About the job
As a Senior Software Engineer - Data Platform, AI Framework 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.
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
Qualifications
Minimum
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.
Preferred
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