Senior Manager, AI Engineering -- Clinical Development and Operations (CD&O)

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 you’ll 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

• Master's 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

• Bachelor’s 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.

The annual base salary for this position ranges from $139,100.00 to $231,900.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 17.5% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.

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.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.

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