AI LLM Engineer - Autonomous Network
Added 15 Jul · still live
Not disclosed
Salary
Not disclosed by employer
£54,700
Going rate
Skilled Worker going rate
This role likely qualifies for a Skilled Worker visa
SOC 2134 (90% match) is an eligible occupation, with a going rate of £54,700, and Capgemini is a licensed sponsor. That is our reading of the rules. Whether they issue a Certificate of Sponsorship is still their call.
About the role
Your Role
This role focuses on designing and building the AI brain for autonomous network operations. The AI / LLM Engineer will develop LLM-based agents, RAG systems, multi-agent workflows, semantic search, graph-enhanced reasoning, predictive analytics, KPI models, fault correlation models, and closed-loop decision support capabilities.
Key Responsibilities
This role focuses on designing and building the AI brain for autonomous network operations. The AI / LLM Engineer will develop LLM-based agents, RAG systems, multi-agent workflows, semantic search, graph-enhanced reasoning, predictive analytics, KPI models, fault correlation models, and closed-loop decision support capabilities.
Key Responsibilities
- Design and develop LLM-based and agentic AI solutions for autonomous network operations.
- Build RAG frameworks using network documentation, alarms, topology, inventory, KPIs, trouble tickets, procedures, configuration data, and operational knowledge.
- Develop multi-agent workflows using LangChain, LangGraph, MCP, or similar frameworks.
- Implement vector search, semantic retrieval, graph-enhanced retrieval, and hybrid search patterns.
- Develop AI agents for fault diagnosis, root-cause analysis, KPI analysis, configuration recommendation, incident summarisation, and operational decision support.
- Build token-efficient prompting, context optimisation, caching, and response generation techniques.
- Integrate LLM solutions with OSS, AIOps, inventory, graph databases, vector databases, data pipelines, and automation platforms.
- Develop fault correlation, KPI modelling, predictive analytics, and closed-loop trigger logic.
- Implement safe AI workflows with human-in-the-loop approval, confidence scoring, explainability, and auditability.
- Optimise AI models and agent workflows for latency, cost, accuracy, and reliability.
- Support model evaluation, prompt evaluation, hallucination reduction, retrieval quality improvement, and grounding validation.
- Work with cybersecurity teams to implement LLM security, prompt injection protection, data leakage prevention, and access controls.
- Deploy AI services using Kubernetes, Docker, APIs, and cloud-native patterns.
- Experience in AI/ML engineering, data engineering, software engineering, or applied machine learning.
- Hands-on experience with LLMs, RAG, semantic search, or agentic AI systems.
- Strong Python programming skills.
- Experience with ML fundamentals, deep learning concepts, embeddings, transformers, and LLM architectures.
- Experience using LangChain, LangGraph, LlamaIndex, AutoGen, MCP, or similar AI frameworks.
- Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, ChromaDB, or equivalent.
- Experience with graph databases, knowledge graphs, or Graph APIs.
- Experience building data pipelines and integrating structured and unstructured data sources.
- Understanding of AIOps, fault correlation, KPI modelling, predictive analytics, or telecom network operations.
- Experience deploying AI services using Kubernetes, Docker, APIs, and cloud-native environments.
- Python.
- ML basics and deep learning.
- LLMs and transformers.
- LangChain, LangGraph, MCP, or similar frameworks.
- Vector databases and semantic search.
- Graph APIs and knowledge graphs.
- Data pipelines and data aggregation.
- Docker and Kubernetes.
- Fault correlation and KPI modelling.
- Predictive analytics and AIOps.
- Closed-loop triggers.
- Prompt engineering and context optimisation.
- AI observability and evaluation.
- Google Cloud AI/ML or Vertex AI certification.
- Azure AI Engineer or AWS Machine Learning certification.
- Databricks, BigQuery, or data engineering certification.
- Kubernetes certification.
- TM Forum Autonomous Networks or Open API certification.
- Experience with Google Vertex AI, Gemini APIs, BigQuery, or equivalent platforms.
Make it real – what does it mean for you?
- Exposure to top global companies working withCapgemini (145 of the Fortune 500 companies)
- Open access to digital learning platforms
- Active employee networks promoting diversity, equity and inclusion like OutFront, CapAbility or Women@Capgemini
- Declare they have a disability, and
- Meet the minimum essential criteria for the role.
- Please opt in during the application process.
Need to know
- All roles will require a level of security clearance; BPSS OR Security Clearance OR Developed Vetting.
- Location: This is a permanent role with Capgemini, offering a hybrid working model. The client is based in Newbury and occasional travel to the client site will be required.
- You can bring your whole self to work. At Capgemini building an inclusivefuture is part of everyday life and will be part of your working reality. We havebuilt a representative and welcoming environment, for everyone.
Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 202
5 global revenues of €22.5 billion.
Make it real | www.capgemini.com
Make it real | www.capgemini.com
This description is the source posting as it read when we added it. We are not affiliated with Capgemini, so check their own site for the current details.
Where this offer sits in the market
SOC 2134 · UK · ONS ASHE 2025 · ~343k in sampleP25 £42kP75 £76k
£33kmedian £57kgoing rate £55k£103k
Similar sponsored roles
See all UK visa jobsNo close matches live right now.
Browse more sponsored jobs at CapgeminiAbout sponsorship for this role
Does this job guarantee visa sponsorship?
Not necessarily. Capgemini holds a sponsor licence, but sponsorship for a specific hire is always the employer's decision. Be upfront in your application that you'll require it.
What salary is needed for this role to be eligible?
The offer must clear both the general threshold and the SOC 2134 going rate of £54,700. New-entrant and shortage discounts can lower it.