# Knowledge Engineering Lead

**Company**: Accenture
**Experience**: senior
**Job type**: full-time
**Category**: IT
**Industry**: Consulting

**Apply**: https://accenture.wd103.myworkdayjobs.com/en-US/AccentureCareers/job/Hong-Kong/Data---AI-Engineering-Manager-Consultant_R00341022?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_b832be31-be0

## Description

You lead a significant knowledge engineering scope and function within a large program, actively contributing to thought leadership. You shape how a substantial body of work formulates real-world problems into scalable AI and KG solutions, setting the technical direction for that scope.

You lead a team and guide exploration and implementation of new methodologies, model building techniques and cutting-edge algorithms. You remain at the forefront, driving innovation by applying these techniques to new business problems, use cases and scenarios.

Key responsibilities:

- Lead the build of Knowledge Graph solutions that transform a client's data architecture within program scope.

- Direct the design, development and implementation of AI and semantic solutions, ensuring seamless integration.

- Collaborate with project leaders, delivery leads and client stakeholders to create standout, graph-powered Data & AI offerings.

- Develop strong client relationships and earn the trust of key advisors.

- Make the business case for the semantic layer solution recommended to the client.

- Contribute to Accenture sales and pre-sales efforts.

- Provide thought leadership on technology trends, new opportunities, innovations and foreseeable limitations, risks and concerns.

Requirements:

- Bachelor's degree or equivalent, plus at least 4 of the following:

- Minimum 3 years of experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL).

- Minimum 3 years of experience in schema design, ontology management and KG curation.

- Minimum 3 years of designing and developing KG solutions and graph-based ML models.

- Minimum 2 years of experience with end-to-end data pipeline implementations for AI applications.

- Minimum 4 years of experience with strong knowledge of relational databases, object stores, graph databases and vector databases.

- Minimum 2 years of experience in leading a team or workstream within a larger program.

## Skills

### Required
- Knowledge Graph technologies
- RDF
- SPARQL
- LPG
- SHACL
- schema design
- ontology management
- KG curation
- graph-based ML models
- data pipeline implementations
- relational databases
- object stores
- graph databases
- vector databases

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