Microsoft

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.

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.

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.

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.

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 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.

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.

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 AI Platform Engineer role focuses on building and improving systems within the response quality stack for AI products at Microsoft. This includes data pipelines, evaluation frameworks, RAG, and inference serving. The role involves designing and operating a data flywheel to collect production signals for model improvements, identifying and fixing quality degradation, shipping production retrieval systems, and collaborating with researchers and cross-functional teams to translate quality insights into shipped improvements. The position requires production code ownership end-to-end and emphasizes rapid iteration and deployment.

Senior Applied AI Engineer role focused on building and shipping LLM-powered assistant features and agentic systems. Responsibilities include designing and developing conversational flows, retrieval pipelines, and multimodal interactions using prompt architectures and orchestration logic. The role also involves building evaluation frameworks, running hillclimbing loops for continuous improvement, and developing internal tools for experimentation and debugging. Integration with product surfaces and building lightweight ML components are key. The team operates with startup energy in a fast-moving AI environment.

This role focuses on building and optimizing AI Agents with world-class orchestration and inference layers. The engineer will develop secure and performant AI Platform services that power products like Copilot, working collaboratively with researchers and other engineers to create next-generation AI products and services. The emphasis is on shipping high-quality, well-tested, secure, and maintainable code within a fast-paced development cycle.

Applied Engineer II role focused on developing and integrating AI technologies, including foundation models, prompt engineering, RAG, and multi-agent architectures. The role involves fine-tuning models, evaluating behavior, building prototypes, and deploying solutions into production, with a strong emphasis on responsible AI and ethical considerations.

This role focuses on prompt engineering for an AI companion, aiming to create empathetic and collaborative user experiences. Responsibilities include designing prompting techniques, establishing frameworks for social and ethical navigation, and creating evaluations for AI behavior. The role requires experience with chain-of-thought prompting, scaled implementation of prompted systems, and evaluation design.

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.

Senior Applied AI Engineer for the Customer Service Applications Team, focusing on developing and integrating AI technologies, including foundation models, prompt engineering, RAG, graphs, and multi-agent architectures, into Microsoft products. The role involves fine-tuning models, evaluating their behavior, building prototypes, contributing to production deployment, and translating research into scalable, impactful solutions. Emphasis on responsible AI practices and leveraging AI for real-world customer service outcomes.

This role focuses on building and scaling large-scale AI systems for Copilot memory and personalization, leveraging technologies like RAG, embeddings, retrieval, and ranking. The engineer will be responsible for designing and implementing these systems, collaborating across product groups, and ensuring system reliability and performance.

Principal Software Engineer to architect and implement an agentic auto-bidding platform for digital advertising, leveraging AI, machine learning, and large-scale distributed systems to optimize bids in real-time across Microsoft's marketplaces. The role involves defining requirements for AI-driven capabilities, building data validation frameworks, ensuring operational excellence, and exploring emerging AI techniques like multi-agent systems.

Principal Applied Scientist role focused on building and shipping AI agentic applications and predictive models for Viva Engage. The role involves end-to-end delivery of ML capabilities, including problem framing, data handling, modeling, evaluation, experimentation, deployment, and monitoring. Emphasis is on production-viable solutions, leveraging LLMs and generative AI for knowledge discovery, moderation, recommendations, and enhancing user experiences. The position requires hands-on coding in production environments and driving measurable product impact.

The Principal Software Engineer will work on an auto-bidding platform for digital advertising, leveraging AI, machine learning, and large-scale distributed systems. The role involves designing and building an agentic bidding platform that processes billions of auction events daily, optimizing bids in milliseconds. Responsibilities include defining requirements for agentic AI-driven bidding capabilities, architecting the next-generation platform, building data validation frameworks, driving operational excellence, developing experimentation frameworks, adopting new technologies, mentoring engineers, and exploring emerging AI techniques like multi-agent systems.

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.

Full Stack Engineer to build LLM-powered data engineering experiences and infrastructure for Microsoft Fabric. The role involves implementing agentic workflows and scalable LLM-backed data features, focusing on AI Engineering and modern LLM-based systems.

