AI Data Engineer

Summary

This role is part of a team that works in a people-centric, culture-first environment alongside designers, product partners, engineers, strategists, and writers to design and build modern experiences. The focus is on building innovative technology and shipping delightful experiences, especially where AI changes what products can do. The team is passionate about exploring the future of intelligent products and is currently focused on Copilot in the M365 Enterprise world.

Responsibilities

• Design, build, and evolve synthetic data-generation systems, assessing existing approaches and technical trade-offs while developing scalable, maintainable workflows.
• Build and operate scalable pipelines and orchestration, applying concurrency, asynchronous execution, and resilient failure handling where appropriate.
• Design and evolve data models, storage approaches, and retrieval patterns to support large data volumes and efficient access.
• Develop and evolve validation frameworks and systems that define quality criteria and automate checks.
• Apply cloud engineering practices to build, deploy, monitor, and support dependable systems, balancing scalability, operational simplicity, and cost.
• Evaluate technical trade-offs, communicate progress and risks, and collaborate on practical solutions.

Qualifications

• 5 years of software or data engineering experience, or equivalent significant experience building systems with coding in languages & frameworks including, but not limited to, Python, Spring Boot, .NET.
• Strong backend programming and systems engineering skills.
• Deep experience designing, building, and operating data generation, ETL, and distributed data-processing workflows.
• Strong working understanding of LLMs, including their capabilities, limitations, and common failure modes.
• Working knowledge of orchestration, concurrency, asynchronous execution, and streaming or event-driven architectures.
• Strong knowledge of large-scale data storage, modeling, and retrieval.
• Practical cloud engineering experience and the ability to work independently in an existing codebase.

Skills

• Experience with Python.
• Experience integrating LLMs through AI platforms, frameworks, and APIs.
• Experience designing and running evaluations of LLM output.
• Experience with distributed processing, streaming or event-driven systems, and workflow orchestration tools.
• Experience with observability, performance tuning, and deployment automation.
• Familiarity with relational or NoSQL databases, cloud object storage, and data lake architectures.
• Strong technical communication, documentation, collaboration, adaptability, and problem-solving skills.