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Tier-1 brand, mid-level generalist AI role, metro location, and broad cloud/AI skills increase applicant competition.
Core ML and cloud engineering skills are transferable across industries despite pharmaceutical preference.
Explicit 2–5 year requirement plus mandatory ML, cloud, and programming skills makes filters highly strict.
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Lead design, development, and implementation of AI and generative AI solutions for Safety, Regulatory, and Clinical business problems.
Ensure product technical architecture and software development align with technology roadmap and engineering standards.
Collaborate with cross-functional teams to integrate cloud computing and automation technologies and provide technical guidance to junior engineers.
2-5 years of engineering experience focusing on AI, generative AI, cloud computing, automation, and software development.
Bachelor's degree or higher in Computer Science or related fields (Engineering, Math, Physics, IT).
Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
Proficiency in programming languages such as Python, Java, or C++ and familiarity with automation tools like Kubernetes, Docker, CI/CD pipelines.
Experienced in applying AI and cloud technologies in regulated or clinical environments is preferred but not mandatory.
Operates at the intersection of technical leadership and hands-on engineering with ability to manage multiple projects.
Skilled in mentoring engineers and collaborating with business partners and data scientists to translate requirements into scalable technical solutions.