Software Engineer II role focused on building foundational platforms for intelligent agents and generative AI systems within Microsoft Foundry. The role involves developing large-scale, cloud-native systems for the end-to-end agent lifecycle, including secure enterprise deployment, tool integration, model fine-tuning, and production observability/evaluation. It sits at the intersection of distributed systems, AI infrastructure, and developer platforms.

This role focuses on delivering enterprise AI solutions using Azure OpenAI, Azure AI Services, and custom machine learning. It involves designing and implementing secure, advanced agentic AI systems and optimized RAG architectures, requiring expertise in full-stack application engineering, cloud-native architecture on Azure, and DevOps. The role also emphasizes solutioning, pre-sales, and technical leadership, with a requirement for relevant Azure AI certifications.

Principal Software Engineer to lead architecture and delivery of a Teams-integrated product (Innovation Studio) that uses agentic AI workflows, Azure-native services, and modern web experiences to help organizations run hackathons and accelerate ideas. The role involves defining how the team uses agentic development itself for various SDLC stages.

This role focuses on building and extending AI-driven agents for incident triage, classification, and automation within Microsoft's Azure Data engineering team. The goal is to replace manual operations with engineered solutions, improving the stability and efficiency of cloud-scale data infrastructure.

This role focuses on architecting and designing AI solutions, specifically leveraging Microsoft's Copilot and agent technologies, to address customer business challenges. The architect will assess customer AI readiness, translate business requirements into technical solutions using Power Platform, Azure, and Microsoft 365 Copilot, and ensure scalable, secure, and compliant deployments. The role involves close collaboration with customers, product engineering, and delivery teams to drive adoption and validate business value.

This role focuses on co-engineering Generative AI and agentic solutions for enterprise customers on Microsoft platforms. The consultant will translate ambiguous business needs into requirements, design and implement GenAI/agentic solutions, prototype rapidly, and ensure production-ready implementations with testing, monitoring, and secure deployment. Key responsibilities include identifying and mitigating AI-specific risks, building agentic workflows with tool invocation and guardrails, and implementing evaluation strategies for AI output quality and safety.

Senior Consultant, AI Business Solutions at Microsoft, focusing on co-engineering GenAI and agentic solutions for customers on Microsoft platforms. The role involves translating ambiguous business needs into working prototypes and production-ready solutions, with an emphasis on end-to-end delivery, risk mitigation, and evaluation of AI outputs. Requires strong engineering and consulting skills to deliver measurable business outcomes.

Senior Software Engineer role focused on integrating AI capabilities into traditional computer systems and products across Microsoft's Experiences & Devices division. The role involves formulating design patterns, creating prototypes, architecting solutions, and delivering AI-enabled experiences, with a focus on agent-based systems and AI integration into agent workflows.

Software Engineer role focused on building an agentic engineering platform for AI-powered productivity across Microsoft's codebases, involving AI models and orchestration frameworks.

Senior Software Engineer role focused on building an agentic engineering platform for Microsoft developers, leveraging AI models and orchestration frameworks to enhance software engineering workflows like code refactoring and understanding. The role involves designing, developing, and deploying platform capabilities, applying AI-assisted development tools, and mentoring other engineers.

This Principal Software Engineer role focuses on building a new AI agent platform for enterprise use within Microsoft Copilot Studio. The role involves designing and delivering scalable, secure, and reliable platform capabilities for autonomous agents that can perform multi-step work, operate across contexts, and integrate with Microsoft 365 and Power Platform tools. The position is at the intersection of distributed systems, applied AI, and user experience, requiring leadership in system design, technical execution, and championing engineering excellence.

Applied Scientist II role on the Bing Places team, focusing on building and shipping AI/ML solutions for local search experiences. The role involves end-to-end work from problem formulation to production deployment, with a focus on LLMs, RAG, learning-to-ranking, and entity understanding. Collaboration with engineering and product partners is key, with opportunities for publications and patents.