Back
Strong employer brand and metro location increase applicants, but AI specialization limits generalist competition.
AI architecture skills transfer across industries, but regulated-pharma context raises domain specificity.
Mandatory 6+ years, production ML experience, and specific LLM/MLOps skills create rigid filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Architect end-to-end AI solutions for commercial AI initiatives impacting healthcare professional engagement in international markets.
Translate ambiguous business problems into actionable AI solutions and lead cross-functional teams to deliver production-grade AI systems.
Design data flows, model approaches, agent orchestration, human-in-the-loop interactions, and ensure compliance in regulated environments while maintaining quality and observability standards.
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related technical field.
6+ years of relevant industry experience including at least 2 years designing or building AI/ML solutions in production.
Strong Python proficiency and hands-on experience with cloud platforms, preferably AWS services such as Bedrock, SageMaker, S3, and Lambda.
Work Experience Required: 6+ years; Notice period: Not explicitly mentioned in the JD.
Experienced in architecting full-stack AI systems with ability to discern tractable AI solutions vs hype or non-AI approaches.
Familiar with large language models, agentic AI frameworks, MLOps, and regulated industry contexts such as pharma or healthcare.
Able to influence without direct authority and produce concise, senior leader-level technical and business documentation.