AI Knowledge Engineer

Are you ready to be a part of the AI reinvention of industry and revolutionize your career?

In today’s world, our mission for AI reinvention is to be the leading reinvention partner for global enterprises by building a strong digital core and unleashing artificial intelligence to create 360° value at speed.

That’s where Global Center for AI & Data comes in. We bring together strategic visionaries, industry experts, data and AI practitioners, analytics professionals, and technology specialists to co-create each client’s unique path to reinvention.

You will work with multidisciplinary teams to help organizations transform complex enterprise data, unstructured data and domain expertise into trusted, governed and AI-ready knowledge, enabling advanced analytics, Generative AI and intelligent agent-based solutions.

Accenture’s Global Center for AI & Data is a unified capability center intended to bring together Accenture’s AI and data talent across its global reinvention efforts to help clients reinvent faster, scale AI, and accelerate priority skills development.

WORK YOU’LL DO

As part of the Global Center for AI & Data (out of Greece), you will design and implement the knowledge foundations that enable modern AI and Generative AI solutions.

As an AI Knowledge Engineer, you will work at the intersection of data, semantic technologies and Generative AI, transforming structured and unstructured enterprise information into reusable, trusted knowledge that can be effectively discovered and used by people, applications and AI agents.

You will work across knowledge graphs, semantic models and layers, enterprise search and document retrieval, RAG and agent context engineering, helping AI systems access the right enterprise knowledge with the appropriate meaning, context and governance.

There will never be a typical day, and you will continuously learn and grow while working on innovative Data & AI initiatives across industries.

Key Responsibilities

• Design and maintain enterprise knowledge models, semantic layers, ontologies, taxonomies and knowledge graphs that represent business concepts, entities and relationships.
• Transform structured and unstructured enterprise information into trusted, reusable and AI-ready knowledge, applying appropriate metadata, semantics and relationships.
• Design and implement enterprise search, document retrieval and RAG solutions, combining semantic, vector, keyword and graph-based retrieval where appropriate.
• Develop knowledge ingestion and enrichment capabilities, including entity and relationship extraction, classification, linking and entity resolution, using NLP and LLM techniques.
• Contribute to agent context engineering, ensuring AI agents receive relevant enterprise knowledge, metadata, instructions and contextual information to support reliable responses and actions.
• Support the design of appropriately scoped agent memory, enabling agents to retain and reuse relevant context while considering privacy, security, provenance and lifecycle requirements.
• Integrate knowledge solutions with enterprise data platforms, document repositories, metadata/catalog platforms, APIs and AI applications.
• Apply knowledge quality, provenance, lineage, access control and governance principles to improve the trustworthiness and traceability of knowledge used by AI solutions.
• Apply software engineering best practices to develop scalable, maintainable, testable and production-ready solutions.
• Collaborate with AI engineers, data engineers, architects, domain experts and business stakeholders to translate business knowledge into effective technical solutions.

WHO WE’RE LOOKING FOR

• Bachelor’s degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Information Systems, or another relevant discipline. A Master’s or PhD is considered an advantage.
• 4+ years of relevant experience in Data/AI, data engineering, software engineering or related areas, with recent hands-on exposure to Knowledge Graphs, semantic technologies or Knowledge Engineering.
• Strong understanding of knowledge representation and semantic modeling, including entities, relationships, ontologies, taxonomies and semantic models.
• Hands-on experience with knowledge graphs or graph databases and associated query/modeling approaches such as RDF/SPARQL or property graphs/Cypher.
• Strong programming skills in Python, with experience integrating APIs and processing structured and unstructured information.
• Understanding of Generative AI and LLM architectures, including embeddings, vector search, semantic search and Retrieval-Augmented Generation (RAG).
• Experience with information retrieval, document processing or NLP, including techniques such as entity extraction, classification or entity resolution.
• Understanding of how semantic layers, metadata and enterprise knowledge can provide trusted business context to AI applications.
• Familiarity with software engineering practices including Git, testing, CI/CD, APIs, and containerization.
• Strong analytical, communication and collaboration skills, with the ability to translate business concepts into technical knowledge models and work effectively in multidisciplinary environments.

CONSIDERED A PLUS

• Experience designing or implementing GraphRAG or hybrid retrieval solutions.
• Experience with agentic AI, including context engineering, agent memory patterns or multi-agent solutions.
• Experience with enterprise metadata/catalog platforms such as Alation, Collibra, Microsoft Purview, Informatica, or equivalent technologies.
• Experience integrating knowledge graphs with Databricks, Snowflake, cloud data platforms, lakehouses, or data warehouses.
• Familiarity with MCP and developing REST APIs.
• Relevant cloud, data, graph, or AI certifications.

WHAT’S IN IT FOR YOU?

• Competitive salary and benefits, including but not limited to: life/health insurance, performance-based bonuses, monthly vouchers, company car (depending on management level), flexible work arrangements, employee share purchase plan, TEA Accenture, parental leave and various corporate discounts.
• Continuous training & development through global platforms & local academy. At Accenture, we believe in bringing the best to our clients through continuous learning & improvement – from basic skills to industry-specific content – available to all our people.
• Career coaching and mentorship to help you manage your career and develop professionally.
• Ongoing strength and skill-based evaluation process.
• Various opportunities to develop your career across a spectrum of clients, industries and projects.
• Diverse and inclusive culture.
• Opportunities to get involved in corporate citizenship initiatives, from volunteering to doing charity work.