Microsoft Senior Software Engineer - Bing Fundamentals Quality Metrics 

United States, Washington 

602644763

As ain the team, you need to build tools and services to help partners in Bing search and Microsoft AI for solving super critical Bing quality metrics and production debugging problems. You will work closely with peer developers and partner teams to quickly generate and iterate on designs. You will then implement cross platform, performant, high quality code, along the way collaborating with senior leaders to help define the overall architecture of the product. You can expect us to continually support your growth and always value your insights and contributions. Our goal is to not only build great products, but great engineers, who can deliver features to our customers.

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, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.
• 4+ years of experience in working in backend or full stack development
• 1+ year of experience on frontend development using HTML and React, Angular or similar UI framework
• 6+ months working on Applied AI solutions where AI was used to solve a user facing problem as a E2E (End to End) solution

Preferred Qualifications:

• In addition to required qualifications:
• 6+ months experience working with SLMs or LLMs and knowledge about fine tuning models for advanced scenarios.
• 1+ years Experience working with Kafka and Spark or similiar technologies.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

January 6, 2025.

• Coding - Leads by example within the team by producing extensible and maintainable. Optimizes, debugs, refactors, and reuses code to improve performance and maintainability, effectiveness, and return on investment (ROI). Applies metrics to drive the quality and stability of code, as well as appropriate coding patterns and best practices.
• Design - Independently creates a clear and articulated plan for testing and assuring quality of solutions, and defines success for outcomes of tests (e.g., unit tests). Identifies needs for a broad versus selected approach in testing mechanisms and makes informed decisions to implement the most effective tests
• Engineering Excellence - Maintains communication with key partners across the Microsoft ecosystem of engineers. Acts as a key contact for leadership to ensure alignment with partners' expectations. Considers partner teams across own organization and their end goals for products to drive and achieve desirable user experiences and fitting dynamic needs of partners/customers through product development.
• Implement - Creates and updates implementation framework as necessary, following industry standards. Drives implementation and deployment of the solution in the existing framework. Considers and accounts for the impact of build deployments on both users and other services. Assures that solutions are deployed safely.
• Understand User Requirements - Collaborates with appropriate stakeholders (e.g., project manager, technical lead) to determine user requirements for a scenario. Leverages a variety of feedback channels to incorporate insights into future designs or solution fixes. Ensures appropriate continuous feedback loops measuring customer value, usage patterns, and other actionable metrics of value are incorporated.
• Reliability and Supportability - Drives efforts to collect, classify, and analyze data on a range of metrics (e.g., health of the system, where bugs might be occurring). Drives the refinement of products through data analytics, and makes informed decisions in engineering products through data integration.
• Engineering Excellence - Remains current in skills by investing time and effort into staying abreast of current developments. Proactively seeks new knowledge and adapts to new trends, technical solutions, and patterns that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale.