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As a Research Engineer II at Microsoft you will apply both software engineering and AI expertise to design, build and implement cutting-edge solutions within Dynamics 365 Contact Center organization. You’ll collaborate with Research Scientists, business and technology leaders, internal users, and partners to design and build inclusive, ethical, impactful and scalable, production-ready systems that leverage AI to solve complex business problems. In this role, you are expected to bring software engineering fundamentals—architecture, design, coding, testing, and deployment—while also selecting and integrating the most effective AI models and frameworks to deliver measurable impact and innovation.
Job Responsibility:
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, research 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 deployment, quality and operation of AI systems, including automated evals, CI/CD pipelines, deployment, and monitoring with strong MLOps and DevOps practices
Troubleshoot live site issues as part of both product development and live site support rotations, ensuring rapid resolution and learning
Requirements:
Bachelor's Degree in Computer Science or related technical field AND 4+ 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 professional experience working with generative artificial intelligence, large language models, or agent-based systems
Ability to meet Microsoft, customer and/or government security screening requirements
This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter
Nice to have:
Master's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
Deep understanding of Distributed System Design, Design patterns, Algorithms, SDLC and Software Engineering experience
AI & Domain Expertise: Deep expertise in one or more AI domains, with a proven track record of deploying and scaling AI models in cloud environments
MLOps & LLMOps: Strong experience with MLOps workflows (CI/CD, monitoring, retraining pipelines) and familiarity with modern LLMOps frameworks
Strong experience with Realtime APIs, open API, Rags, Lang chain, Caching, LLM Finetuning, prompt, Evals, MCP, graphRags
Cloud & Infrastructure: Skilled in building and operating infrastructure using Azure, AWS, or Google Cloud, and deploying containerized models with Docker, Kubernetes, or similar tools
Engineering Excellence: Passion for building high-quality, reliable, and maintainable software with strong coding and debugging practices
Collaboration & Communication: Excellent verbal, written, and cross-team communication skills
a collaborative team player across time zones and diverse stakeholder groups
Experience with customers success, zero trust security and compliance
Experience with proficient coding, debugging, and problem-solving skills