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 Applied Scientist role focused on building and scaling AI-powered content recommendation systems for Microsoft Copilot Discover. The role involves advancing the recommendation and ranking stack using LLMs and multimodal models, deepening user and content understanding, scaling ML/AI systems, and driving innovation in AI-forward products like agentic content feeds and generative UI. The position requires technical leadership, mentoring, and close collaboration with engineering, product, and policy teams.

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.

Principal Data and Applied Scientist role within Microsoft's EngOps team, focusing on developing and deploying cutting-edge GenAI and ML solutions to improve Azure customer experience, security, reliability, and quality. The role involves the full AI project lifecycle, from ideation to production, with a strong emphasis on experimentation, evaluation, and collaboration with cross-functional teams. Requires experience in building and deploying live production systems and delivering AI product features.

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.

Principal Software Engineer focused on optimizing the performance of AI model inference, particularly LLMs, across various hardware platforms (GPUs, Microsoft silicon). The role involves deep technical work on the AI software stack, from fundamental abstractions to system-level optimizations, aiming to improve efficiency and reduce costs for large-scale AI deployments, including those for Azure OpenAI service.

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.

Principal Applied Scientist Architect for the Core Recommendation Ranking team, focusing on integrating GenAI and agentic systems into large-scale content recommendation and ranking stacks for consumer-facing Microsoft surfaces. The role involves designing, implementing, and architecting advanced ML/DL models, including LLMs, for ranking, reranking, and retrieval, with a strong emphasis on production ML systems at scale and cross-team technical leadership.

This Principal Product Manager role within Microsoft AI focuses on defining the vision, strategy, and execution for AI training pipelines. The role involves leading cross-functional teams to build scalable and high-quality training data collection and processing systems, defining success metrics, and ensuring compliance. It requires deep collaboration with engineering, research, and data science to operationalize new evaluation techniques and metrics for LLM and ML-based products, with a strong emphasis on data processing, infrastructure, and evaluation systems.

Software Engineer role focused on building and managing large-scale GPU infrastructure and training/inference platforms for AI models (LLMs, SLMs, multimodal, code-specific) on Azure and partner clouds. Responsibilities include architecting, designing, and developing core AI infrastructure services, collaborating with researchers, and enhancing system stability, latency, security, and maintainability for training runs.

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.

The AI Frameworks team at Microsoft develops software for training and deploying advanced AI models, collaborating with hardware teams and partners on supercomputers and AI accelerators. This role involves developing and evaluating core algorithmic and hardware technologies for large-scale AI model training and inference, working closely with ML researchers and developers, and with OpenAI on Azure OpenAI service models. The position requires hands-on software design and development skills in languages like Python, C/C++, and CUDA, focusing on LLM optimization technologies, model scripting, and kernel languages.

Principal Software Engineer on the AI Frameworks team at Microsoft, responsible for developing and evaluating core algorithmic and hardware technologies for large-scale AI model training and inference on novel hardware. Collaborates with ML researchers, system engineers, and partners to optimize and scale AI models, build validation tools, and perform software development in languages like Python, C/C++, and CUDA.

This role focuses on researching and developing machine learning models, specifically large language models (LLMs), for Microsoft 365 Copilot. The core responsibilities involve advancing research through projects, developing new algorithms and prototypes, and collaborating with product groups and Microsoft Research. The role emphasizes fine-tuning models for specific applications and contributing to the AI platform infrastructure that enables Copilot workflows. The position requires expertise in LLMs, deep learning, and responsible AI, with a strong emphasis on shipping applied research to production.

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.

This role focuses on building and optimizing training data pipelines and evaluation frameworks for audio models, with a secondary focus on model tuning and deployment. The engineer will be responsible for data sourcing, cleaning, labeling, QA, versioning, and lineage, as well as developing evaluation frameworks and driving continuous quality improvements. They will also optimize training and inference performance for latency, throughput, cost, and reliability.

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 Scientist II role at Microsoft focusing on integrating AI research into productivity products like M365 Copilot. The role involves defining and leading research projects, collaborating with cross-functional teams, and contributing to the scientific community through publications. Research areas include reinforcement learning, agentic systems, multimodal modeling, post-training techniques, and LLM applications.

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.

Principal Applied Scientist role at Microsoft AI Web Data team, focusing on building the data foundation for Bing and Microsoft AI experiences. This involves large-scale grounding, LLM training, and end-to-end processing of web content. The role translates research into production, advancing state-of-the-art modeling and deploying algorithms to improve system performance and accuracy.

Senior Software Engineer focused on building Responsible AI services, including identifying, measuring, mitigating, and monitoring AI risks across various content types. The role involves designing and developing large-scale distributed cloud services with a focus on safety, governance, inference, evaluation, and multimodal safety infrastructure.

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.

Senior Researcher focused on advancing efficiency across the AI stack for generative AI serving systems, spanning models, ML frameworks, cloud infrastructure, and hardware. The role involves algorithmic and systems optimization for latency, throughput, and cost, with a strong emphasis on driving research ideas through prototyping, validation, and production deployment.

Lead the science behind Copilot Discover's ranking and content-quality stack, combining LLMs, multimodal models, and large-scale recommender systems to drive measurable gains in engagement, satisfaction, and trust. This role involves setting technical direction, mentoring scientists, and partnering with engineering, PM, UXR, and policy to ship end-to-end outcomes.

Research intern position focused on computer vision and deep learning to improve user understanding of devices and environments. Involves analyzing multimodal sensor data and human-object interactions to enhance human-computer interactions, with opportunities to advance the state of the art.

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.

Principal Product Manager for Microsoft Edge, focusing on defining and executing an AI-native product strategy to enhance user experience and collapse the distance between user intent and accomplishment. The role involves inventing new AI-driven features, translating frontier AI capabilities into customer-facing products, and driving product strategy from research to shipped product.

Seeking a Design leader to own the end-to-end design quality of AI model personality, tone, and user-facing experiences. This player-coach role involves hands-on IC work (80%) and coaching a small team (20%) of model and UX designers. Responsibilities include defining the creative vision, shaping model personality, driving UX for product surfaces, and building evaluation systems for design quality. The role requires a strong design craft, intuition for language and personality, and the ability to ship regularly.

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 AI Software Architect role focused on enabling and optimizing machine learning model training workflows on custom hardware (MAIA accelerators). Requires expertise in PyTorch, Triton/CUDA, and understanding of accelerator architecture for efficient deployment of large models.

Principal Software Engineer focused on optimizing GPU inference for large-scale deep learning models (LLMs/SLMs) within Microsoft's AI-native monetization platform, serving ads, shopping, and Copilot.

Product Manager for Microsoft Foundry's AI Models & Training organization, focusing on platforms and infrastructure for training, evaluating, launching, and operating AI models at scale. The role involves defining product strategy and roadmaps for model training, inference, experimentation, and platform enablement, driving initiatives across the AI model lifecycle, and enabling internal teams and customers to access and adopt models. Requires strong technical fluency, ability to lead cross-functional initiatives, and experience with AI/ML platforms and infrastructure.

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.

Principal Engineer on the AI Core Infrastructure team, responsible for large-scale GPU management infrastructure and inference/training platforms powering Microsoft's AI workloads. The role involves setting roadmaps, designing backend services, and providing insights for customers to monitor, troubleshoot, and scale AI training workloads on supercomputers. Focus on ML infrastructure, distributed systems, and observability.

Principal Software Engineer on the AI Frameworks team at Microsoft, focusing on developing and optimizing software for running AI models across diverse hardware platforms. This includes working on ONNX, ONNX Runtime for high-performance inferencing and training acceleration, and Foundry Local for on-device inference.

Product Designer for Microsoft's Superintelligence Team, focusing on end-to-end UX for AI product surfaces like MM Labs and Playground. This role leverages AI-native tools and agentic coding workflows to rapidly prototype and ship UI, bridging the gap between design and engineering. The designer will collaborate with researchers and model designers, contribute to design systems, and use data to inform decisions, with a high bar for visual craft and interaction quality.

Principal Software Engineer role focused on building and supporting large-scale GPU management infrastructure and inference/training platforms for AI workloads at Microsoft. The role involves architecting, designing, and developing core AI infrastructure services and compute, storage, and networking subsystems for LLM training, customization, and inference.

Senior Software Engineer focused on building and optimizing foundational inference engines and APIs for large-scale AI inference across Azure. The role involves improving latency, throughput, availability, and cost for LLMs, working with OpenAI and open-source models, and developing experimentation capabilities for safe and rapid iteration.

Principal Software Engineer focused on building and optimizing foundational inference engines and APIs for large-scale AI inference across Azure. The role involves driving production-grade serving improvements for OpenAI and open-source LLMs, focusing on latency, throughput, availability, and cost efficiency. Responsibilities include making hands-on engine changes, building experimentation capabilities, and designing inference serving architectures to support multitenant AI systems at global scale.