Accenture UK & Ireland
Knowledge Engineering Senior Manager

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YOU ARE
You lead the complete knowledge engineering scope on our most strategic and complex programs; lead creation of thought leadership, innovation, and assets for the discipline. You own how the most demanding programs formulate real-world problems into scalable AI and KG solutions, setting strategy and architecture end to end. You lead and develop teams of engineers, building capability across the discipline and guiding adoption of new methods and algorithms. You define what staying at the forefront means for the practice; drive innovation and translate it into new offerings. You set the standards for how ontologies are designed, evaluated, and maintained across programs. You make the case to senior stakeholders and shape the methodologies and data architectures that prove value at scale. You lead the creation of thought leadership, innovation, and reusable assets that advance the discipline beyond any single engagement. You partner with business and technical leaders to direct end-to-end delivery across complex, multi-stakeholder programs.
THE WORK
- Lead the complete Knowledge Graph solution scope that transforms data architecture for our most strategic and complex clients.
- Own the design, development, and implementation of AI and semantic solutions across the program.
- Partner with project leaders, delivery leads, and senior client stakeholders to create stand-out, graph-powered offerings.
- Develop trusted-advisor relationships with senior client stakeholders.
- Make and defend the business case for the semantic layer solution at the executive level.
- Lead Accenture sales and pre-sales efforts and shape data transformation programs.
- Drive the practice's thought leadership, innovation, and asset development on trends and agentic technologies, and develop the teams who deliver them.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Basic (required) Qualification
- Bachelor's degree or equivalent
- Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)
- Experience in schema design, ontology management, and KG curation
- Expertise in designing and developing KG solutions and graph-based ML models (functional + technical)
- Experience with end-to-end data pipeline implementations for AI applications (esp. LLMs), with hands-on design and configuration
- Experience with strong knowledge of relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases
- Managerial experience leading people, able to explain the value of the semantic layer and knowledge graphs to senior business and technology stakeholders, with a proven track record in sales and/or pre-sales and in delivering data transformation programs and developing teams


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Preferred Qualification
- Experience in Practical experience with NLP techniques and/or Search Techniques, prompt engineering
- Experience with LLMs for enterprise-scale applications.
- Hands-on experience with cloud platforms (AWS, Azure, GCP)
- Experience in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow)
- 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.
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