Invent - Contextual Systems Engineer Senior Consultant

Position: Capgemini Invent - Contextual Systems Engineer Senior Consultant
# Capgemini Invent - Contextual Systems Engineer Senior Consultant Dallas Apply  for this job
* Permanent* Experienced Professionals
* Strategy & Transformation
* -en USAt Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose.##

About the Job You’re Considering At Capgemini Invent, our Data Driven Transformation (DDT) team makes AI work at scale by combining data science and engineering with business consulting. We build context-driven analytics and GenAI/agentic systems that reflect how decisions and work actually happen—grounded in semantic layers, strong data foundations, and governance embedded in decision flows. With a builder-advisor (“forward deployed”) mindset, DDT delivers production-ready impact across operations and customer domains, redefining what enterprise AI advisory looks like in practice.##

Your Role As a Senior Consultant, Contextual Systems, you will own defined work streams end‐to‐end within AI and data‐driven transformation engagements. You will design and implement the semantic and knowledge foundations that enable AI systems to understand enterprise context, working closely with senior architects and client data teams to deliver production‐quality solutions.

You will develop trusted relationships with day‐to‐day client counterparts, operate independently within your work streams, and manage priorities while escalating appropriately. In addition to client delivery, you will begin contributing to internal knowledge development and practice assets within the Data Driven Transformation team.

Core responsibilities include:
* Designing and implementing semantic layer architectures end‐to‐end, including LookML models, dbt metrics, and ontologies
* Building knowledge graph schemas and implementing Graph

RAG patterns for contextual AI retrieval
* Defining context contracts, including versioned semantic objects, governed datasets, and metric definitions
* Leading technical workshops to extract and encode enterprise knowledge into machine‐readable forms
* Evaluating and configuring knowledge platform tooling, including graph databases, vector stores, and embedding pipelines
* Partnering with AI engineering teams to integrate context layers into agentic and AI workflows## Your Skills + Experience 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:

* 5–6 years of experience in data engineering, data architecture, or knowledge management
* Hands‐on expertise with semantic layer tooling such as LookML, dbt, or equivalent technologies
* Experience designing and working with knowledge graphs (Neo4j preferred)
* Familiarity with modern LLM integration patterns, including RAG, embedding pipelines, and vector stores
* Strong ability to translate business semantics into formal, well‐governed technical specifications

Beneficial experience:
* Experience working across cloud data platforms such as Big Query or Snowflake
* Exposure to governance and catalog tooling (e.g., Collibra, Atlan)
* Interest in applied AI, agentic architectures, and enterprise‐scale contextual systems

The base compensation range for this role in the…