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Microsoft Corporation Logo Microsoft Corporation · IT - Software Development

Principal Applied AI Engineer

United States, Redmond 139900.00 - 274800.00 USD / Year · Job Posted February 04, 2026
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Job Description

Microsoft Dynamics 365 powers mission-critical business operations across the globe. Within this ecosystem, the Customer Experience Applications (CX Apps) team delivers Dynamics 365 Sales and Service an AI-native solution enabling organizations to build intelligent, scalable, and omnichannel customer service operations through voice, chat, SMS, and more. As a Principal Applied AI Engineer, you will be a principal technical leader responsible for driving the architecture, design, and implementation of AI-first experiences across the Dynamics 365 Sales and Service platform. This role blends deep AI/ML expertise with modern software engineering excellence, applied at scale to mission-critical enterprise SaaS applications. You will work across boundaries partnering with engineering, product, design, data science, and infrastructure teams to deliver intelligent, secure, and customer-centric solutions. You will influence strategic decisions, guide junior engineers, and contribute directly to production systems used by some of the world’s largest enterprises. We are looking for a results-driven, hands-on technical leader who thrives in fast-paced environments, thinks end-to-end, and brings both a strong systems mindset and deep AI/ML experience to solve enterprise-grade challenges.

Job Responsibility

  • Own architecture, strategy, and execution of AI-powered features across Dynamics 365 Sales and Service, ensuring technical alignment with Microsoft’s cloud-scale services and AI platform direction
  • Design and deliver production-ready AI solutions that leverage large language models (LLMs), natural language understanding, speech, and real-time reasoning to improve agent productivity and customer satisfaction
  • Lead complex technical initiatives, including AI model integration, platform scalability, reliability, and long-term maintainability
  • Collaborate deeply with applied scientists, product managers, and UX teams to translate customer needs into intelligent capabilities that deliver measurable business value
  • Drive engineering rigor across the team by establishing high standards for code quality, observability, testing, MLOps, and secure deployment practices
  • Mentor engineers across levels, fostering a culture of innovation, inclusivity, and continuous learning
  • Proactively identify technology gaps, evaluate emerging AI frameworks/tools (including open-source and Azure AI offerings), and champion adoption where appropriate
  • Act as a technical advisor across the broader organization, contributing to cross-team initiatives and long-term architectural planning

Requirements

  • Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
  • 2+ years of experience delivering AI/ML-based systems at production scale, ideally including LLMs, transformers, RAG pipelines, or similar architectures
  • Demonstrated experience leading engineering teams or cross-functional initiatives involving AI systems in cloud environments
  • Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter

Nice to have

  • 8+ years of hands-on software engineering experience with deep expertise in languages such as C#, Python, Java, or equivalent
  • Proven track record of designing and deploying AI-first applications at scale, with deep understanding of performance, privacy, compliance, and operational constraints in enterprise SaaS
  • Expertise in MLOps/LLMOps, including model versioning, retraining pipelines, A/B testing, monitoring, and rollout strategies
  • Deep knowledge of cloud platforms (preferably Azure) and experience deploying containerized AI services using Kubernetes, Docker, or similar
  • Hands-on experience integrating models from Azure AI, OpenAI, HuggingFace, or custom-trained models into scalable application pipelines
  • Strong architectural and systems thinking—capable of making trade-offs between performance, cost, simplicity, and maintainability
  • Exceptional written and verbal communication skills with the ability to influence across roles and levels
  • Experience working in highly regulated or secure environments, including Zero Trust, privacy, and compliance practices
  • Prior experience working with or building solutions for customer service, CRM, or enterprise productivity scenarios is a strong plus
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