Principal Applied Scientist to define and develop next-gen intelligent, large-scale content platforms for AI-driven experiences. Responsibilities include modeling, experimentation, product impact, and technical leadership in areas like LLMs, information retrieval, ranking, grounding, search systems, and agentic AI. Focus on improving AI system information retrieval, reasoning, multi-turn conversations, tool use, response ranking, and grounded outputs. Requires hands-on experience tuning models at scale (SFT, preference optimization, distillation, data curation, evaluation, experimentation). Role involves leading scientific workstreams, influencing product direction, and collaborating with cross-functional teams.

The Principal Applied Scientist will drive the applied science foundation for observability in AI agents and multi-agent systems at scale. This role focuses on understanding agent behavior in production, developing scientific methods, evaluation frameworks, and measurement systems to diagnose and improve agent-based systems. Responsibilities include developing evaluation and measurement frameworks, designing methodologies to connect offline evals with online signals, defining quality signals and benchmarks for agent systems, building models for behavior analysis, advancing observability through new approaches, partnering with engineering to operationalize methods, and contributing to instrumentation standards. The role also involves technical leadership, setting scientific direction, and collaborating with product and platform teams.

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.

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.

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.

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 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.

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 designing, shipping, and operating agentic support platforms and AI-driven autonomous support workflows for Microsoft's commercial business. The role involves end-to-end ownership of features, including orchestration, grounding, evals, observability, and SDK surfaces, with a strong emphasis on reliability, trustworthiness, and scalability of AI-managed support systems.

Principal Applied Scientist to lead the development of ML and generative AI systems for conversational commerce experiences within Microsoft Copilot. The role involves product discovery, ranking, personalization, reasoning, LLM-based systems, RAG, tool orchestration, and addressing quality/trust challenges, with a focus on shipping low-latency, reliable user-facing features. Technical leadership and Responsible AI practices are also key.

Principal Software Engineer focused on building AI-powered security systems for Microsoft's cloud environment. The role involves designing, building, and operating production AI services that combine LLMs, agentic workflows, RAG, knowledge graphs, and multi-modal processing, with a strong emphasis on evaluation, responsible AI, and scalability within a large cloud platform. The candidate will lead architecture, design, and delivery of these systems, collaborating across various teams to translate AI advances into practical security solutions.

AI Engineer role focused on designing, building, and deploying AI-native systems for enterprise customers to securely adopt AI at scale. This involves working across the AI lifecycle, including model development, data pipelines, deployment, monitoring, and MLOps, with a focus on LLM-based applications, RAG, and agentic workflows within a security context.

Senior Software Engineer to design and ship core components of an Agentic support platform, owning features end-to-end from prototype to production. Responsibilities include working across orchestration, grounding, evals, observability, and SDK surfaces, while ensuring production-readiness, trustworthiness, and scalability of AI-managed support systems.

Principal Software Engineer to build AI capabilities that automate red team engagements using generative AI and agentic systems, advancing state-of-the-art attacker TTPs, and building online services for security defenders.

This internship focuses on applying advanced machine learning techniques to solve complex business challenges in areas like search, personalization, NLP, computer vision, and recommendation systems. The role involves developing and scaling models, preparing datasets, building ML pipelines, and collaborating with cross-functional teams to deliver product-integrated solutions, with a focus on influencing future AI experiences.

Principal Applied Scientist role focused on designing and developing LLMs and underlying subsystems for Microsoft 365 Copilot and Agents Core. The role involves tailoring models for product scenarios, working with research and engineering teams, and delivering joint-class solutions, including custom LLMs and architecture for specific product needs.

Senior Software Engineer to design and ship core components of an agentic sales platform, owning features end-to-end from prototype to production. Responsibilities include working across orchestration, grounding, evals, observability, and SDK surfaces, while raising the bar for agent development and evaluation. Requires experience building with agent stacks and a strong understanding of AI-native development principles.

Senior Data Scientist role focused on end-to-end delivery of strategic data science and AI solutions for clients, including generative AI applications and agentic AI solutions. Responsibilities include business understanding, data preparation, modeling, insight communication, and collaboration, with a strong emphasis on responsible AI principles and integrating AI into client workflows.

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.

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 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.

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.

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.

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.

Research Intern role focused on agentic programming, involving building agentic workflows and ML models for software engineering tasks, within a PhD program context.

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.

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.

