You will work in a group focusing on advancing Azure Content Understanding, a multimodal AI capability that enables organizations to transform unstructured data-such as text, documents, audio, images, and video-into structured, actionable insights.

As a Software Engineer on the team, you will work on building end-to-end multimodal AI systems that process and extract insights from diverse multi-modality data types. In this role, you will combine strong software engineering with applied ML expertise to design and ship production systems using techniques like context engineering, data generation and rigorous evaluation/metrics to continuously improve quality.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we are dedicated to this mission across every aspect of the company. Our culture us centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positivelyimpactour culture every day.

Responsibilities

• Design, build, andoperateproduction-grade generative AI and multimodal systems, with end-to-end ownership from concept through deployment and service operations.

• Contribute to technical design for core GenAI capabilities (e.g., retrieval-augmented generation, context and memory, orchestration) and make data-driven tradeoffs across quality, latency, cost, and safety.

• Define and improve model and system quality using evaluation frameworks, experiment design, and production telemetry; ensure robust testing and regression coverage.

• Collaborate with security, privacy, and compliance partners to build solutions that meet enterprise requirements and align with Responsible AI standards and practices.

• Partner with product and customers to understand scenarios, translate requirements into well-designed APIs and developer experiences, and drive adoption through documentation and samples.

• 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, Python, or equivalent experience.

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 OR Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

• Advanced degree in Computer Science, Machine Learning, or related field.

• Experience with prompt engineering, retrieval-augmented generation (RAG), and memory/agent frameworks.

• Experience building and shipping generative AI systems (including multimodal scenarios).

• Familiarity with compliance and security standards in enterprise AI solutions.

• Track recordof delivering enterprise-facing AI productsatscale.

• Experience building and operating ML/AI systems in cloud environments; familiarity withMLOpspractices (Azure a plus).

CoreAI

Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 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 $133,800 - $219,200 per year.