Software Engineering, CoreAI
About The Position
As a Software Engineer on Microsoft’s CoreAI team, you will help advance Azure Content Understanding, a multimodal AI capability that turns unstructured data—including text, documents, audio, images, and video—into structured, actionable insights. You will build end-to-end multimodal AI systems that process diverse data and extract insights, combining software engineering with applied machine learning to design and ship production systems. The work uses techniques such as context engineering, data generation, and rigorous evaluation and metrics to continuously improve quality. The role includes ownership of generative AI and multimodal systems from concept through deployment and service operations. You will contribute to core GenAI capabilities, assess tradeoffs among quality, latency, cost, and safety, and work with product, customers, and security, privacy, and compliance partners. Microsoft describes its mission as empowering every person and organization to achieve more and emphasizes a growth mindset and an inclusive work environment.
Requirements
- Bachelor's degree in Computer Science or a related technical field, and 2+ years of technical engineering experience coding in languages including C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
Nice To Haves
- Master's degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in C, C++, C#, Java, JavaScript, or Python; or a bachelor's degree in a related field and 6+ years of such experience; or equivalent experience.
- Advanced degree in Computer Science, Machine Learning, or a related field.
- Experience with prompt engineering, retrieval-augmented generation (RAG), and memory or agent frameworks.
- Experience building and shipping generative AI systems, including multimodal scenarios.
- Familiarity with compliance and security standards for enterprise AI solutions.
- Track record of delivering enterprise-facing AI products at scale.
- Experience building and operating ML/AI systems in cloud environments; familiarity with MLOps practices, with Azure a plus.
Responsibilities
- Design, build, and operate production-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, such as retrieval-augmented generation, context and memory, and orchestration, making 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 teams and customers to understand scenarios, translate requirements into well-designed APIs and developer experiences, and drive adoption through documentation and samples.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
