Accenture
Knowledge Engineering Consultant / Team Lead
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YOU ARE
You are a strong individual contributor knowledge engineer growing into a team lead. You are well versed in the full knowledge graph development lifecycle. You formulate real-world problems into practical, efficient, scalable AI and Knowledge Graph solutions, working hands-on across the lifecycle from ingestion through modeling, curation, and deployment. You apply current methodologies, techniques, and algorithms with the right architecture, and begin to guide junior engineers on the project. You stay current with knowledge engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with the team. You collaborate with users, use case reps, engineers, architects, and UI designers to deliver their piece of an end-to-end solution.
THE WORK
- Build Knowledge Graph components that contribute to transforming a client's data architecture.
- Design, develop, and implement AI and semantic solutions; ensure their work integrates cleanly with the broader system.
- Work alongside the project team and delivery leads.
- Build solid working relationships with client counterparts on their workstream.
- Help assemble the supporting evidence for the recommended semantic layer solution.
- Support Accenture sales efforts when called on.
- Keep developing skills in cutting-edge Data & AI solutions, especially agentic technologies, and share with the team.
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BASIC (REQUIRED) QUALIFICATION
- Bachelor's degree or equivalent, plus at least 3 of the following:
- Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)
- Experience in schema design, ontology management, and KG curation
- Well versed in designing and developing KG solutions and graph-based ML models (functional + technical)
- Proven experience with end-to-end data pipeline implementation for AI applications (esp. LLMs), with hands-on design and configuration
- Strong knowledge and working experience with relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases
- (no leadership/commercial requirement at this band)
PREFERRED QUALIFICATION
- Hands-on experience with cloud platforms (AWS, Azure, GCP)
- Well versed in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow)
- Practical experience with NLP and/or Search techniques
- Prompt engineering, and LLMs for enterprise-scale applications.
- You have team lead experience
- Strong collaboration skills with the ability to work across engineering, research, and product teams across multiple time zones.
- You have external client-facing consulting experience
- Broad experience in diverse ML techniques and agentic systems
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
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