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Tier-1 employer, mid-level generalist role, metro location, and desirable AI/cloud skillset increases applicant competition.
ML and cloud skills transfer well across industries though finance domain experience is advantageous.
Explicit 3+ years, mandatory cloud/AI certifications and hands-on LLM/cloud stack.
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Design, develop and operate large-scale, sophisticated LLM-driven and AI/ML-enabled applications integrated with cloud technologies.
Collaborate cross-functionally with Data Science, Cybersecurity, and DevOps teams to deliver secure, scalable, and compliant ML products and cloud-native architectures.
Apply enterprise-authorized AI-assisted software development tools to improve code quality, delivery speed, and software automation within a regulated environment.
3+ years of applied software engineering experience with formal training or certification.
Advanced Python programming skills and proven experience building scalable ML-driven products.
Hands-on experience and certifications in Azure and/or AWS, including Kubernetes and Airflow expertise.
Experience working in highly regulated environments and proficiency with Infrastructure as Code (Terraform) and microservices performance optimization.
Experienced in integrating AI/ML solutions within large-scale cloud-native architectures, focusing on scalability and security.
Skilled in using AI-assisted software development tools critically, ensuring secure, high-quality code in compliance-driven contexts.
Familiar with responsible AI engineering practices, including handling data sensitivity and guiding safe AI tool usage within teams.