Software Engineer II - MBO

As a Software Engineer II, you will apply computer science principles to design, develop, and optimize software solutions for a set of product features and services. Working with minimal supervision, you will partner with product managers, technical leads, and fellow engineers to understand customer and business requirements and translate them into secure, reliable, scalable, and maintainable solutions.

You will use artificial intelligence (AI) tools and practices across the software development lifecycle in a disciplined manner, taking responsibility for the content of your AI-generated changes to artifacts and applying appropriate tooling and processes. You will apply coding patterns and recommended practices to build extensible, maintainable code; use logging and telemetry to investigate issues and improve reliability, availability, and performance; and uphold Microsoft standards of security, privacy, safety, and accessibility while collaborating with and learning from more experienced engineers.

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.

As a Software Engineer II, you will contribute across the engineering lifecycle for a set of product features and services - designing, coding, testing, deploying, and operating solutions that are secure, reliable, accessible, and maintainable. You will work with minimal supervision within your feature area, begin to own design decisions under technical leadership, and use AI tools across the development lifecycle in a disciplined manner.

• AI-native development: Use AI tools across the full software development lifecycle in a disciplined manner. Take responsibility for the content of your AI-generated changes to artifacts, reviewing all changes and applying appropriate tooling and processes with minimal guidance, and apply Responsible AI practices.
• Coding: Create and implement extensible, maintainable code for a product, service, or feature with minimal supervision, reusing code where applicable. Apply coding patterns and recommended practices, including GenAI-assisted development. Escalate blockers and unknowns and communicate how they impact timelines.
• Code reviews: Review product features and test code to ensure it meets team standards, has correct test coverage, and is appropriate for the feature. Bring insight to code reviews to improve code quality and help develop other engineers’ skills, reviewing for coding patterns, security risks, compliance issues, and recommended practices.
• Design and architecture: Provide feedback on architecture proposals under technical leadership, test and explore design options while outlining strengths and weaknesses and begin to own or collaborate on the architecture of solutions. Help ensure designs meet performance, scalability, resiliency, cost (COGS), security, and privacy requirements, and contribute to design documents that support user stories.
• Testing and quality: Create a clear test strategy that ensures solution quality and prevents regression with minimal supervision. Add tests to cover gaps, fix or remove broken tests, build testable code, and leverage AI tools for test automation, including security testing to validate security invariants.
• Customer requirements: Work with internal stakeholders (e.g., product managers, security/privacy subject matter experts, technical leads) to understand customer and user requirements for a set of features. Incorporate customer insights and continuous feedback loops and advocate for the security and privacy needs of customers.
• Dependencies and coordination: Identify dependencies and incorporate them into design documents, understand downstream interactions between systems, and collaborate with other teams to reach common goals where dependencies and validation concerns overlap.
• Planning and implementation: Execute project plans, release plans, and work items; contribute to breaking larger work items into smaller ones with estimation; escalate issues that might cause delays; and ensure security, privacy, and compliance requirements are accounted for in planning with minimal guidance.
• Deployment and velocity: Support safe deployment to customers by following safe-change practices, contribute to deployment automation targeting zero-touch deployment, monitor dependency status to ensure only the latest secure versions ship, and help identify when rollback plans should be enacted.
• Experimentation: Conduct experiments using feature flags and flighting to determine the impact of changes, collaborating with internal partners (e.g., Data Science, product managers) to incorporate success and guard rail metrics.
• Engineering excellence: Apply secure design principles and “security as code,” build and share tools that improve engineering efficiency, reuse open-source or internal code responsibly, and stay current with developments that improve availability, reliability, efficiency, observability, and performance.
• Live site and reliability: Participate in an on-call rotation as a designated responsible individual (DRI), mitigating live-site issues using least-privilege access and escalating appropriately. Improve troubleshooting guides, telemetry, and tests to make on-call better, respond within SLA, and contribute to logging and instrumentation for monitoring system health, performance, and security.
• Security, privacy, and compliance: Apply security guidelines, contribute to deployment gates, scanners, and security monitoring, and follow the correct processes for privacy, safety, and accessibility. Maintain an up-to-date understanding of global and local regulations for the technologies you work on.
• Collaboration and communication: Communicate clearly and respectfully - verbally and in writing - to drive collaborative, mutually beneficial outcomes; work effectively across teams; and contribute to an inclusive culture and a growth mindset.

• Bachelor’s Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Preferred Qualifications

• Hands-on experience using artificial intelligence (AI) tools and practices across the software development lifecycle in a disciplined manner, taking responsibility for the content of AI-generated changes to artifacts and reviewing all changes.
• Experience applying computer science principles to design, develop, and optimize scalable algorithms, distributed systems, and business applications, including reference architecture and patterns for resilient system design.
• Experience in one or more technology domains (e.g., analytics, applications, web, mobile, big data, compute, containers, databases, developer tools, Internet of Things, microservices, or storage).
• Experience across the engineering and product lifecycle, including task estimation, design and code review, specification review, bug triage, code check-in, sign-off, test targeting, and performance standards.
• Experience with quality assurance processes, measurements, and standards, including test automation and security testing to validate security invariants.
• Experience validating solutions and driving improvement by identifying opportunities, and delivering informed, ready designs ahead of production with time for feedback and iteration.
• Experience building secure software and meeting regulatory and compliance requirements, including secure coding practices, threat modeling, and privacy considerations.
• Experience with logging, telemetry, monitoring, and live-site operations, including on-call/DRI rotations to maintain reliability and availability.
• Problem-solving and data analysis skills, applying systems thinking and a data-driven approach to extract actionable insights and make sound decisions in a fast-paced environment.
• Experience contributing to code reviews and coaching engineers, reviewing for coding patterns, security risks, and recommended practices to improve code quality and help develop others’ skills.
• Experience collaborating across teams on novel solutions, resolving conflict, and communicating clearly and respectfully - verbally and in writing - to achieve mutually beneficial outcomes.

Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 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 $133,800 - $219,200 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.