Principal Applied AI Engineer

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Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world.

The Purview AI Research team leads the charge in advancing artificial intelligence, conducting groundbreaking research across deep learning, NLP, LLMs, RL, and graph-based approaches. Our expertise lies in developing sophisticated agentic systems, including cutting-edge innovations that leverage RL fine-tuning of LLMs to create intelligent solutions capable of autonomous reasoning, adaptation, and action. Our mission is to stay ahead of emerging technological trends and seamlessly embed transformative AI capabilities into our product ecosystem. We aim to deliver solutions that not only address current challenges but also pave the way for the future of applied AI and data science. We are seeking a passionate Principal Applied AI Scientist/Engineer to join our team. The ideal candidate is deeply engaged with the latest AI advancements, committed to team success, and skilled in delivering high-quality, production-ready code. This role offers the opportunity to collaborate with world-class applied AI researchers to develop new methodologies, tools, and frameworks that demonstrate how AI-powered innovations can redefine Microsoft Security—ushering in a new era of securing and managing our customers’ digital estates.

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.

• Bachelor's Degree in Computer Science, Data Science or related technical field
• 5+ years technical engineering experience with coding in languages including C#, Java AND Python
• Should have 5+ years in Data Science experience
• 3+ years of experience with LLMs and open-source GenAI frameworks, such as LangChain, LlamaIndex, Haystack, or equivalents (e.g., Transformers, AutoGen, DSPy), including agent-based orchestration, prompt engineering, retrieval-augmented generation (RAG), and fine-tuning and evaluation.​
• Proficiency in writing production-quality software code in one or more modern programming languages (Python, C#)
• 3+ years experience developing software systems end-to-end, from design to implementation.
• 2+ years experience in shipping at least 2 large scale ML/AI-based services or applications on cloud platforms (Azure, AWS, GCP, etc.)

• Design, develop, and deploy end-to-end AI/ML systems, including data ingestion, model training, evaluation, and integration into production environments.
• Build and optimize applications leveraging LLMs and open-source GenAI frameworks such as LangChain, LlamaIndex, Haystack, Transformers, AutoGen, and DSPy.
• Implement advanced GenAI techniques including agent-based orchestration, prompt engineering, retrieval-augmented generation (RAG), and model fine-tuning.
• Write production-grade software in Python and C# or Java, ensuring maintainability, scalability, and performance.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Ship and maintain large-scale AI applications, with a focus on performance monitoring and continuous improvement.
• Conduct rigorous evaluation of AI models using appropriate metrics and benchmarks.
• Optimize models for latency, throughput, and accuracy in real-world scenarios.
• Work closely with data scientists, product managers, and other engineers to drive AI initiatives.
• Stay current with the latest advancements in GenAI, LLMs, and AI frameworks.
• Prototype and experiment with emerging technologies to assess feasibility and impact.