Knowledge Graph & Agentic GenAI Specialist
We are seeking a Knowledge Graph & Agentic GenAI Specialist with X+ years of experience to lead and deliver enterprise-scale GenAI and Knowledge Graph solutions.
This role sits within our Data & AI Consulting practice and focuses on building reasoning ‑heavy, graph ‑centric GenAI systems for complex business domains. The ideal candidate brings deep expertise in Knowledge Graph engineering, combined with hands-on experience in Agentic AI and Graph RAG architectures, and can lead client engagements from ideation through production deployment.
Key Responsibilities
Knowledge Graph & Graph RAG
Design, build, and scale enterprise Knowledge Graphs, including schema, ontology, and relationship modeling for complex, high ‑cardinality domains; operate and optimize Neo4j platforms at scale with strong proficiency in Cypher, performance tuning, and ingestion pipelines. Architect and implement Graph RAG and Agentic GenAI solutions, combining Knowledge Graphs with LLMs using frameworks such as LangGraph, enabling multi ‑step reasoning, hybrid Graph + Vector retrieval, and end ‑to ‑end GenAI architectures from ingestion through inference.
Delivery, Leadership & Consulting
Lead project delivery and ensure client business objectives are achieved end ‑to ‑end. Contribute to solution ideation, technical design, and client workshops with stakeholders. Support pre-sales activities, including solution design, demos, and technical inputs for proposals. Build secure, scalable APIs and microservices, collaborating with data, ML, and product teams. Mentor, upskill, and provide technical guidance to team members; perform design and code reviews.
Required Skills & Experience
6+ years of hands-on experience in Knowledge Graphs, GenAI, or Agentic AI solutions. Strong hands-on experience with Neo4j (Enterprise preferred). Advanced proficiency in Cypher, including query optimization, indexing, and constraints. Proven experience managing large, complex, and evolving graph datasets, ideally at TB scale. Solid understanding of graph theory, traversal patterns, and graph algorithms. Hands-on experience with LangChain and LangGraph, especially for Graph RAG and agent orchestration. Strong understanding of RAG architectures, with emphasis on Graph RAG.
Experience integrating LLMs with structured data systems, embeddings, and vector databases. Strong Python development skills; hands-on experience with SQL and API development (REST/GraphQL/Cypher). Experience with at least one cloud platform: Azure, AWS, or GCP. Familiarity with Docker, Kubernetes, and CI/CD pipelines. Exposure to classical machine learning and data engineering is a plus.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related fields.
Demonstrated experience leading end-to-end solution delivery from ideation to deployment in client-facing environments.
Knowledge Graph & Agentic GenAI Specialist
We are seeking a Knowledge Graph & Agentic GenAI Specialist with X+ years of experience to lead and deliver enterprise-scale GenAI and Knowledge Graph solutions.
This role sits within our Data & AI Consulting practice and focuses on building reasoning ‑heavy, graph ‑centric GenAI systems for complex business domains. The ideal candidate brings deep expertise in Knowledge Graph engineering, combined with hands-on experience in Agentic AI and Graph RAG architectures, and can lead client engagements from ideation through production deployment.
Key Responsibilities
Knowledge Graph & Graph RAG
Design, build, and scale enterprise Knowledge Graphs, including schema, ontology, and relationship modeling for complex, high ‑cardinality domains; operate and optimize Neo4j platforms at scale with strong proficiency in Cypher, performance tuning, and ingestion pipelines. Architect and implement Graph RAG and Agentic GenAI solutions, combining Knowledge Graphs with LLMs using frameworks such as LangGraph, enabling multi ‑step reasoning, hybrid Graph + Vector retrieval, and end ‑to ‑end GenAI architectures from ingestion through inference.
Delivery, Leadership & Consulting
Lead project delivery and ensure client business objectives are achieved end ‑to ‑end. Contribute to solution ideation, technical design, and client workshops with stakeholders. Support pre-sales activities, including solution design, demos, and technical inputs for proposals. Build secure, scalable APIs and microservices, collaborating with data, ML, and product teams. Mentor, upskill, and provide technical guidance to team members; perform design and code reviews.
Required Skills & Experience
6+ years of hands-on experience in Knowledge Graphs, GenAI, or Agentic AI solutions. Strong hands-on experience with Neo4j (Enterprise preferred). Advanced proficiency in Cypher, including query optimization, indexing, and constraints. Proven experience managing large, complex, and evolving graph datasets, ideally at TB scale. Solid understanding of graph theory, traversal patterns, and graph algorithms. Hands-on experience with LangChain and LangGraph, especially for Graph RAG and agent orchestration. Strong understanding of RAG architectures, with emphasis on Graph RAG.
