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As a Senior AI Engineer in the Office AI team, you will help lead the evolution of Office productivity through AI-driven experiences and services across key applications. The team builds the core platforms and experiences that bring large language models (LLMs) and real-time intelligence into Office applications, combining the power of LLMs with enterprise data and native integration to streamline content creation, navigation and comprehension. We are looking for a creative Senior AI Engineer who will collaborate with software engineers, researchers, and product managers to express product needs as well-defined machine learning problems, push the state of the art in LLMs and bring prototypes all the way to planet scale production. Help drive the culture shift to AI first development and mentor junior engineers on the team. You’ll build the engineering that makes AI work in production: you will build APIs, platforms and services around AI features; design data pipelines and feedback loops; deploy and finetune state of the art deep learning models; orchestrate prompts and tools; and monitor AI specific signals—such as drift, hallucinations, safety and cost—alongside traditional service reliability metrics. Join us to empower people through AI, bringing cutting edge deep learning into everyday work at scale.
Job Responsibility:
Leadership and cross-functional collaboration. Partner with product management and engineering teams to define vision and roadmap, co-own scenario goals, and translate complex product requirements into scientific plans and production-ready AI solutions. Lead technical design reviews and ensure alignment with quality, latency, and cost objectives
Generative AI and advanced technologies. Apply knowledge of generative AI, large language models, and modern frameworks to develop intelligent features and automation within the service
Architecture and cloud integration. Design and implement scalable, reliable, and secure AI services on Azure, optimizing performance, cost and compliance
Technical innovation and strategy. Identify and evaluate emerging AI technologies, frameworks and methodologies. Pioneer new approaches to retrieval-augmented generation, prompt engineering and continuous learning to deliver adaptive and resilient AI systems
Mentoring and inclusive culture. Provide mentorship, technical guidance, and peer coaching to other engineers, fostering a culture of innovation, continuous learning, and inclusion. Encourage best practices in code quality, security and responsible AI while elevating the skills of fellow team members
Requirements:
Bachelor'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 equivalent experience
AI and machine learning mastery, Hands-on experience with state-of-the-art generative AI and ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and deep understanding of large language models, embeddings, prompt engineering and model fine-tuning
Distributed systems and cloud scale, Proven ability to design, implement and operate scalable, fault-tolerant microservices and distributed storage on cloud platforms such as Azure
experience building APIs and services, designing data pipelines and feedback loops, and implementing secure, compliant solutions
Technical leadership, demonstrated experience leading complex AI/ML initiatives from concept to production, mentoring engineers, and driving technical decision-making while working with cross-functional teams
Security and compliance, ability to meet Microsoft’s and customers’ security and background requirements and to ensure that AI solutions adhere to responsible AI and data privacy standards
7+ years of technical leadership with a track record of delivering mission-critical AI solutions at global scale, including model deployment, evaluation and lifecycle management
Experience with retrieval-augmented generation, multimodal architectures, prompt orchestration, model alignment and safety evaluation, and emerging AI methodologies
Hands-on experience with Azure Machine Learning, MLOps pipelines, and large-scale data systems (e.g., Cosmos DB, Spark, Data Lake) and establishing robust telemetry and evaluation frameworks
Demonstrated passion for mentoring, fostering an inclusive team culture, and collaborating closely with product, research and design partners to drive strategy and deliver user value