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Popular full-stack AI role, metro location, and broad technical requirements increase applicant competition significantly.
Core full-stack and AI skills are broadly transferable across industries despite pharma-preferred compliance experience.
Explicit 3–13 years requirement plus varied technical must-haves creates moderate rigor in candidate filtering.
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Own end-to-end development, productionization, and deployment of complex software products integrating front-end and back-end workflows.
Collaborate cross-functionally with Product Owners, Data Scientists, UI/UX Developers, Scrum Masters, and business stakeholders to build scalable AI-powered production solutions.
Implement and uphold engineering best practices including QA, risk management, CI/CD, MLOps, and DevOps throughout the software lifecycle.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
3 to 13 years of software development and solution architecture experience.
Proficient in Python, JavaScript, Oracle, RDBMS, .Net, or Java; experience with AWS, Azure, or GCP cloud platforms.
Familiar with Agile development, DevOps practices, and engineering best practices such as code refactoring and design patterns.
Experienced full-stack engineer comfortable working in agile, cross-functional teams delivering AI-enabled enterprise software at scale.
Knowledgeable in deploying AI/ML solutions and familiar with Gen AI technologies or Data Engineering tools is a plus.
Capable of translating complex business needs into practical technical solutions with strong ownership over software quality and operationalization.