Use Your Power for Purpose At Pfizer, the impact of technology resonates through every facet of our operations, driving a transformative digital and 'data first' approach. Across all functions—from groundbreaking research to efficient manufacturing—we embrace innovative solutions that empower us to enhance every aspect of drug discovery and development. Your efforts in building robust, reusable AI Solutions and empowering development teams streamline processes, making our work not only faster but easier. In doing so, you contribute significantly to a mission that transcends mere efficiency; you become a vital part of saving countless lives. As a Staff Software Engineer, you will be reporting to the Head of Applied AI Engineering at the AI Center of Excellence division. Through hands-on development of reusable components and mentorship of fellow engineers, you play a pivotal role in democratizing AI capabilities across the organization. Your technical expertise and collaborative approach are essential, paving the way for transformative impacts across all functions, ensuring every stride we take is towards a healthier future powered by robust, scalable AI solutions. Role Responsibilities Design, develop, and maintain high-quality reusable AI components, SDKs, APIs, and templates that enable common AI capabilities across development teams Implement and optimize shared libraries and toolkits that standardize how we build, integrate, and deploy AI solutions Contribute to the architecture and implementation of solutions and services with focus on performance, reliability, and developer experience Ensure proper versioning, documentation, and maintainability of shared assets through hands-on development and code reviews Create and maintain comprehensive technical documentation, API references, and implementation guides for platform components Develop sample applications, tutorials, and best practice examples that accelerate developer onboarding and adoption Build developer tooling and automation that streamlines the integration and consumption of platform services Work closely with cross-functional teams to understand requirements and translate them into robust platform capabilities Collaborate with senior engineers and architects to implement strategic platform initiatives and technical roadmaps BASIC QUALIFICATIONS 7+ years in Software Engineering roles. Advanced degree in Computer Science or Engineering. Demonstrated experience building RESTful APIs, microservices, and distributed systems components Understanding of AI/ML engineering principles, model deployment, and MLOps practices Knowledge of software engineering best practices including testing, version control, and CI/CD processes Understanding of SDK design principles and API development best practices Knowledge of software architecture patterns and system design considerations Experience with monitoring, logging, and observability tools for distributed systems Ability to document technical concepts clearly and create developer-friendly resources PREFERRED QUALIFICATIONS Experience in pharmaceutical, healthcare, or regulated industry environments. Experience with core concepts of Large Language Models (LLMs), including prompt engineering, retrieval-augmented generation (RAG), orchestration, context management, evaluation strategies (factuality, safety, bias) Experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn) and model serving platforms. Knowledge of asynchronous programming, performance optimization, and concurrent processing Experience with open-source contribution and community engagement