Senior Engineer

We are:

The Advanced Technology Centers (ATCs) are the engine for reinvention in our clients’ transformation journey. Powered by more than 255,000 people across 24 countries, ATCs provide our clients with seamless access to industry insights and innovative technology solutions.

Stronger together!

The Advanced Technology Centers (ATCs) make a tremendous impact in solving our clients’ business problems by leveraging innovation, intelligence, industry insights, new IT, and new technology skills. With the global environment changing at a faster pace, our clients are facing unprecedented challenges, and they need us more than ever before. As a Network, ATCs are positioned to unlock greater opportunities and exponential value for our clients.

The value for our clients and our people:

For our clients, the Network provides the strength of our geographic diversity, greater resilience, and seamless access to the deepest industry knowledge, the latest in Gen AI solutions, and tech expertise from around the world.

For our people, it brings an opportunity to shape truly boundaryless career paths in a highly collaborative team of experts where they can learn from each other and solve the world’s most complex client challenges.

You are a Knowledge Architect at the intersection of semantic AI and agentic systems — shaping the knowledge backbone of AI platforms by designing the ontologies, graphs, and data models that enable intelligent agents to reason, plan, and act. You are equally comfortable whiteboarding an ontology with a domain expert and pushing graph schemas to production alongside an ML team. You see the world as a graph, and you believe that well-structured knowledge is the foundation of truly intelligent machines.

You thrive on translating complex, messy real-world knowledge into clean, reasoned, machine-readable structures that AI agents can act on — and you bring the rigor, curiosity, and collaboration to do it at scale.

You will embed directly with clients as a trusted technology advisor and hands-on engineer — leading the architecture and development of knowledge graphs, ontologies, and semantic data models that power next-generation agentic AI systems at enterprise scale.

• Own the end-to-end design, governance, and maintenance of enterprise-scale knowledge graphs and ontologies, bridging structured domain knowledge with large-scale agentic AI pipelines to enable reasoning, planning, and decision-making.

• Develop and govern ontologies, taxonomies, and semantic data models that formalize domain knowledge and support interoperability across systems and teams.

• Define and enforce data modeling standards, schema design patterns, and best practices for structured and semi-structured knowledge representation.

• Translate complex domain knowledge from subject matter experts into formal, machine-readable knowledge structures using RDF, OWL, SPARQL, or property graph models.

• Lead knowledge engineering discovery workshops and working sessions with client stakeholders to surface, validate, and formalize domain knowledge requirements.

• Collaborate with AI/ML engineers to integrate knowledge graphs as grounding and contextual layers for LLM-based agentic pipelines and retrieval-augmented generation (RAG) systems.

• Design knowledge structures that support multi-step agent reasoning, tool use, and dynamic planning across heterogeneous data sources.

• Work with project teams, team leaders, delivery leads, and client stakeholders to create standout Data & AI offerings powered by graph-based technologies.

• Collaborate with data engineering and platform teams to build scalable pipelines for knowledge graph population, enrichment, and lifecycle management.

• Develop strong client relationships and earn the trust of key stakeholders as a strategic advisor.

• Communicate complex ontological concepts and graph architectures clearly to both technical and non-technical audiences.

• Evaluate and pilot emerging tools, frameworks, and standards (e.g., LPG vs. RDF, Wikidata, schema.org, W3C standards).

Knowledge Representation & Ontology

• Ontology design and engineering (OWL, RDF, RDFS)

• Taxonomy and thesaurus…