Senior Software Engineer - Azure Storage Observability at Microsoft

, , United States -

Full Time

Start Date

Immediate

Expiry Date

14 Apr, 26

Salary

234700.0

Posted On

14 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

C++, Rust, Distributed Systems, Observability, Telemetry, Machine Learning, Artificial Intelligence, API Development, Data Analysis, Statistical Methods, Site Reliability Engineering, Performance Optimization, Security, Testing, Continuous Integration, Continuous Deployment

Industry

Software Development

Description

Overview Microsoft Azure Storage is a highly distributed, massively scalable, and ubiquitously accessible cloud storage platform. Azure storage already runs at Exascale (storing Exabytes of data) and we will scale our designs over the next decade to support Zettascale (storing Zettabytes of data). As a Senior Software Engineer - Azure Storage Observability you will design, implement, optimize, and maintain core components of the Azure Storage stack that operate at massive global scale. You will work across the full storage lifecycle—including architecture, implementation, testing, deployment, and operational support—to deliver highly reliable and performant backend systems that power Azure’s storage platform. A key part of this role is driving observability across the storage fleet. You will build and enhance telemetry, monitoring, alerting, diagnostics, and analytics capabilities that ensure deep visibility into system behavior, performance, reliability, and efficiency. Your work will help engineers detect anomalies earlier, understand system health more accurately, and respond to issues with faster root‑cause identification. You will also partner with data scientists and engineering peers to design and integrate AI/ML-driven intelligence into the storage platform. This includes using machine learning techniques and statistical methods to detect patterns, optimize operations, predict failures, and automatically tune systems. You’ll experiment with data, validate models, and ship production-ready intelligent features that directly improve storage efficiency and reliability for Azure’s global customer base. 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. If you share our values, love working with data, and want to solve some of the most exciting challenges on a massive product like Azure storage, this could be the perfect position for you. Responsibilities Architect, implement, and maintain reliable, scalable, and secure distributed systems and Application Programming Interfaces (API); write high‑quality, extensible, and diagnosable code with strong attention to performance, resiliency, and maintainability. Drive end‑to‑end observability and operational excellence by instrumenting services with robust telemetry, logging, tracing, alerting, and dashboards; improve Mean Time to Detect (MTTD)/Mean Time to Repair (MTTR) through proactive monitoring, health checks, and data‑driven Site Reliability Engineering (SRE) practices that raise availability and efficiency at global scale. Act as Directly Responsible Individual (DRI) for critical components and mentor engineers. Hold on‑call ownership to triage and resolve incidents; lead root‑cause analysis and postmortems; coach teammates on production readiness, safe deploys, rollback strategies, and sustainable operations. Collaborate with Program Manager (PM), User Experience (UX), and partner teams to clarify user and business needs; decompose work into project/release plans and executable items; incorporate feedback from customers, telemetry, and support channels into iterative improvements. Integrate Artificial Intelligence (AI)/Machine Learning (ML) to enhance storage intelligence and efficiency by partnering with data scientists to design and productionize Machine Learning (ML) capabilities (e.g., anomaly detection, capacity forecasting, auto‑tuning); build scalable pipelines; define online/offline evaluation, A/B Testing (A/B) experiments, and telemetry‑based model iteration. Apply modern engineering best practices across the lifecycle. Uphold high bars for code reviews, testing (unit/integration/end‑to‑end (e2e)), security, reliability, and performance; reuse and refactor shared components; enforce Continuous Integration/Continuous Deployment (CI/CD) quality gates and incremental rollouts to reduce risk. Elevate technical strategy through data‑driven insights. Use metrics, experiments, and statistical analyses to inform design trade‑offs and platform investments; advocate Artificial Intelligence (AI)/Machine Learning (ML) and observability standards; share learnings and patterns that drive consistency in monitoring and operations across teams. Qualifications Required Qualifications: 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++, Rust OR equivalent experience. 4+ years experience with system design, distributed systems, or service-level engineering skills AI/ML integration. Other Requirements: 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 Qualifications: Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, Rust OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C++, Rust OR equivalent experience. #azurecorejobs Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

Design, implement, optimize, and maintain core components of the Azure Storage stack, focusing on observability and operational excellence. Collaborate with data scientists to integrate AI/ML capabilities for enhanced storage intelligence and efficiency.