Senior Manager, AI Engineering Clinical Development and Operations (CD&O)
Job Location:
New York City, NY - USA
Monthly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
POSITION SUMMARY
As a hands-on Senior Manager AI Engineering you will drive the technical execution data engineering and operationalization of production-grade AI systems within the Clinical Development & Operations (CD&O) organization.
In this individual-contributor engineering role you will be focused on dependable delivery. Taking direction and technical guidance from the AI Platform Lead you will work from defined business cases and requirements to deliver well-scoped AI/ML and LLM-based solutions to production. Your centre of gravity is data engineering AI capability build and operationalization - turning validated needs into reliable scalable and reproducible systems - with strong hands-on depth in a focused domain.
What youll do:
Analyze and Scope:
- Work from business cases and requirements defined and translate them into clear technical requirements for your assigned use cases.
- Partner with operational and line teams to clarify scoped needs edge cases and acceptance criteria; surface risks and dependencies.
Engineer Data and Pipelines:
- Build and maintain robust production-ready data pipelines within the established data and knowledge architecture within CD&O organisation.
- Ensure data quality lineage and reproducibility across the solutions you deliver.
Build and Deploy AI Solutions:
- Build test and deploy AI/ML and LLM-based solutions for assigned process-heavy workflows (e.g. protocol feasibility and site selection study start-up) contributing hands-on to the majority of the engineering work.
- Implement agentic workflow components tool integrations prompts evaluation routines and orchestration patterns according to approved enterprise architecture and AI engineering standards.
Testing Validation and Production Support:
- Develop and execute unit testing integration testing model/LLM evaluation support performance checks and production-readiness activities to ensure delivered AI capabilities are robust and maintainable.
Collaborate Across Disciplines:
- Partner closely with CD&O line teams scientists and Digital partners to ensure that AI efforts remain tightly aligned to real scientific needs and can be deployed in ways that are trusted scalable and adopted in day-to-day work.
- Champion best practices in AI engineering system lifecycle.
MINIMUM QUALIFICATIONS
PhD in Computer Science Artificial Intelligence Machine Learning Data Science Software Engineering or a related technical discipline and 1 years experience building practical reusable workflows or systems OR
Masters degree in Computer Science Artificial Intelligence Machine Learning Data Science Software Engineering or a related technical discipline and 5 years experience building practical reusable workflows or systems OR
Bachelors degree in Computer Science Artificial Intelligence Machine Learning Data Science Software Engineering or a related technical discipline and 6 years experience building practical reusable workflows or systems
Strong implementation skills in Python and modern AI / ML tooling
Strong hands-on experience with Python building ML/DL solutions with libraries (e.g. TensorFlow PyTorch Keras Scikit-learn) and LLM-based systems and agentic frameworks including RAG architectures prompt engineering embeddings fine-tuning evaluation and orchestration (e.g. ADK LangChain LangGraph Databricks Vertex AI Claude).
Experience with Java JavaScript/TypeScript React FastAPI SQL/PostgreSQL Snowflake S3 and enterprise data and knowledge systems.
Proficiency with Git Docker CI/CD with a strong focus on reproducibility deployment monitoring and production-ready MLOps.
Experience working directly with domain users or stakeholders to translate ambiguous needs into useful technical solutions
Strong collaboration and communication skills
PREFERRED QUALIFICATIONS
Experience in life sciences pharma biotech systems biology immunology translational science omics or related research environments.
Experience operating across scientific and technical disciplines with enough domain fluency to engage credibly with scientists while still bringing a strong applied-AI builder mindset.
Work Location Assignment: This is a hybrid role requiring you to live within commuting distance and work on-site an average of 2.5 days per week.
Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers develop and coach others oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.
NON-STANDARD WORK SCHEDULE TRAVEL OR ENVIRONMENT REQUIREMENTS
Occasional travel may be required to collaborate with colleagues across Pfizer sites participate in workshops support adoption activities or engage with internal and external partners.
Work Location Assignment: This is a hybrid role requiring you to live within commuting distance and work on-site an average of 2.5 days per week or more as needed.
Relocation assistance may be available based on business needs and/or eligibility.
Candidates must be authorized to be employed in the U.S. by any employer.
U.S. work visa sponsorship (such as TN O-1 H-1B etc.) is not available for this role now or in the future.
Sunshine Act
Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care providers name address and the type of payments or other value received generally for public disclosure. Subject to further legal review and statutory or regulatory clarification which Pfizer intends to pursue reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse your name address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter please do not hesitate to contact your Talent Acquisition representative.
EEO & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race color religion sex sexual orientation age gender identity or gender expression national origin disability or veteran status. Pfizer also complies with all applicable national state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.
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To learn more about acceptable and prohibited uses of AI during the recruitment process please review our candidate AI-use guidelines available onPfizer Careers.
Information & Business TechRequired Experience:
Senior Manager
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