Senior AI Software Engineer

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Would you like to work on a product that transforms Microsoft AI technologies and a modern-work suite to help millions of users work better and faster together? Do you enjoy working with teams that leverage AI to create fast and useful solutions for end-users?

The future of work is being redefined with AI agents acting as digital co-workers. Microsoft is leading this transformation with M365, Copilot Studio, and Azure AI Foundry. As part of this team, you will help build Agent Cloud - an enterprise-grade solution that secures, governs, and manages AI agents with the same rigor and familiarity as human employees.

As a Senior AI Software Engineer, you will collaborate with a diverse multi-discipline, multi-site team delivering end-to-end solutions and end user experiences across the M365 ecosystem. These experiences are built upon a highly scalable Azure service architecture, featuring a React-based UI that will delight our customers.

You can learn more about our Dublin Engineering site here:
https://careers.microsoft.com/v2/global/en/locations/dublin.html

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.

Required Qualifications

• Bachelor's degree in computer science, or related technical discipline or relevant experience

• Extensive years of experience coding in one or more high level languages including, but not limited to Python, C#, Java

• Proven experience in developing and deploying large language models (LLMs): Demonstrated expertise in working with state-of-the-art LLMs, including their training, fine-tuning, and application in natural language processing tasks

• Practical experience in prompt engineering and evaluation, with the ability to design, refine, and test prompts to improve model accuracy, reliability, and usability

Preferred Qualifications

• Experience with Agent based architectures, frameworks and technologies (such as MCP, A2A protocol, Langchain, Azure AI Foundry)

• Proficiency in Python for data science workflows, leveraging libraries such as NumPy, Pandas, scikit-learn, Matplotlib, and Jupyter for data analysis, experimentation, and rapid prototyping

• Exposure to Deep Neural Network training and inference and experience in one or more deep learning frameworks (PyTorch, TensorFlow, etc.).

• Experienced in web application development frameworks, such as React

• Experience delivering a Cloud SaaS product on Azure, AWS or GCP

• Excellent communication and collaboration skills to work effectively across disciplines and partner teams

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.

#BICJOBS

This role demands a blend of artificial intelligence expertise with full-stack development skills to contribute to all phases of our product lifecycle, from conception to deployment. You'll work closely with our product and design teams to deliver on the vision.

• Implement, evaluate, and deploy AI-powered applications and services

• Develop and fine-tune large language models (LLMs) and other deep learning models

• Write clean, maintainable, and scalable code for model training, evaluation, and inference pipelines

• Optimize AI models for performance, latency, and cost efficiency in production environments

• Apply prompt engineering to enhance model outputs and performance

• Collaborate with cross-functional teams to integrate AI solutions into our products

• Stay current with emerging research, tools, and frameworks in AI/ML to drive innovation.

• Conduct experiments, analyze results, and communicate findings to both technical and non-technical stakeholders