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Life Science Solutions Provider

Associate Director AI (Princeton)

Life Science Solutions Provider, Princeton, New Jersey, United States, 08543

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Associate Director/AI, Life Science Solutions Provider, Princeton, 220k plus bonus, Hybrid Model

US CITIZEN OR GREEN CARD ONLY

NO CORP TO CORP

2 DAYS A WEEK ON SITE

MUST HAVE FIVE YEARS AI/DATA ANALYTICS

MUST HAVE PHARMA EXPERIENCE

MUST HAVE STRONG API/CLOUD SKILLSET

The ideal candidate will be responsible for defining and executing the digital technology roadmap, driving innovation, and leading high-performing engineering teams to deliver scalable, secure, and high-quality digital solutions. Responsibilities: Lead and manage the end-to-end digital engineering function, including software development, cloud architecture, DevOps, and emerging technologies. Design and implement strategic digital initiatives aligned with business goals and technology vision. Establish and enforce engineering best practices, coding standards, and governance frameworks. Collaborate with product, data, and business teams to translate business requirements into scalable technical solutions. Drive innovation in digital platforms using AI/ML, cloud-native solutions, microservices, and modern software architectures. Lead cross-functional teams and mentor senior engineering managers and technical leads. Ensure high-quality delivery through robust CI/CD pipelines, automated testing, and performance monitoring. Manage budgeting, resource planning, and vendor relationships for digital engineering projects. Stay ahead of industry trends and emerging technologies to ensure the company maintains a competitive edge.

Bachelors or Masters degree in Computer Science, Engineering, or related field. 15+ years in software engineering, digital technology, or related domains, with at least 57 years in senior leadership roles. Proven experience in leading large-scale digital transformation programs and engineering teams. Strong expertise in cloud platforms (AWS, Azure, GCP), microservices architecture, AI/ML integration, API-first development, and DevOps practices