Experience integrating LLMs with structured data systems, embeddings, and vector databases. Strong Python development skills; hands-on experience with SQL and API development (REST/GraphQL/Cypher). Experience with at least one cloud platform: Azure, AWS, or GCP. Familiarity with Docker, Kubernetes, and CI/CD pipelines. Exposure to classical machine learning and data engineering is a plus.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related fields.
Demonstrated experience leading end-to-end solution delivery from ideation to deployment in client-facing environments.
Knowledge Graph & Agentic GenAI Specialist
We are seeking a Knowledge Graph & Agentic GenAI Specialist with X+ years of experience to lead and deliver enterprise-scale GenAI and Knowledge Graph solutions.
This role sits within our Data & AI Consulting practice and focuses on building reasoning ‑heavy, graph ‑centric GenAI systems for complex business domains. The ideal candidate brings deep expertise in Knowledge Graph engineering, combined with hands-on experience in Agentic AI and Graph RAG architectures, and can lead client engagements from ideation through production deployment.
Key Responsibilities
Knowledge Graph & Graph RAG
Design, build, and scale enterprise Knowledge Graphs, including schema, ontology, and relationship modeling for complex, high ‑cardinality domains; operate and optimize Neo4j platforms at scale with strong proficiency in Cypher, performance tuning, and ingestion pipelines. Architect and implement Graph RAG and Agentic GenAI solutions, combining Knowledge Graphs with LLMs using frameworks such as LangGraph, enabling multi ‑step reasoning, hybrid Graph + Vector retrieval, and end ‑to ‑end GenAI architectures from ingestion through inference.
Delivery, Leadership & Consulting
Lead project delivery and ensure client business objectives are achieved end ‑to ‑end. Contribute to solution ideation, technical design, and client workshops with stakeholders. Support pre-sales activities, including solution design, demos, and technical inputs for proposals. Build secure, scalable APIs and microservices, collaborating with data, ML, and product teams. Mentor, upskill, and provide technical guidance to team members; perform design and code reviews.
Required Skills & Experience
6+ years of hands-on experience in Knowledge Graphs, GenAI, or Agentic AI solutions. Strong hands-on experience with Neo4j (Enterprise preferred). Advanced proficiency in Cypher, including query optimization, indexing, and constraints. Proven experience managing large, complex, and evolving graph datasets, ideally at TB scale. Solid understanding of graph theory, traversal patterns, and graph algorithms. Hands-on experience with LangChain and LangGraph, especially for Graph RAG and agent orchestration. Strong understanding of RAG architectures, with emphasis on Graph RAG.
Experience integrating LLMs with structured data systems, embeddings, and vector databases. Strong Python development skills; hands-on experience with SQL and API development (REST/GraphQL/Cypher). Experience with at least one cloud platform: Azure, AWS, or GCP. Familiarity with Docker, Kubernetes, and CI/CD pipelines. Exposure to classical machine learning and data engineering is a plus.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related fields.
Demonstrated experience leading end-to-end solution delivery from ideation to deployment in client-facing environments.
KPMG – це міжнародна мережа фірм, що надають аудиторські, податкові та консультаційні послуги. В офісах KPMG у 143 країнах світу працюють понад 273,000 співробітників (FY23). Кожна фірма KPMG є незалежною юридичною особою і представляє себе як таку.
KPMG працює в Україні з 1992 року. KPMG в Україні надає аудиторські, податкові, бухгалтерські та консультаційні послуги для місцевих і міжнародних компаній. Нашою метою завжди було використання глобального інтелектуального потенціалу фірми в поєднанні з практичним досвідом наших українських професіоналів, щоб допомогти провідним компаніям досягти своїх цілей.
Офіси компанії знаходяться у Києві та Львові.
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KPMG is a global network of professional services firms providing audit, tax and advisory services. We operate in 143 countries and territories, and in FY23, collectively employed more than 273,000 people working in member firms around the world.
KPMG in Ukraine provides audit, tax, accounting and advisory services to local and international businesses. KPMG has been working in Ukraine since 1992, and our goal has always been to use the firm's global intellectual potential, combined with the practical experience of our Ukrainian professionals, to help leading companies to achieve their goals.
In Ukraine KPMG has its offices in Kyiv and Lviv.