This role involves partnering directly with customers to translate real-world problems into production-grade AI solutions using cutting-edge AI innovation. The Forward Deployed Engineer will design, develop, and deploy sophisticated AI-powered systems at scale, engineer data pipelines, build custom applications, and deploy scalable workflows. The role also involves monitoring, refining, and driving adoption of built solutions, and sharing field insights to influence AI platform direction. Requires a strong balance of AI understanding and practical software engineering experience, with a focus on generative AI and ML/LLM-based solutions in production.

Senior/Principal Software Engineer role focused on building and improving intelligent systems, specifically agents and evaluation frameworks, within the Microsoft Security organization. The role involves leading complex technical problem-solving, partnering with customers, translating customer needs into scalable product capabilities, and driving experimentation and learning loops for product improvement. Emphasis on end-to-end ownership, engineering standards, and mentorship.

Senior Data Scientist role focused on applying machine learning and AI agents to sales compensation and incentive plans. The role involves designing, developing, and implementing ML solutions, building data pipelines, and leveraging Microsoft's AI/ML stack to drive insights and improve sales operations. The position requires strong business acumen in sales compensation and the ability to translate business context into analytical frameworks.

Principal Researcher role within the Office Product Group at Microsoft, focusing on advancing AI-powered experiences embedded in Microsoft 365 applications. The role involves designing, developing, evaluating, and deploying AI systems that can reason and act across tools and documents, with a strong emphasis on scaling these capabilities to a large user base. Key responsibilities include developing frameworks for AI component coordination, improving code generation, implementing fine-tuning and post-training for LLMs, designing evaluation strategies for real-world workflows, and collaborating to translate research into production-ready features.

Senior Software Engineer to join the Microsoft Discovery team, working on an AI-driven platform that transforms the scientific research process using AI agents and high-performance computing. The role involves designing and building scalable, distributed systems, driving features from ideation to rollout, mentoring engineers, and improving engineering velocity with AI-enabled enhancements. Collaboration with Microsoft Research and platform teams is key, along with applying site-reliability engineering practices.

Solution Architect role focused on designing and deploying solutions leveraging Microsoft technologies, particularly Copilot and Agentic solutions. The role involves gathering client requirements, architecting solutions, building technical capabilities, and supporting pre-sales and implementation. It emphasizes deep product knowledge in Business Applications, Modern Work, Copilot, and Agentic solutions, with a focus on AI applications.

This role focuses on developing user-facing Generative AI features and building AI agent platforms, requiring a blend of AI knowledge and software development expertise to deliver scalable, high-quality solutions for enterprise clients.

Software Engineer II role focused on building and maintaining enterprise AI agent systems for security customers. This involves designing, developing, and integrating AI agents with enterprise platforms, ensuring data privacy, compliance, and responsible AI practices, and supporting agent operations in production.

Senior Solution Architect for Microsoft Industry Solutions Delivery (ISD) Canada, focusing on architecting and delivering AI-powered enterprise solutions using emerging Microsoft platform capabilities. The role involves leading technical teams, driving AI-first delivery practices, and ensuring engineering-grade rigor in solution design and implementation at enterprise scale.

Software Engineer II 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 features, and robust data pipelines, with a strong emphasis on AI engineering, evaluation, and operationalization of LLM systems.

Software Engineer II role focused on building LLM-powered data engineering experiences and infrastructure for Microsoft Fabric. The role involves implementing agentic workflows, LLM-backed data features, and operationalizing AI/ML features, with a focus on full-stack development including React-based UX and backend services in .NET/Python.

Software Engineer II to build key features across the Copilot stack in Bing, spanning backend services, LLM prompting, and cross-surface UI experiences. The role involves creating AI-powered experiences for real-world decision-making, integrating Search, Maps, and Copilot.

Senior Product Manager for Commercial Engineering & AI (CEAI) at Microsoft, focusing on transforming the support ecosystem into an AI-first, agent-powered model. The role involves owning and delivering AI-powered support experiences and agent-based workflows to improve customer outcomes and operational efficiency at global scale. Responsibilities include defining product vision, leading design and delivery of AI-powered experiences, driving product execution, and using data and experimentation for continuous improvement.

Senior Software Engineer role focused on building and integrating cutting-edge AI into Microsoft products and services within the Copilot, Agents, and Platform (CAP) group. The role involves applied research, ML engineering, and product innovation, with a focus on shipping reliable, production-grade AI systems from model development to deployment. Responsibilities include backend system design, end-to-end ownership, data and platform infrastructure, performance optimization, and cross-functional collaboration.

Product Manager II for Microsoft Foundry, focusing on building and scaling an AI-first application stack, including agent runtimes, orchestration, and a model serving platform. The role involves defining product offerings, identifying opportunities for team velocity, tracking metrics, managing dependencies, and communicating with executives.