Senior / Principal Software Engineers (AI), Commerce Platforms

Microsoft • Redmond, WA

1d • $119,800 - $304,200 • Hybrid

About The Position

Microsoft Commerce Platforms powers the services and data foundations behind offers, pricing, and transactions across first-party and third-party commerce experiences. The team is modernizing shared platforms and data architecture to make commerce capabilities more scalable, reliable, intelligent, and easier to extend. Microsoft is hiring for both Senior Software Engineer and Principal Software Engineer roles; the level will be determined based on experience, technical depth, scope of impact, architectural leadership, and ability to influence engineering direction across teams.

In this role, you will build and evolve distributed services, APIs, and large-scale data platforms that support critical commerce experiences. You will work across engineering, product, and data science teams to solve complex technical problems, modernize shared capabilities, and apply data and AI to improve commerce and engineering outcomes. The role is onsite three days a week in Microsoft’s Redmond, Washington offices.

Requirements

• Bachelor's degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
• Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Nice To Haves

• Experience designing and building scalable distributed or cloud-based systems, including backend services, APIs, and service-oriented architectures.
• Experience with cloud platforms such as Azure, AWS, or Google Cloud and building high-scale data pipelines or shared data models.
• Understanding of software architecture, system design, scalability, performance, reliability, security, and operational excellence.
• Experience with CI/CD, automated testing, observability, production monitoring, incident response, and operating services at scale.
• Ability to evaluate complex technical trade-offs, troubleshoot distributed systems, and translate ambiguous business or customer needs into effective technical solutions.
• Experience partnering across engineering, product, data science, and other cross-functional teams to deliver complex technical initiatives.
• Experience with data-intensive systems and technologies supporting large-scale ingestion, processing, analytics, or real-time decision-making.
• Experience applying machine learning or AI to production scenarios such as anomaly detection, forecasting, intelligent routing, automated insights, or LLM-based automation.
• Experience driving technical design, architecture, engineering standards, and modernization efforts, with the ability to influence technical decisions beyond an individual service or component.
• Communication and collaboration skills, including experience sharing technical knowledge, conducting design and code reviews, and mentoring other engineers.
• Experience with commerce domains such as offers, catalogs, pricing, payments, marketplaces, billing, or transactions.
• Experience with large-scale data technologies such as Spark, Kafka, Databricks, or similar platforms.
• Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Experience with experimentation, statistical modeling, feature engineering, model evaluation, or model lifecycle management.
• Experience with generative AI, LLMs, AI-assisted software development, or other practical applications of AI in production environments.
• Full-stack development experience with technologies such as React or TypeScript.

Responsibilities

• Design, build, and evolve scalable distributed services that support reliable commerce experiences across teams and products.
• Develop APIs and high-scale data pipelines supporting offer lifecycle management, ingestion, data modeling, analytics, and real-time decision-making.
• Shape architecture and modernization efforts that standardize shared capabilities, reduce fragmentation, and improve platform consistency.
• Build solutions designed for scalability, extensibility, performance, security, and operational reliability.
• Partner with engineering, product, and data science teams to define requirements and translate customer and business needs into well-scoped technical solutions.
• Apply data, machine learning, and AI to practical problems such as anomaly detection, forecasting, intelligent routing, automated insights, and engineering productivity.
• Explore and build extensible LLM-based capabilities where they can meaningfully improve engineering and commerce outcomes.
• Own service and model reliability through observability, testing, deployment, monitoring, incident response, and continuous improvement.
• Evaluate new approaches through experimentation, data analysis, feature engineering, model evaluation, and production validation as appropriate.
• Raise engineering standards through design and code reviews, technical mentorship, knowledge sharing, and hands-on delivery.

Benefits

• Certain roles may be eligible for benefits and other compensation; additional benefits and pay information is available through Microsoft’s corporate pay information page.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior