Cloud Solution Architect focused on AI solutions, primarily Microsoft 365 Copilot, Copilot Studio, and Copilot Chat, to drive customer AI transformation. The role involves understanding business requirements, designing and implementing AI agent solutions, providing technical support, and maximizing business value and ROI for enterprise clients.

Senior Consultant role focused on designing, developing, and deploying AI-powered full-stack applications on Microsoft Azure. Requires strong full-stack engineering skills combined with applied AI capabilities, particularly in LLM and agentic AI solutions using frameworks like Semantic Kernel, LangChain, and RAG patterns. The role involves technical leadership, customer engagements, and ensuring solutions are scalable, secure, and aligned with business objectives and Responsible AI principles.

Lead and grow a team building and operating world-class research compute infrastructure, including large-scale GPU clusters and agentic development tools, for Microsoft Research globally.

This Principal Software Engineer role on the Microsoft Playwright team focuses on integrating AI-native and agentic capabilities into test automation. The engineer will design and implement systems enabling autonomous agents to reason about, generate, and validate software behavior, advancing Playwright's runtime, infrastructure, and tooling. The role emphasizes AI-assisted development and intelligent automation within the modern developer workflow.

This Director role focuses on leveraging AI and AI-enabled tools to accelerate technical due diligence, product integration, and decision-making for Microsoft's strategic deals (acquisitions, divestitures, data/IP transactions). The role involves leading cross-functional teams, assessing technical risks (including AI/ML, security, privacy, compliance), developing integration plans, and driving innovation in AI-first workflows to improve efficiency and decision quality in a rapidly evolving AI market.

Senior Software Engineer for Microsoft Copilot's backend platform, focusing on scaling AI services, integrating AI models, and providing tools for engineers. Requires strong backend and cloud infrastructure experience.

Senior 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.

Senior Security Engineer focused on identity security, translating threats into AI-first engineering requirements, analyzing advanced attacks using large-scale telemetry, designing detections, and building automation for investigation and response within Microsoft Security's Identity Security Breach Response Squad.

This role focuses on building and scaling the backend platform for Microsoft Copilot, integrating with AI models and empowering Copilot teams. The engineer will design, develop, and maintain performant and secure AI Platform services, ensuring reliability, scalability, and performance. The role requires experience with public cloud infrastructure, containerization, and production software development.

Principal Data Scientist role focused on applying advanced analytics and data science to solve complex business problems for Microsoft's strategic customers. The role involves shaping data science strategy, defining reusable patterns, and leading technical direction across engagements, with a strong emphasis on business understanding, data preparation, modeling, and evaluation in a customer-facing consulting and engineering context.

This role is for a Platform Engineering Manager at Microsoft AI, focusing on building and scaling the AI platform services that power Copilot. The role involves managing a team to develop secure, performant APIs for finetuning and deploying core AI experiences, collaborating with various teams, and ensuring high-quality code delivery in a fast-paced consumer-facing environment.

This role is for a Data Engineering Manager within Microsoft AI's Copilot team. The primary responsibility is to build and manage scalable data pipelines that ingest, process, and publish data streams for AI use cases, specifically for fine-tuning models and improving human-AI interactions. The role involves managing a team of data engineers and ensuring operational excellence for the data platform.

This role focuses on building and operating the foundational GPU accelerated infrastructure for large-scale AI training and inference across Azure. It involves designing systems for GPU management, scheduling, isolation, and sharing, as well as optimizing performance, reliability, and utilization of GPU fleets. The role also requires driving end-to-end platform features, including observability and diagnostics, and influencing platform architecture.

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.

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.

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.

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.

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.

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.

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.

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.

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.