Capgemini Invent - Contextual Systems Engineer Senior Consultant

Capgemini • Chicago, IL

1d • $105,600 - $199,480 • Remote

About The Position

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.

Requirements

• 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
• Strong AI literacy, including core AI and generative AI concepts, and understand how these capabilities apply to enterprise transformation.
• Ability to identify and support AI‑enabled opportunities that improve business outcomes and delivery effectiveness.
• Experience working in AI‑augmented ways of working to enhance research, analysis, and solution development.
• 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.
• Demonstrate curiosity and a continuous learning mindset around emerging AI capabilities and their practical application in client environments.

Nice To Haves

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

Responsibilities

• Designing and implementing semantic layer architectures end‑to‑end, including LookML models, dbt metrics, and ontologies
• Building knowledge graph schemas and implementing GraphRAG 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

Benefits

• Medical, dental, and vision coverage
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
• Company paid holidays
• Personal Days
• Sick Leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed