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.

We innovate quickly and collaborate closely with our partners and customers in a very agile environment. If the opportunity to collaborate with a diverse Research and Engineering team, on shipping reliable, production-grade AI systems using cutting-edge AI first technologies excite you, we would love to talk to you!

In your role you will advance Microsoft’s mission 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.

As a Research Engineer with blend of Software Engineering, Applied AI focus, Machine Learning Engineering, you will design and implement AI systems and solutions that power Dynamics 365 Contact Center services used globally. You’ll collaborate with cross-functional teams to evaluate and deliver high-impact AI systems and features aligned with enterprise standards and cloud-scale requirements. Your responsibilities include:

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.

Required Qualifications:

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.

Other Requirements:

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.

Preferred Qualifications:

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 . 2+ years of professional experience working with generative artificial intelligence, large language models, or agent-based systems.

OR 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. 2+ years of professional experience working with generative artificial intelligence, large language models, or agent-based systems.

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

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.