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Tier-1 brand, generalist full-stack AI role and mid-level experience band increase applicant competition.
Core full-stack and MLOps skills are transferable, though pharmaceutical compliance preference increases specificity.
Explicit years range and multi-technology requirements make screening moderately strict.
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Design, develop, and deploy end-to-end, production-grade AI and software solutions in cloud environments.
Collaborate with cross-functional teams including Product Owners, Data Scientists, and UI/UX Developers to build scalable AI-accelerated products.
Implement engineering best practices such as CI/CD, MLOps, QA/Risk Management, and DevOps for AI-focused projects.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
3 to 13 years of software development and architecture experience.
Strong skills in Python, JavaScript, Oracle, RDBMS, .Net, or Java.
Experience with cloud platforms like AWS, Azure, or GCP.
Experienced in full-stack engineering with a focus on AI acceleration and integration of complex workflows.
Able to translate business needs into scalable, secure AI and software solutions in highly regulated environments.
Familiar with Agile methodologies and capable of contributing to engineering best practices and team knowledge sharing.