[Hiring] AI Data Engineer @Business Needs

Role Description

This role works in a people-centric, culture-first environment alongside designers, product partners, engineers, strategists, and writers to design and build modern experiences that make intelligent systems feel clear, trustworthy, and human.

The team is forward-looking and passionate about building innovative technology and shipping delightful experiences—especially where AI changes what products can do. We invest in rapid prototyping, model tuning and evaluation, data experiments, and AI-related explorations to help explore the future of intelligent Microsoft products.

The team brings diverse backgrounds in multiple disciplines, from engineering, design, or research to behavioral sciences or medicine; we come in all shapes and sizes. We love pushing boundaries and helping evolve Microsoft's products. Our current focus is on Copilot in the M365 Enterprise world.

Team is seeking a hands-on senior backend engineer with deep expertise in data generation and processing, scalable pipelines, large-scale storage, and quantitative analysis. The ideal candidate combines strong software engineering fundamentals with practical experience building and maintaining reliable, cloud-based backend systems.

The candidate will take ownership of technical work from assessment and design through implementation and ongoing support. This role requires sound engineering judgment, comfort working in existing codebases, and the ability to translate evolving requirements into maintainable solutions while collaborating closely with engineering and cross-functional partners.

You're a self-driven backend engineer who cares about building reliable, scalable foundations for thoughtful product experiences. You can turn evolving ideas into maintainable services and data workflows, learn new tools quickly, and are comfortable exploring the unknown. You value strong engineering practices and know how to collaborate across engineering, design, and product.

You contribute openly, prototype or experiment to learn, share feedback generously, and help raise the quality of the team's work. You are curious, adaptable, and motivated to build systems that make a real impact.

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, including designing maintainable services, modular components, APIs, and automated tests.
• Deep experience designing, building, and operating data generation, ETL, and distributed data-processing workflows, including creating, scaling, and maintaining cloud-based pipelines.
• Strong working understanding of LLMs, including their capabilities, limitations, common failure modes, and the role of data quality, prompting, evaluation, and model behavior in AI-powered systems.
• Working knowledge of orchestration, concurrency, asynchronous execution, streaming or event-driven architectures, and recovery from failures.
• Strong knowledge of large-scale data storage, modeling, and retrieval, including partitioning, indexing, access patterns, and trade-offs among storage approaches.
• Strong quantitative analytical and troubleshooting skills, with the ability to validate data and system behavior, interpret performance measurements, and make evidence-based engineering decisions.
• Practical cloud engineering experience and the ability to work independently in an existing codebase.
• Clear technical communication, effective collaboration, and a disciplined approach to documentation and operational reliability.

Requirements

• Experience with Python.
• Experience integrating LLMs through AI platforms, frameworks, and APIs, including building or evaluating production-oriented AI workflows.
• Experience designing and running evaluations of LLM output, such as defining quality criteria, building automated checks.
• Experience with distributed processing, streaming or event-driven systems, and workflow orchestration tools—such as Apache Spark, Kafka, or equivalent technologies.
• Familiarity with relational or NoSQL databases, cloud object storage, or data lake architectures.
• Ability to work independently within an existing codebase and translate evolving requirements into maintainable solutions.
• Strong technical communication, documentation, collaboration, adaptability, and problem-solving skills.
• Experience creating automated tests and data-quality validation frameworks.
• Portfolio/work samples are optional.

Benefits

• Opportunity to work at the intersection of AI, synthetic data, backend engineering, and UX/product experimentation.
• Building infrastructure that directly enables Microsoft's exploration of future M365 Copilot experiences.
• The work has broader importance for model-forward prototyping ambitions, rather than being routine pipeline maintenance.