Sr. Manager, AI Engineer

ROLE SUMMARY

Join Pfizer Digital’s Commercial Creation Center & CDI organization (C4) to leverage cutting-edge technology for critical business decisions and enhance customer experiences for colleagues, patients, and physicians. Our team of engineering, data science, and AI professionals is at the forefront of Pfizer’s transformation into a digitally driven organization, using data science and AI to change patients’ lives, leading process and engineering innovations to advance AI and data science applications from prototypes and MVPs to full production.

As a Sr. Manager, AI Engineer, you will be a hands-on technical expert responsible for architecting and delivering user-facing AI features, full-stack application components, and data-driven visualizations that empower commercial decision-makers. 
 
You will work within a cross-functional product team — partnering with data scientists, product owners, and local commercial stakeholders — to iteratively develop, test, and ship AI-powered capabilities. This role emphasizes product delivery, user experience, and engineering quality. You translate business needs into working software that users love. 

 

ROLE RESPONSIBILITIES

1) AI Product Feature Development 

• Design and develop end-to-end AI-powered features for DecisionIQ: from data ingestion and model integration through API development and frontend delivery 

• Build and maintain data ETL pipelines using Python and SQL; integrate ML model outputs into production application workflows 

• Develop server-side logic using Python and back-end technologies; implement RESTful APIs to connect AI components with the broader application 

• Create responsive, visually appealing web interfaces and interactive data applications using modern frontend frameworks (React, Vue) and visualization libraries (Dash, Streamlit, Tableau, Power BI) 

• Synthesize complex data and model outputs into intuitive visualizations that non-technical commercial users can act on confidently 

2) User-Centric Development & Stakeholder Collaboration 

• Partner with product owners, data scientists, and local commercial stakeholders to gather user requirements and translate them into technical specifications 

• Drive iterative development with rapid prototyping, user feedback loops, and continuous improvement of DecisionIQ capabilities 

• Communicate complex technical concepts and insights to both technical and non-technical stakeholders to inform product decisions 

• Collaborate with cross-functional teams to ensure successful integration of reusable AI components into production solutions 

3) Engineering Quality & Best Practices 

• Enforce coding standards, best practices, and thorough testing (unit, integration, E2E) to ensure reliability and maintainability 

• Implement and maintain CI/CD pipelines for smooth, frequent software delivery 

• Implement logging and monitoring tools to gain insights into system behavior; proactively identify and resolve production issues 

• Perform root cause analysis to diagnose and fix production errors; maintain high system availability 

4) Team Contribution & Knowledge Sharing 

• Contribute to a highly effective engineering team; actively help colleagues grow through mentoring, code reviews, and knowledge sharing 

• Train and guide junior developers on AI, data science, and software development best practices 

• Stay up-to-date with emerging technologies and evaluate their applicability to DecisionIQ 

• Act as a subject matter expert for AI solution engineering on cross-functional teams 

This role covers a broad spectrum of skills and we encourage you to apply even if you meet partially.

 

BASIC QUALIFICATIONS 

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field 

• 7+ years of experience in software engineering, data science, or related technical fields 

• Proven experience as a Full Stack Engineer or AI Solution Engineer with a strong portfolio of shipped products 

• Solid experience in Python and relevant ML libraries/frameworks (scikit-learn, TensorFlow, PyTorch) 

• Solid understanding of back-end technologies, databases (SQL and NoSQL), and RESTful APIs 

• Good knowledge of data manipulation, preprocessing, feature engineering, and ETL pipeline development 

• Good understanding of statistical modeling, machine learning algorithms, and data mining techniques 

• Experience building interactive web applications with JavaScript frameworks (React, Vue, or AngularJS) 

• Experience building dashboards and data applications (Tableau, Power BI, Dash, Streamlit) 

• Familiarity with cloud-based analytics ecosystems (AWS, Snowflake) 

• Proficiency in Git for version control 

• Hands-on experience working in Agile teams, processes, and practices 

• Highly self-motivated; strong English communication skills (written and verbal) 

PREFERRED QUALIFICATIONS 

• Advanced degree in Computer Science, Data Science, Statistics, or related field 

• Experience with CI/CD integration (GitHub, GitHub Actions) and containers (Docker) 

• Experience with responsive UI technologies (HTML, Tailwind CSS, Bootstrap, Material, Vuetify) 

• Experience with Infrastructure as Code (IaC) tools such as Terraform, Ansible, or CloudFormation 

• Experience with data science platforms (Dataiku DSS, AWS SageMaker) 

• Familiarity with monitoring and observability tools (Prometheus, Grafana, ELK stack) 

• Experience with LLM frameworks (LangChain, Langfuse) and prompt engineering 

• Background in product-led engineering teams 

Please apply by sending your CV in English.

Work Location Assignment: Hybrid

Information & Business Tech