Our client is a fast-growing technology consulting firm that helps major corporations transform their operations and products through strategy, generative AI, and implementation. The company integrates AI agents, business expertise, and technology to address complex challenges across industries, including pharmaceuticals, telecommunications, finance, and manufacturing.
With a focus on practical, measurable transformation, teams support clients from initial strategy and proof of concept through production deployment and ongoing operations. The company is building an ambitious, collaborative culture in which professionals take ownership, work closely with senior client stakeholders, and create solutions tailored to real business needs. This is an opportunity to join an entrepreneurial organization at an important stage of growth, with the opportunity to shape its pharmaceutical practice, develop reusable knowledge and solutions, and contribute to its broader global expansion.
As Pharma Project Lead, you will lead pharmaceutical industry projects from initial client engagement and project planning through solution design, implementation, and operational adoption. You will work directly with leaders and practitioners across medical affairs, clinical development, pharmacovigilance, digital, and related functions to identify business challenges and design high-value applications of generative AI.
You will manage project progress, quality, and stakeholders while coordinating consultants, engineers, and client teams. Your work may include clinical development planning, protocol framework generation, adverse-event information extraction, MSL and MR activity digitalization, literature review, and content creation. You will help transform workflows through AI agents—not simply deliver isolated proofs of concept—while ensuring alignment with GxP requirements, pharmacovigilance regulations, promotional codes, ROI expectations, and operational realities. You will also build trusted client relationships, develop new opportunities, and contribute to the standardization of knowledge and delivery methods.
