Senior Knowledge Graph Engineer
$152k - $178.3kThe Coca-Cola Company
Job Description Summary:
Job title: Senior Knowledge Graph Engineer
At The Coca-Cola Company, our vision is to craft brands and choices people love while refreshing the world in more ways than ever before. Data and intelligence are at the heart of how we understand consumers, accelerate growth, and create a more connected enterprise. The Senior Knowledge Graph Engineer play a pivotal role in building the semantic foundations that drive consistent, trusted, and actionable data across our global system. This role will be part of a forward-looking Data Engineering and Platforms team, enabling scalable use of trusted data, advanced analytics, and knowledge graphs to power decision-making.
Semantic clarity is essential for interoperability across markets, AI models, and platforms. This role will drive the creation of a governed semantic and graph foundation that connects fragmented data sources and enables agents, copilots, analytics, and operational decision-making. This is an individual contributor role focused on hands-on technical leadership, solution design, and delivery excellence rather than direct people management.
Core Responsibilities
Lead the design, development, and maintenance of enterprise ontologies, taxonomies, controlled vocabularies, and graph models to enable semantic consistency and interoperability.
Define modeling standards, reusable patterns, and implementation strategies for ontologies, entity relationships, upper ontology concepts, and property graph structures.
Integrate graph solutions with enterprise data stores, APIs, MCP servers, and related technologies to meet stakeholder needs.
Architect scalable mapping pipelines that connect distributed physical data sources to the logical graph layer without data redundancy.
Enable AI and machine learning through structured knowledge representations that improve inference, entity resolution, and data discoverability.
Use LLMs, GenAI, rules engines, reusable frameworks, and automation utilities to curate, build, adapt, and evolve the corporate ontology catalog.
Implement semantic validation, formal reasoning, and performance monitoring frameworks to ensure model correctness, scalability, auditability and reliability.
Design semantic layers that explicitly bind underlying physical data tables to the enterprise ontology, ensuring autonomous agents and subagents are grounded in deterministic business logic rather than probabilistic LLM outputs.
Develop context-injection and semantic routing patterns that allow multi-agent systems to securely query and traverse the knowledge graph for complex, multistep reasoning and planning.
Establish the graph model as the foundational long-term memory and context engine for enterprise copilots, enabling agents to maintain state and context across disjointed user sessions.
Required Qualifications & Experience
Bachelor’s or master’s degree in information science, library science, ontology, semantics, computational linguistics, computer science, or related field.
2+ years of experience defining and implementing production-grade knowledge graphs and ontologies.
Ability to develop and implement ontologies and data models in collaboration with stakeholders across data management, search, product management, machine learning, and other enterprise initiatives.
3+ years of experience with knowledge graph technologies such as RDF, OWL, SHACL, SKOS, LPG, and SPARQL.
At least 2 years of experience or training with ontology and linked data tools such as Protégé, TopQuadrant, Stardog, Jena, or Data.World.
Expert proficiency with graph query languages such as Cypher, GQL, or SPARQL.
Familiarity with enterprise ontology management suites and governance frameworks, including Knowledge Graph (organizational, GraphRAG, Query/Traversal) patterns.
Hands-on experience integrating knowledge graphs with LLM orchestration and agent frameworks (e.g., LangChain, AutoGen, Semantic Kernel) to build productiongrade GraphRAG pipelines.
Proficiency in hybrid retrieval strategies, combining vector embeddings with graph traversals to optimize agent context windows.
Preferred Qualifications
Understanding of the development of ontologies and the use of controlled vocabularies and thesauri in enhancing the discovery of management of enterprise data.
Experience designing architectures that manage parallel, autonomous AI subagents, utilizing the graph to enforce boundaries and prevent conflicting actions.
Familiarity with exposing graph traversal functions as distinct 'tools' or 'skills' for LLM tool-calling (e.g., via OpenAI function calling or MCP servers).
Experience with Palantir, Microsoft Fabric and Microsoft Foundry.
Success Measures
Evaluate the current state of semantic pilots, data assets, and structural mappings across the organization.
Standardize the core taxonomical conventions and architectural blueprints for initial multi-domain integration.
Demonstrate a measurable reduction in AI hallucination rates and a quantifiable increase in autonomous multi-step task completion by leveraging the governed semantic foundation.
Showcase a quantifiable increase in context-retrieval accuracy and performance for dependent enterprise AI applications.
Skills:
Pay Range:
United States of America: 152,000 USD - 178,300 USDBase pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.
Annual Incentive Reference Value Percentage:
15Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.
Location(s):
United States of AmericaCity/Cities:
AtlantaTravel Required:
00% - 25%Relocation Provided:
NoJob Posting End Date:
August 20, 2026Our Purpose and Growth Culture:
We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.- McKinsey & Company in the United States (Georgia, Atlanta) seeks a data engineer to build graph-centric data pipelines and a semantic data layer powering GenAI applications across regions. You will design entity/relationship models, implement ingestion, normalization, and...Senior
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