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Manager - Staff Engineer

Salary
$99.2K–$165.4K
USD
Moves you to
United States
Support
Relocation support
Posted
Sep 24, 2026
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Use Your Power for Purpose

At Pfizer, technology impacts everything we do. Our digital and 'data first' strategy focuses on implementing impactful and innovative technology solutions across all functions, from research to manufacturing. By digitizing drug discovery and development, identifying solutions, or making our work easier and faster, you will be making a difference to countless lives. Your dedication and hard work will be instrumental in helping Pfizer achieve new milestones and make a positive impact on patients worldwide.


What You Will Achieve


Builds and maintains software systems, focusing on code quality, architecture, and reliable delivery of business value. In the AI era, emphasizes verification and review of AI-generated code.


You embed directly with business units — Commercial, Manufacturing, and R&D — operating like a "startup CTO" who bridges building products and solving real business problems. As part of the discovery-to-scale pipeline, you identify recurring patterns and hand validated solutions to Platform Engineers for generalization into enterprise capabilities.


This role encompasses large features and technical initiatives including leading small projects. You will do self-directed work while seeking input on strategic decisions, shape team practices and mentor junior engineers. You will handle high complexity with comfort navigating ambiguity.


ROLE BEHAVIOURS

- Don't Lose Your Curiosity: Proactively investigates root causes; experiments with new technologies and AI capabilities; protects time for exploration; treats failure as learning; discovers requirements through immersion in problem spaces

- Own the Outcome: Takes end-to-end ownership of features and business outcomes; accepts technical debt intentionally when it accelerates value; builds trust through rapid delivery of working solutions; owns stakeholder relationships; balances quality with delivery speed

- Be Polymath Oriented: Applies knowledge from one domain to inform decisions in another; studies adjacent fields like design, business, or science; begins learning domain language of business partners

- Communicate with Precision: Writes clear documentation and specifications; reduces ambiguity in requirements; crafts effective prompts for AI tools; adapts communication style for different audiences

- Think in Systems: Identifies upstream and downstream impacts; uses observability tools to trace requests across services; understands feedback loops; maps dependencies before making changes


ROLE RESPONSIBILITIES


DELIVERY

You own feature delivery from design through deployment, making sound technical trade-offs to ship value on time:


- Application Deployment: You select appropriate deployment patterns (Monorepo, Client-Server, Microservices) based on team and application needs. You integrate enterprise SSO, configure deployment workflows, and troubleshoot deployment failures.

- Data Integration: You integrate multiple data sources independently, clean messy datasets, handle inconsistent formats and missing values, and document data lineage. You troubleshoot integration failures.

- Full-Stack Development: You deliver complete features end-to-end independently—frontend, backend, database, and infrastructure (CloudFormation/Terraform). You make pragmatic technology choices and deploy what you build.

- Problem Discovery: You navigate ambiguous problem spaces independently. You discover requirements through observation and user shadowing, reframe problems to find higher-value solutions, and distinguish symptoms from root causes.

- Prototype to Production: You independently convert full prototypes to production across frontend, database, LLM, and retrieval layers. You know which skill owns each concern and apply its production patterns without re-inventing them.


ARTIFICIAL INTELLIGENCE

You integrate AI capabilities into solutions, critically evaluate AI-generated code, and never ship code you don't understand:

- AI Evaluation & Observability: You design evaluation frameworks with custom evaluators tailored to your use case. You build golden datasets, establish annotation workflows with clear rubrics, and run experiments to compare prompt and model changes systematically.

- AI Literacy: You evaluate AI solutions critically for specific use cases. You understand bias, fairness, and hallucination risks. You make informed decisions about when AI helps vs when traditional approaches are better.

- AI-Augmented Development: You integrate AI tools strategically into your development workflow. You review AI-generated code with the same rigor as human code and never ship code you don't fully understand.

- LLM Integration: You build reliable LLM integrations with appropriate model selection, streaming responses, structured output, and error handling. You optimize for cost and latency and choose between authentication methods based on requirements.

DOCUMENTATION

You design documentation strategies for your projects, ensure knowledge persists beyond individuals, and write specifications that enable effective collaboration:

- Developer Experience: You design golden paths—opinionated, well-documented workflows developers can follow with minimal cognitive load. You conduct user research, create self-service capabilities, and build for Day 50, not just Day 1.

- Knowledge Management: You design knowledge structures for discoverability, ensure knowledge accessibility across teams, facilitate knowledge sharing sessions, and reduce single-person dependencies.

- Pattern Generalization: You extract reusable components from field solutions, design appropriate abstractions that balance flexibility with simplicity, and collaborate with FDEs to validate generalized solutions in new contexts.

- Technical Writing: You create comprehensive documentation for complex systems. You write precise specifications that enable accurate AI-generated code, establish documentation practices for your projects, and ensure docs are discoverable.


MACHINE LEARNING

You design and deploy ML models for business problems, engineer effective features, monitor model performance, and communicate ML trade-offs to stakeholders:

- Model Development: You select appropriate algorithms for business problems, engineer effective features, deploy models to production, and monitor model performance. You communicate ML trade-offs to stakeholders.

- Model Fine-Tuning: You design fine-tuning strategies for business problems, select appropriate base models, optimize training hyperparameters, and evaluate model quality comprehensively. You communicate trade-offs between fine-tuning approaches.

- Retrieval Augmentation: You design production RAG systems with appropriate chunking, embedding, and retrieval strategies. You optimize for relevance and latency, handle edge cases, and evaluate end-to-end system quality.


BUSINESS

You translate business needs into technical solutions, manage stakeholder expectations, and articulate technical decisions in business terms:

- Business Immersion: You apply deep domain knowledge to technical solutions, bridge business and technology conversations fluently, speak the domain language naturally, and shadow operations to build understanding.

- Stakeholder Management: You manage multiple stakeholders with different interests, navigate conflicting priorities diplomatically, and build trust through consistent delivery. You tailor communication to each audience.


PEOPLE

You mentor junior engineers on technical topics, contribute to hiring through interviews, and actively build team knowledge:

- Multi-Audience Communication: You present complex topics clearly to any audience, facilitate productive discussions, translate between technical and business language fluidly, and write compelling proposals and specifications.

- Team Collaboration: You facilitate collaboration across the team, resolve minor conflicts before they escalate, enable others to succeed, and contribute positively to team dynamics and morale.


Here Is What You Need (Minimum Requirements)


  • Applicant must have a bachelor's degree, Computer Science, Engineering or related field preferred, with at least 4 years of experience; OR a master's degree with at least 2 years of experience; OR a PhD with 0+ years of experience; OR as associate's degree with 8 years of experience; OR a high school diploma (or equivalent) and 10 years of relevant experience ​
  • Proven track record of leading technical initiatives and mentoring team members.

PHYSICAL/MENTAL REQUIREMENTS

Extensive time at laptop


NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS

10% travel required


Work Location Assignment: Hybrid

Last date to apply: September 30, 2026

The annual base salary for this position ranges from $99,200.00 to $165,400.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 12.5% 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.

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 provider’s 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.

Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.

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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