Mountain View, United States; Redmond, United States
Full job description
Microsoft Advertising's Forecasting team is seeking a Senior Software Engineer to lead the architecture, development, and evolution of forecasting and planning systems. The role involves building scalable distributed platforms for inventory management, forecasting, reach estimation, and capacity planning. Responsibilities include driving technical strategy, platform modernization, ensuring platform reliability and operational excellence, and collaborating with product, data science, and business teams. Candidates must have a Bachelor's degree in Computer Science or related field with 4+ years of engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, and meet Microsoft security screening requirements. Preferred qualifications include a Master's degree or 6+ years experience, expertise in large-scale distributed systems, cloud platforms (Azure, AWS, GCP), Spark, microservices, Kubernetes, CI/CD, DevOps, and AI application development. The position is full-time, on-site in Redmond, WA or Mountain View, CA. Salary ranges from $119,800 to $234,700 annually in most US locations, higher in Bay Area and NYC. Benefits and additional compensation may apply.
What you'll do
Similar jobs
More roles worth a look
Related opportunities based on specialty and working model so candidates can keep momentum.
Bellevue, United States; Boston, United States; Boulder, United States; Chicago, United States; Denver, United States; Los Angeles, United States; New York, US; San Francisco, United States; San Jose, United States; Seattle, United States; Ventura, United States•7 days ago
Mountain View, United States; Redmond, United States
Full-time
Lead architecture, design, implementation, testing and delivery of highly scalable distributed platforms for forecasting, inventory allocation, reach estimation, capacity planning
Drive technical strategy and engineering decisions across teams, influencing architecture direction, platform modernization, and long-term technology investments
Own platform health and operational excellence by establishing observability, monitoring, telemetry, alerting, resiliency, and automation practices
Drive engineering efficiency and platform evolution through service consolidation, platform simplification, automation, and adoption of modern engineering practices
Partner with Product teams, Data Science, and business stakeholders to translate complex business requirements into technical solutions
Serve as Designated Responsible Individual (DRI) for critical services, providing technical leadership during production operations, incident response, capacity planning, and service lifecycle management
Mentor engineers, develop future technical leaders, and foster a culture of technical excellence, accountability, continuous learning, and innovation
Requirements
Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements including Microsoft Cloud background check
Preferred: Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience OR Bachelor's Degree AND 8+ years experience OR equivalent experience
Experience building and operating large-scale distributed systems using cloud-native services and data-intensive platforms with proficiency in Spark
Experience leading complex cross-team engineering initiatives, system design, service architecture, reliability engineering, and production operations
Strong problem-solving and deep technical leadership skills
Solid understanding of architecture patterns, data structures, algorithms, time complexity
Experience designing, building, or supporting applications on Microsoft Azure, AWS, or Google Cloud Platform
Experience with modern software development stack including APIs, microservices, containers, Kubernetes, CI/CD, DevOps, cloud-native architectures, and AI application development
