Applied Engineer II

As an Applied Engineer II you will play a pivotal role in contributing to the development and integration of cutting-edge AI technologies into Microsoft products and services, ensuring they are inclusive, ethical, and impactful.

You will collaborate across product, research, and engineering teams to bring innovative solutions to life, applying your experience in machine learning, data science, and AI to solve complex problems. Your work will directly influence product direction and customer experiences.

We are in an era of unprecedented innovation and openness. As Microsoft continues to lead in AI, we are seeking individuals to impact some of the most exciting initiatives in the field. Our vision is to build a truly open architecture platform that enables users to summon tailored AI agents to drive real-world outcomes.

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 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.
• 1+ year of experience with Generative AI OR Large Language Models/Machine Learning algorithms.

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:

• Experience with Machine Learning Operations Workflows, including Continuous Integration/Continuous Delivery (CI/CD), monitoring, and retraining pipelines.
• Familiarity with modern Large Language Model Operations frameworks (e.g., LangChain, PromptFlow).
• 1+ year of experience developing and deploying live production systems.
• Experience across the product lifecycle from ideation to shipping.

Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: US corporate pay information | Microsoft Careers

Microsoft will accept applications for the role until October 23, 2025.

• Research and implement state-of-the-art technologies using foundation models, prompt engineering, Retrieval Augmented Generation (RAG), graphs, multi-agent architectures, as well as classical machine learning techniques.
• Fine-tune foundation models using domain-specific datasets
• Evaluate model behavior on relevance, bias, hallucination, and response quality via offline evaluations, shadow experiments, and online experiments
• Build rapid AI solution prototypes, contribute to production deployment of these solutions, debug production code, and support Machine Learning and AI operations
• Utilize demonstrated experience in AI subfields (e.g., deep learning, Generative AI, Natural Language Processing (NLP), muti-modal models) to translate cutting-edge research into practical, real-world solutions that drive product innovation and business impact.
• Apply an understanding of fairness and bias in AI by proactively identifying and mitigating ethical and security risks—including XPIA (Cross-Prompt Injection Attack) unfairness, bias, and privacy concerns—to ensure equitable and responsible outcomes.
• Embody our culture and values.