Pfizer

Senior Manager role focused on designing, developing, and deploying AI agents for enterprise workflow automation, decision enhancement, and intelligent user interactions. Requires experience with agentic orchestration frameworks, vector databases, RAG, and LLM principles, along with leadership in managing technical teams and delivering enterprise-scale projects.

Lead a team focused on rapidly determining the solvability of ambiguous AI/ML problems for commercial use cases in a regulated pharmaceutical environment. The role involves hands-on technical leadership, rapid prototyping (2-6 week cycles), enforcing engineering excellence, and guiding the adoption of Generative AI, including LLMs and RAG, with a focus on building production-ready prototypes that can scale.

AI/ML Engineer role focused on vaccine research, applying AI/ML to discover and develop vaccines. Responsibilities include shaping scientific strategy with AI, owning foundational and predictive modeling end-to-end, advancing generative AI for vaccine design, engineering robust ML systems, decoding high-dimensional biology, and elevating AI fluency. Requires PhD or Master's with experience in AI/ML within life sciences, knowledge of vaccine R&D, and expertise in foundation models, generative AI, and ML system design.

AI/ML Engineer role focused on vaccine research, applying AI/ML to discover and develop vaccines. Responsibilities include shaping scientific strategy with AI, owning foundational and predictive modeling end-to-end, advancing generative AI for vaccine design, engineering robust ML systems, decoding high-dimensional biology, and elevating AI fluency. Requires PhD or Master's with experience in AI/ML within life sciences, knowledge of vaccine R&D, and expertise in foundation models, generative AI, and ML system design.

This role focuses on building and deploying production-grade full-stack applications that integrate LLM and AI capabilities into pharmaceutical research workflows. Responsibilities include developing backend services for data processing, embedding generation, vector search, and LLM orchestration, creating frontend interfaces, implementing RAG systems and agentic LLM architectures, and deploying/maintaining systems on AWS. The role also involves contributing to semantic frameworks and conceptual research.

This role focuses on applying LLMs and agentic AI to scientific workflows in healthcare (Pfizer). The scientist will identify use cases, build reusable workflows and agentic systems, and partner with scientists to ensure adoption and impact. The role emphasizes practical application, scientific credibility, and scalable solutions.

Head of AI Delivery & Enablement (AIDE) at Pfizer, leading strategy and technical direction for applied AI in Inflammation & Immunology. Focuses on translating advances in LLMs, agentic systems, and multimodal AI into reusable capabilities, establishing governance and evaluation standards, and driving AI adoption. Requires strong technical credibility in AI/ML and computational biology, with experience in strategy, portfolio management, and scaling reusable solutions.

Senior Manager, Applied AI Workflow Scientist at Pfizer, focused on applying LLMs and agentic AI to scientific use cases in Inflammation & Immunology. The role involves identifying high-value scientific applications, building reusable AI workflows and agentic systems, and partnering with scientists to ensure adoption and impact. It emphasizes practical application, scientific credibility, user partnership, and scalable workflows.

This role focuses on building and deploying full-stack applications that integrate LLM and AI capabilities into pharmaceutical research workflows. Responsibilities include developing backend services for data processing, embedding generation, vector search, and LLM orchestration, implementing RAG systems and agentic architectures, and creating frontend interfaces. The role also involves contributing to semantic frameworks and deploying systems on AWS.

Director of AI Engineering role focused on applying AI automation and advanced analytics in regulated healthcare R&D operations. The role involves leading the definition and delivery of AI solutions for lab and office workflows, strengthening operational decision-making through predictive models, enabling regulated AI systems with governance, optimizing development planning, and engineering/scaling production-grade ML platforms. Requires expertise in predictive modeling, optimization, automation, generative AI, and ML system design, with strong programming skills in Python and ML frameworks, and experience scaling models in cloud/HPC environments. Collaboration across scientific, operational, quality, and business teams is critical.