversarial pressure, rather than process or coordination.

Senior Software Engineer to develop security features and solutions for agentic AI in Copilot, focusing on protecting customers and enabling new capabilities. The role involves designing and building AI-powered defenses, secure orchestration frameworks, and enabling technologies for safe and responsible AI actions at scale.

Principal Software Engineer at Microsoft Foundry, Core AI, focused on building and scaling the platform for intelligent agents and generative AI systems. This role involves driving technical direction, architectural decisions, and ensuring quality, reliability, security, and compliance for large-scale AI systems. The engineer will mentor others, influence without authority, and champion automation and responsible AI practices.

Senior Applied Scientist role focused on building and optimizing generative AI models, particularly LLMs and agentic systems, for Microsoft's consumer products like Bing and Copilot. The role involves hands-on work with SOTA models, prompt engineering, large-scale data analysis, and experimental design to improve search experiences and deliver impactful AI features.

Senior Software Engineer role focused on building the foundational platform and distributed systems for agentic AI applications at scale. This includes developing cloud-native infrastructure, runtime systems, and orchestrating agent-based AI applications with enterprise-grade guarantees, while integrating multi-modal capabilities.

This role focuses on building and productionizing machine learning and generative AI systems for conversational commerce experiences within Microsoft Copilot. It involves developing models for product discovery, ranking, personalization, and reasoning, as well as LLM-based systems for conversational shopping, including RAG and tool orchestration. The role also addresses quality and trust challenges and defines evaluation frameworks, aiming to translate models into low-latency, reliable user-facing experiences.

Senior Applied Scientist role focused on building and scaling an AI-driven testing platform for Microsoft's AI products. The role involves using LLMs, prompt engineering, and agent-based workflows to validate product quality, design testing strategies, develop evaluation frameworks, and create actionable insights. The goal is to evolve the platform towards more autonomous and agentic workflows.

Senior Software Engineer focused on building and scaling AI/ML-powered features for Windows, integrating multimodal input, agentic workflows, and generative AI. The role involves end-to-end development, from research and implementation of foundation models, prompt engineering, RAG, and multi-agent architectures, to fine-tuning, evaluation, and production deployment. Emphasis on creating inclusive and accessible experiences, particularly for users with disabilities, using human-centered AI.

The Senior AI Product Manager will drive Copilot model capabilities such as tool-use to ensure that the language models that power Microsoft Copilot deliver high quality responses to our users whilst being grounded, reliable, and cost-efficient. This role works at the nexus of product and research, driving execution in partnership with engineers, language engineers, data scientists and researchers. Responsibilities include developing LLM platform strategy, prototyping approaches, identifying and prioritizing issues impacting quality/factuality/safety, defining and building evaluations, defining and deploying experiments for tool use, and partnering with teams to scale tool building and resolve dependencies.

Product Manager for Microsoft's Agentic Engineering platform, focusing on building and scaling AI-powered developer tools and experiences for thousands of Microsoft engineers. The role involves defining product vision, strategy, and roadmap for the core orchestration layer, developer tools, plugin marketplace, and enterprise governance, with a strong emphasis on hands-on use of AI tools and driving adoption.

AI Security Research Intern focused on developing autonomous systems to detect and disrupt cyber attacks in near real-time, leveraging LLMs and agentic frameworks.

Applied AI Engineer role focused on building and shipping LLM-powered assistant features, agentic behaviors, and retrieval pipelines. Responsibilities include prompt architecture, orchestration logic, evaluation frameworks, hillclimbing for performance improvement, and developing internal tooling for experimentation and debugging. The role also involves integrating LLMs with product surfaces and building lightweight ML components for enhanced assistant intelligence. Requires experience in production-level code/models and working in fast-moving AI teams with a startup-like energy.

Engineering Manager to lead a team focused on building and scaling an agentic engineering platform for AI-powered developer productivity across Microsoft. The role involves managing engineers, setting team direction, fostering experimentation, and partnering with other teams to advance AI in developer workflows.

The Principal Software Engineer will build and own the agentic engineering platform used across Microsoft, orchestrating AI models to enhance developer productivity. This role involves designing, implementing, and shipping features for the platform, advocating for best practices in agentic development, and mentoring other engineers. The focus is on creating the core agentic platform and experiences, with a tight feedback loop from internal developer customers.

Senior Software Engineer to build and own the agentic AI platform for developer productivity at Microsoft scale, orchestrating AI models and experiences for thousands of developers.

Principal Product Manager for Microsoft Copilot's Identity & Expression layer, focusing on how AI agents communicate intent, reasoning, and trust. This role involves defining strategy, owning a reference implementation (Mico), translating AI capabilities into enterprise value, establishing trust models, and leading AI evaluation for expressive and agentic experiences, using Japan as a pilot market.

This role focuses on designing, developing, and deploying end-to-end AI/ML solutions for enterprise customers using Python and Azure AI services. It involves building AI models and agents, working with data pipelines, and engaging directly with customers to solve business challenges.

Senior Research Software Engineer on the Agentic Experiences team at Microsoft Research. The role involves designing and building software using AI tools and agentic workflows across the SDLC, from prototypes to scalable products. Responsibilities include coding, design, engineering excellence, cross-project collaboration, and technical leadership, with a focus on AI-native development and agentic experiences.

Principal Research Software Engineer to provide technical leadership and direct technical contribution on the AI Agentic Core Team. The mission is to accelerate the path from research to product by building AI-driven systems, workflows, and platforms that help researchers and product teams move faster from exploration to real-world impact. This role involves collaborating with engineers, researchers, and product teams to build high-impact systems spanning early-stage prototypes through production-ready tools, services, and experiences, while modernizing how software is designed, built, evaluated, and shipped. The role requires designing, developing, and shipping systems that transition MSR concepts into production-quality tools, services, and product capabilities, owning the end-to-end engineering lifecycle. It also involves defining and implementing AI-driven processes that accelerate research-to-product pipelines using LLMs, agentic workflows, and modern developer tooling, including designing and integrating agentic AI frameworks and LLM-based pipelines, developing tool-use and function-calling architectures, and applying prompt design, RAG, and evaluation frameworks. Contributions to model experimentation and fine-tuning are also part of the role.

Seeking a Senior Machine Learning Engineer for Microsoft Teams Calling, Meeting & Devices group to deliver next-generation innovations using foundation models, fine-tuning, and prompt engineering. The role involves developing and deploying conversational and language understanding models at scale, creating ML pipelines, and collaborating with research and AI groups to build AI innovations in products and services.