Software Engineering IC3
Technology, Data & Digital · Software & Web Development · Software Engineering · DevOps
In short
Commercial Engineering & AI (CEAI) is seeking a Software Engineering IC3 to design, build, and operate distributed services on Azure, integrating AI capabilities like NLP and semantic search. This hybrid role involves end-to-end feature ownership, driving performance, and contributing to a DevOps culture, with a focus on transforming Microsoft's commercial business with AI.
Responsibilities
- Design, build, and operate distributed services and microservices on Azure.
- Own features end-to-end: requirements, design, implementation, testing, deployment, and live-site support.
- Contribute to platform capabilities such as offer publishing, catalog, search, purchase, fulfillment, metering, and billing.
- Integrate AI capabilities such as natural language processing, semantic search, and intelligent agents.
- Drive performance, scalability, and cost-efficiency.
- Ensure robust data validation, schema enforcement, and compliance with privacy and security standards.
- Collaborate across disciplines to define technical requirements, review designs, and deliver high-quality software.
- Mentor other engineers and promote engineering best practices.
- Participate in an on-call rotation and resolve live-site incidents.
- Contribute to our DevOps culture: CI/CD pipelines, automated testing, telemetry, and safe deployment practices.
Requirements
- Bachelor's Degree in Computer Science or related technical field.
- 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.
- Proficiency in C#, Python, or JavaScript.
- Familiarity with cloud platforms like Azure or AWS.
- Experience designing and consuming REST APIs.
- Experience working with relational and/or NoSQL data stores.
- Fundamentals in data structures, algorithms, distributed systems, and debugging.
- Experience with AI development tools and frameworks (e.g., OpenAI APIs, transformers, semantic search).
- Understanding of CI/CD pipelines, GitHub workflows, and infrastructure-as-code.
- Problem-solving, communication, and collaboration skills.
- Demonstrated ability to lead design efforts and deliver production-grade solutions.
- Experience building or operating large-scale cloud services on Azure or another major cloud.
- Familiarity with commerce, billing, or marketplace/storefront systems.
- Experience with Kubernetes, event-driven architectures, or high-throughput data pipelines.
- Experience building LLM-powered applications RAG pipelines, prompt engineering, agent frameworks (Semantic Kernel, LangChain), or fine-tuning.
- Written communication: design docs, postmortems, customer-facing release notes.
- Contributions to live-site / SRE practices: monitoring, alerting, incident response.
Benefits
- The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 per year.
- For specific work locations in the San Francisco Bay area and New York City metropolitan area, the base pay range is USD $133,800 - $219,200 per year.
- Certain roles may be eligible for benefits and other compensation.
#Software Engineering#AI#Azure#Distributed Systems#Microservices#Cloud Computing#DevOps#SRE