Senior Software Engineer role on the Microsoft Teams AI Platform team, focusing on building and operating high-scale backend services that enable AI agents to work seamlessly across Teams. The role involves designing and developing foundational infrastructure, collaborating with AI teams, and ensuring high standards of availability, reliability, and performance for features impacting millions of users.

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.

Seeking a Senior AI Development Consultant to lead AI/agent development for enterprise clients using Microsoft Copilot, Copilot Studio, and Azure AI. Responsibilities include architectural design, technical implementation, custom agent development, data and AI foundation building with Microsoft Fabric, and RAG architecture implementation. The role involves end-to-end project delivery and technical support for client workstyle transformation.

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.

Lead a team of engineers to build and manage LLM evaluation solutions for Microsoft Copilot, focusing on quality, reliability, and scalability. This role involves designing evaluation platforms and techniques to measure and improve the performance of AI companions.

Senior Software Engineer to join the Evaluation platform team within Core AI, focusing on building core services for large-scale agent observability and optimizing AI agent performance.

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.

Senior Software Engineer on the Path team, focused on modernizing work management with AI by pioneering LLMs and advanced Agentic frameworks. The role involves using AI agents to automate tasks and create intelligent assistants to streamline workflows.

Engineering Manager for Microsoft AI's Copilot product, focusing on full-stack development, team leadership, and shipping AI-powered experiences. The role involves hands-on coding, architectural guidance, and working across data sampling, collection, processing, analysis, and insights stages of the evaluation platform. Prompt engineering and extensive use of AI tools are also key aspects.

Product Manager for Visual Studio Copilot, focusing on AI-powered developer experiences within the IDE. The role involves defining product strategy, roadmaps, and end-to-end workflows for chat, code completions, and agentic capabilities, requiring close collaboration with engineering, design, research, and data science teams. The goal is to enhance developer productivity while ensuring quality, control, and trust, with a strong emphasis on enterprise readiness and competitive differentiation.

Solution Engineer focused on helping enterprise customers adopt and integrate Microsoft's Cloud & AI Applications, including AI Foundry and Azure AI. The role involves driving technical sales, leading hands-on engagements (PoCs, hackathons), co-designing secure and scalable AI architectures, and resolving technical blockers. Expertise in Agentic AI frameworks, Responsible AI, and cloud-native development is required to accelerate AI application development and deployment.

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.

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.

Research intern to conduct research and lead collaborations on incorporating AI capabilities into Azure SQL Database platform. Focus on advancing state-of-the-art in machine intelligence and machine learning applications, implementing prototypes, and developing solutions for large-scale problems. Experience with LLMs and ML techniques is preferred.

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.

The Principal Applied Scientist will work on Microsoft's Experimentation Platform (ExP) within CoreAI, focusing on enabling high-scale online experimentation for AI-driven applications. This role involves advancing experimentation methodology and agent evaluations, collaborating with various engineering and science teams, and translating applied research into production features for a large-scale platform. The goal is to accelerate product learning and drive progress across Microsoft's AI ecosystem by providing robust experimentation capabilities.

This role focuses on building cross-cutting capabilities for Microsoft Copilot, aiming to create revolutionary AI-powered experiences across modalities (text, voice, vision, action). The engineer will own features end-to-end, collaborate with applied AI researchers, and ship experiments rapidly to millions of users, defining the future of human-AI interaction.

Product Manager for Microsoft AI, focusing on building AI-powered consumer products and services that leverage advertising and new business models. The role involves understanding user needs, defining product requirements, managing end-to-end product development, and collaborating with cross-functional teams to deliver AI-first products.

Senior Data Scientist role focused on end-to-end delivery of strategic data science and AI solutions for enterprise clients. Responsibilities include understanding business needs, preparing data, building and deploying predictive and generative AI models, integrating AI applications, and communicating findings to stakeholders. The role emphasizes prompt engineering, fine-tuning, and evaluation strategies for LLMs and foundation models, with a strong focus on responsible AI principles and business impact.

Principal Software Engineer focused on building and integrating Responsible AI services, ensuring high availability, scalability, and low latency for customer-facing AI applications within Microsoft's CoreAI organization. This role involves end-to-end ownership of the development lifecycle, evaluating architectures, and upholding software engineering best practices.

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.

This role focuses on designing and leading end-to-end enterprise data, GenAI, Copilot, and agentic AI architectures. The Solution Architect will translate business requirements into scalable, secure, and governed solutions, own data platform design for AI readiness, and define GenAI solution patterns including RAG and grounding strategies. They will also lead the architecture for Copilot and AI-augmented applications, integrating AI services into business workflows.

Principal Software Engineer within Microsoft's Office of the CTO (OCTO) to build AI-based systems that accelerate the deployment of OpenAI technology across Microsoft. This role involves collaborating with key technical teams at Microsoft and OpenAI to create the technical foundation for their partnership, focusing on building and shipping robust AI products, leading system design, and ensuring production reliability, observability, and security.

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.

This role focuses on building and iterating on Responsible AI tools and capabilities to enable developers to build and deploy AI responsibly at scale. It involves prototyping, applying subject-matter expertise, and collaborating across product groups to drive project and release plans. The role emphasizes working in fast-paced, experimental environments and taking ideas from ambiguity to production.

Principal Data Scientist at Microsoft responsible for end-to-end delivery of strategic data science projects, partnering with customers and internal teams to design and implement advanced analytics and AI solutions that create measurable business impact. This role involves leading teams, engaging with stakeholders, applying machine learning, and integrating data models into customer systems, with a focus on Responsible AI principles.

Software Engineers (II and Senior) needed to lead engineering efforts for Teams Copilot, leveraging Generative AI, LLMs, and an AI stack to enhance collaboration and user experience. The role involves end-to-end ownership, prototyping, evaluating new AI features, and developing scalable, reliable services with a focus on live-site operations and data-driven decisions.

This role focuses on building cross-cutting capabilities for AI companions like Copilot, spanning multiple modalities (text, voice, vision, action). The engineer will own features end-to-end, collaborate with AI researchers, and ship experiments rapidly to create user experiences that redefine AI companionship. The role requires strong full-stack fundamentals and comfort with ambiguity in a fast-paced environment.

This role focuses on building and architecting distributed data platforms and pipelines that process massive datasets for AI models, including training, inference, and evaluation. It involves designing event-driven architectures, handling unstructured data, engineering feedback loops for AI, and optimizing compute for cost and performance.

Backend Engineer role focused on building the data foundations for Copilot's memory and personalization features. This involves designing and operating large-scale data pipelines for signal ingestion, normalization, enrichment, aggregation, and memory generation, enabling downstream ML and product consumers. The role also involves technical leadership in data systems and influencing architecture.

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.

Principal Researcher at Microsoft Research focusing on the intersection of AI and society, with an emphasis on sociotechnical approaches to AI evaluation, measurement, and responsible AI in industry. The role involves interdisciplinary research, collaboration with engineering and policy teams, and a strong publication record.

This role focuses on researching and developing next-generation intrusion detection systems by leveraging large-scale security event logs and applying advanced data processing and machine learning techniques. The goal is to achieve accurate and rapid detection of sophisticated attacks.

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.

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.

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.

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.

Research intern to work on multi-modal sensing, device security, and authentication, with opportunities to influence next-generation device design. The role involves prototyping on mobile OS, Android development, and performing preliminary user evaluations. Familiarity with speech interfaces to agents and LLMs is a plus.

Engineering Lead to build and own the software engineering platform for large-scale machine learning retrieval systems, including RAG for Copilots, web-scale search, and personalized recommendations. The role focuses on translating retrieval research into reusable, scalable systems, defining engineering standards, and integrating new methods. It involves cross-team technical leadership and improving developer/researcher experience.

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.

The AI Data Infra team at Microsoft AI is responsible for building data infrastructure to help MAI teams to generate the biggest and best training dataset. This role focuses on designing and developing data pipelines for multimodal training data and owning critical data infrastructures like Spark, Ray, and Vector Databases.

Senior/Principal Security Researcher on the Global Hunting, Oversight, and Strategic Triage (GHOST) team. The role involves performing threat hunts, assisting with investigations, developing threat intelligence, and cultivating investigation best practices into Microsoft tooling and products. Researchers will support a global team to identify and catalog new attacker TTPs, victims, and deliver customer notifications to protect worldwide enterprise customers and empower customers to protect themselves via constantly improving Microsoft products.

Software Engineer on the Path team at Microsoft, focusing on modernizing work management products (Project, Planner, To Do, Visio) with AI. The role involves pioneering LLMs and agentic frameworks to automate tasks and streamline workflows, contributing to the development of AI-powered productivity tools.

This role focuses on building and operating the core platform infrastructure for training, evaluating, and deploying large-scale AI models within Microsoft. It involves designing scalable services for cluster orchestration, job scheduling, data pipelines, and artifact management, with a strong emphasis on production operations, cloud platforms (Azure), and enhancing developer experience for AI research and engineering teams.

Senior Software Engineer to build GitHub's coding agent CLI and the core agent loop powering agentic experiences across GitHub and Microsoft. The role focuses on turning AI systems into reliable developer tools, with an emphasis on agentic systems, tool design, agent loops, benchmarking, quality optimization, and high-performance terminal experiences.

This role is focused on ensuring the reliability, performance, and availability of Microsoft's large-scale AI training infrastructures, which involve tens of thousands of GPUs and advanced networking. The responsibilities include designing transport, fabric architecture, telemetry, observability, and automated troubleshooting for these clusters. The role also involves AI training and inference cluster bring-up, performance benchmarking, and root-cause analysis, with a goal of developing predictive health models and autonomous remediation systems.

Seeking Data Research Engineers to join the Multimodal team, focusing on building next-generation foundation models. The role involves exploring, designing, and building high-quality multimodal datasets (vision, language, audio) for training and evaluation, collaborating with scientists and engineers, and developing scalable data pipelines. Responsibilities include data analysis, quality assessment, building tools for auditing, and ensuring datasets meet responsible AI practices.

This role focuses on building large-scale Copilot memory and personalization systems using RAG, search, embeddings, retrieval, and ranking. The individual will be responsible for designing and implementing these systems, collaborating with stakeholders, and mentoring engineers. Experience with LLM applications and large-scale embedding/retrieval/ranking systems is required.