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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 Software Engineer II, you will be responsible for driving the architecture, design, and implementation of AI-first experiences across the Dynamics 365 Sales and Service platform. This role blends AI/ML and software engineering experience, applied at scale to mission-critical enterprise SaaS applications. You will work with engineering, product, design, data science, and infrastructure teams to deliver intelligent, secure, and customer-centric solutions. You will determine strategic decisions and contribute directly to production systems used by some of the world’s largest enterprises. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Job Responsibility:
Apply both software engineering and AI experience to build intelligent, scalable solutions that power Dynamics 365 services used globally
Collaborate with cross-functional teams to deliver high-impact features aligned with enterprise standards and cloud-scale requirements
Design and develop highly usable, scalable application capabilities, integrating AI models and enhancing existing features to meet evolving customer needs
Build and debug production-grade code in distributed systems
Translate business requirements into AI solutions, collaborating with data scientists, product managers, and engineering teams to ensure alignment and impact
Optimize AI model performance and reliability in production environments, including retraining, evaluation, and continuous monitoring
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 with applied scientists, product managers, and UX teams to translate customer needs into intelligent capabilities that deliver measurable business value
Drive engineering by establishing high standards for code quality, observability, testing, MLOps, and secure deployment practices
Proactively identify technology gaps, evaluate emerging AI frameworks/tools (including open-source and Azure AI offerings), and champion adoption where appropriate
Embody our culture and values
Requirements:
Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience
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 technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
2+ years of experience delivering AI/ML-based systems at production scale including LLMs, transformers, RAG pipelines, or similar architectures
1+ year of experience leading engineering teams or cross-functional initiatives involving AI systems in cloud environments
1+ year of experience designing and deploying AI-first applications at scale focusing on performance, privacy, compliance, and operational constraints in enterprise SaaS
1+ year of experience in MLOps/LLMOps, including model versioning, retraining pipelines, A/B testing, monitoring, and rollout strategies
1+ year of experience with cloud platforms (preferably Azure) and experience deploying containerized AI services using Kubernetes, Docker, or similar
1+ year of experience integrating models from Azure AI, OpenAI, HuggingFace, or custom-trained models into scalable application pipelines
1+ year of experience working in highly regulated or secure environments, including Zero Trust, privacy, and compliance practices
1+ year of experience working with or building solutions for customer service, CRM, or enterprise productivity scenarios