About the Role
The Associate Director Data Sciences serves as the primary technology authority for all AI/ML and GenAI initiatives within Amgen's Innovation Lab. This role involves defining, guiding, and governing solution architectures, collaborating with the Amgen Product Manager and functional leads to translate business goals into scalable, secure, and compliant technical solutions. It is a hands-on leadership position that balances architecture design, technical mentorship, and delivery governance across multiple Proofs of Concept (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 Master's degree 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.