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Niche GenAI/cloud focus but metro location and known global employer increase applicant density moderately.
Core GenAI and cloud skills transfer across industries, though pharmaceutical governance increases domain specificity.
Explicit 6+ years, specific cloud/AWS stack and regulated pharmaceutical requirements make filtering stringent.
Lead design and implementation of Generative AI applications including prompt engineering, fine-tuning, RAG, and LLM workflow orchestration across business domains.
Own technical roadmap, architecture decisions, and delivery of enterprise-wide GenAI projects integrating cloud-native AI services and open-source models.
Mentor software engineers and AI practitioners; develop reusable components, APIs, and internal tools to ensure scalable, secure, and compliant cloud-native AI solutions.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
Minimum 6 years of development experience with a focus on cloud computing.
Strong knowledge of AWS, Azure, or Google Cloud platforms including core services like compute, storage, networking, and security.
Proficiency in programming languages such as Python, Java, or Node.js; experience with AWS services like EC2, S3, Lambda, and CloudFormation.
Experienced in leading cross-functional teams delivering cloud-based AI/ML applications, especially generative AI and LLM integrations.
Demonstrates ownership of technical architecture and roadmap for complex cloud solutions, balancing innovation with governance, security, and compliance.
Skilled at collaborating with data scientists, MLOps, and platform engineers to operationalize machine learning workflows and ensure production readiness.