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Tier-1 brand, generic software title, mid-level experience, metro location, and broad ML/cloud requirements.
Requires ML/GenAI and regulated-environment experience, moderately limiting cross-industry portability.
Multiple mandatory filters: 3+ years, ML/GenAI experience, cloud/Terraform, and regulated-environment expertise.
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Collaborate across technology teams including Data Science, Cybersecurity, and DevOps to design, deliver, and deploy scalable, secure machine learning and AI-driven software solutions.
Develop, review, and maintain high-quality, secure production code using advanced Python programming and cloud-native architectures on Azure and AWS.
Lead integration and adoption of enterprise-authorized AI-assisted development tools to improve code quality, delivery speed, and automation within software development lifecycle.
3+ years of applied software engineering experience with formal training or certification in software engineering concepts.
Advanced Python programming skills with proven experience in building and operating scalable ML-driven products.
Hands-on experience with Azure and AWS cloud platforms and large-scale cloud-native architecture design and delivery.
Experience working in highly regulated environments; proficient in Software Development Life Cycle, Terraform, and Infrastructure as Code (IaaC).
Experienced in cross-functional agile teams collaborating with Data Science, Cybersecurity, and DevOps to deliver integrated AI/ML solutions.
Skilled in leveraging AI-assisted software engineering tools critically to enhance development outcomes while ensuring secure and responsible AI usage.
Capable of performance tuning microservices and optimizing real-time applications in regulated enterprise environments.