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Tier-1 brand, generic Software Engineer title, metro location, and broad skill requirements increase competition.
Data-platform and cloud engineering skills are moderately transferable across industries but require domain tooling familiarity.
No explicit years or mandatory certifications and only preferred cloud/AI exposure, so filters are relatively low.
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Design, develop, deploy, and operate scalable cloud-based data and analytics solutions using Microsoft Cloud and AI technologies.
Integrate AI capabilities including Azure OpenAI, Cognitive Services, and ML models to enhance system intelligence and user productivity.
Own end-to-end solution lifecycle from design through implementation to operations, including monitoring and analytics-driven product decisions.
Bachelor's degree in Computer Science, Engineering, or related field OR equivalent practical experience.
Strong programming skills in one or more languages: Python, C#, Java, JavaScript, C++.
Business fluency in English (read, write, speak).
Work Experience Required: Not explicitly mentioned in the JD.
Experience or exposure to Microsoft Azure or other cloud platforms (GCP, AWS) and AI/ML tools/frameworks like Azure ML or OpenAI.
Ability to quickly ramp up on new technologies and deliver highly scalable, reliable cloud services and data solutions.
Comfortable working in fast-paced, cross-functional environments collaborating with product managers, stakeholders, and engineers to solve complex customer problems.