Capgemini Invent is seeking inventive transformation consultants to lead cutting-edge solutions in Pharma AI and Smart Manufacturing. Join a team that blends strategic, creative, and scientific capabilities to address client challenges with data-informed, design-driven, and purpose-built technology.

This role focuses on driving digital transformation within pharmaceutical manufacturing, leveraging AI and advanced analytics to optimize processes and ensure quality. We offer a supportive environment with flexible work arrangements and abundant opportunities for career growth and skill development, including certifications in emerging technologies like Generative AI.

Lead discovery workshops to define problem statements, value cases, and transformation roadmaps for pharma manufacturing.

Drive proposal response strategy, solutioning, estimation, and delivery approaches for RFPs.

Own delivery estimation and planning, including work breakdown, resourcing, and timelines.

Act as a trusted advisor to clients, influencing decision-making through executive communication and structured recommendations.

Lead multi-workstream delivery governance across sites, managing stakeholders, vendors, and distributed teams.

Drive paperless manufacturing initiatives, focusing on MES/eBR, recipe/batch execution, and materials management.

Lead lab transformation and standardization of QC processes through LIMS/QC Digitization.

Spearhead digital quality initiatives, including deviations, CAPA, change control, and document management.

Define integration blueprints for IT/OT and data architecture across various manufacturing systems.

Identify and lead AI/advanced analytics use cases for predictive quality and process optimization.

Possess 10–14 years of experience in Pharma/Life Sciences manufacturing digitalization, with a strong background in consulting delivery leadership.

Hold a Bachelor’s or Master’s degree in Engineering, Technology, Industrial, Pharma, Chemical, or related fields, alongside an MBA or equivalent from a reputed institute.

Demonstrate strong experience in at least two of the following: MES/eBR, LIMS, or eQMS/QMS, with exposure to integration and data platforms. Pharma MES experience is a plus.

Proven experience in client management, including CXO-level engagements and advisory roles.

Familiarity with ISA-95/ISA-88 standards, manufacturing data contextualization, and IIoT/historian integrations.

Experience with cloud data platforms, MLOps concepts, and governance in regulated environments is essential.

Proficiency in Agile delivery methodologies (Scrum/SAFe), Lean/Six Sigma, and building demos/POVs.

Experience in delivering or leading 1-2 analytics/AI initiatives in manufacturing or quality contexts.