Associate Director - Data Sciences and AI/ML Solutions Architecture

Associate Director Data Sciences

Career Category

Information Systems

Job Description

The Associate Director Data Sciences is the primary technology authority for all AI/ML and GenAI initiatives in Amgen's Innovation Lab. You will define, guide, and govern solution architectures, partnering with the Amgen Product Manager and functional leads to translate business goals into scalable, secure, and compliant technical solutions. This is a hands-on leadership role that balances architecture design, technical mentorship, and delivery governance across multiple PoCs.

Key Responsibilities

• Define end-to-end technical architectures for AI/ML, data, and digital applications.
• Collaborate with Amgen’s Program Manager and technical leads on solution design and delivery planning.
• Establish coding standards, DevOps / MLOps frameworks, and CI/CD pipelines for the lab.
• Provide technical oversight across PoDs, ensuring scalability, security, and compliance.
• Evaluate and recommend tools, libraries, and frameworks for AI/ML, GenAI, and data engineering.
• Support architecture reviews, design approvals, and release governance.
• Mentor engineers and ensure alignment with Amgen’s enterprise architecture principles.
• Coordinate with Amgen Cloud and IT teams on infrastructure provisioning and integrations.

Required Qualifications

• Phd or Masters and 12–18 years of experience in solution architecture or technical leadership roles.
• Proven expertise across AI/ML, Data Engineering, and Full Stack Development.
• Deep knowledge of cloud platforms (AWS preferred) and containerized deployments.
• Familiarity with Python, Java, React JS, and modern microservices architectures.
• Hands-on experience with MLOps tools (SageMaker, MLflow, Databricks, Kubeflow).
• Strong background in data governance, security, and compliance automation.
• Excellent communication and stakeholder management skills.

Preferred Skills

• Experience architecting GenAI applications (LLMs, LangChain, RAG, OpenAI APIs).
• Prior exposure to pharma / life sciences AI environments is preferred.
• Certifications in AWS Solution Architecture, AI/ML Specialization, or TOGAF.
• Strong understanding of Responsible AI and model validation principles.
  

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Experience Level

Mid Level