Senior Software Engineer - Data Platform, AI Infrastructure

Microsoft•Redmond, WA

About The Position

We are building a large-scale, productized data platform that powers critical insights and systems across Azure-based services for AI Infrastructure. This platform will process terabytes to petabytes of data daily and is designed for reliability, scalability, and long-term evolution. As a Senior Software Engineer - Data Platform, you will focus on building and operating the core infrastructure layer of the platform - covering orchestration, APIs, observability, and system reliability. You will work closely with data engineers and partner teams to ensure the platform is robust, standardized, and capable of supporting rapid growth. We are looking for engineers who execute well, own systems end-to-end, and bring structure to complex problems - not just ideas. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

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.
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.

Nice To Haves

Strong programming experience in Python
Experience building and operating large-scale distributed systems
Hands-on experience with:
Backend services or APIs (e.g., FastAPI, Flask, or similar)
Cloud-based infrastructure (Azure, AWS, or GCP)
Monitoring and observability systems (metrics, logging, alerting)
Experience designing systems with reliability, scalability, and operational clarity in mind
Proven ability to own and deliver production systems end-to-end
Ability to break down ambiguous problems, ask the right questions, and execute effectively
Experience with Azure technologies such as:
ADLS Gen2 (Blob Storage)
Synapse / Spark
Azure Data Explorer (ADX)
Experience with orchestration frameworks (e.g., Airflow)
Experience with infrastructure-as-code (Bicep, ARM, Terraform, or similar)
Familiarity with data platform concepts (data pipelines, schema evolution, data quality, etc.)
Experience working on systems handling terabyte to petabyte-scale data
Exposure to privacy, compliance, and secure data handling practices
#aiinfra

Responsibilities

Design, build, and operate core components of a distributed data platform, including:
Orchestration systems (e.g., Airflow or equivalent)
Backend services and APIs (Python/FastAPI or similar)
Monitoring, alerting, and reliability systems
Own the end-to-end lifecycle of platform components - from design through deployment, scaling, and maintenance
Ensure systems meet requirements for availability, performance, and data reliability at large scale
Define and enforce standardized patterns for infrastructure, deployment, and observability across the platform
Partner with data engineering teams to enable efficient, reliable data processing workflows
Diagnose and resolve complex issues in distributed systems, including performance bottlenecks and failure modes
Contribute to infrastructure-as-code and deployment systems to support reproducibility and operational excellence
Drive continuous improvements in system robustness, cost efficiency, and operational clarity