Capgemini Invent- Contextual Systems Engineer Management Consultant

As a Managing Consultant, Contextual Systems, you will lead the end‑to‑end design and delivery of enterprise context platforms that enable AI systems to understand and operate on business knowledge at scale. You will own the architecture vision for a client’s semantic and knowledge layer, manage delivery teams, and ensure solutions meet both technical standards and business requirements. 

You will serve as a trusted advisor to VP‑level client leaders, including data architects, CDOs, and engineering executives, owning the technical relationship and guiding platform decisions. Operating with significant independence, you are accountable for engagement quality, team performance, and client satisfaction. 

In addition to client delivery, you will contribute to account growth and practice development, helping shape DDT’s contextual systems methodology, reusable accelerators, and architectural standards. 

Core responsibilities include: 

• Leading end‑to‑end design and delivery of enterprise context platforms for major clients 

• Architecting knowledge graph solutions, semantic layers, and context store infrastructure at scale 

• Owning technical relationships with client data, AI, and engineering leadership 

• Establishing platform governance standards, versioning protocols, and reusable architectural patterns 

• Managing delivery teams to ensure quality, timeliness, and alignment with client objectives 

• Contributing to DDT’s contextual systems methodology and accelerator library 

• Driving account expansion by identifying adjacent platform and architecture opportunities 

You bring strong AI literacy, including core AI and generative AI concepts, and understand how these capabilities apply to enterprise transformation. You are able to identify and support AI‑enabled opportunities that improve business outcomes and delivery effectiveness, and you have experience working in AI‑augmented ways of working to enhance research, analysis, and solution development. You collaborate effectively across strategy, technology, data, and design to enable AI‑driven solutions, with a solid understanding of responsible AI principles such as ethics, privacy, security, and governance. You demonstrate curiosity and a continuous learning mindset around emerging AI capabilities and their practical application in client environments. 

Required: 

• 7–9 years of experience in data or knowledge architecture, with enterprise‑scale delivery experience 

• Deep expertise in semantic layers, knowledge graphs, and metadata management 

• Proven experience leading technical delivery teams in consulting or client‑facing environments 

• Strong understanding of AI/ML integration patterns and governed data infrastructure 

• Demonstrated ability to architect platforms designed to scale and endure beyond the engagement 

Beneficial experience: 

• Experience across cloud data platforms such as BigQuery or Snowflake 

• Familiarity with governance and catalog tooling (e.g., Collibra, Atlan) 

• Interest in applied AI, contextual systems, and agent‑enabled architectures