Senior AI LLM Consultant - Autonomous Networks

Capgemini; Newbury; Hybrid; GBP 70,000 - 100,000; Full time

Benefits offered by this job

Hybrid working model

Disability Confident Employer (UK)

Job summary

Capgemini is recruiting an AI/ML Engineer to design and build the AI brain for autonomous network operations at a Capgemini location in Newbury. You will develop LLM-based agents, RAG systems, and multi-agent workflows, leveraging semantic search, graph-aware reasoning, and KPI models.

You will deploy AI services via Kubernetes/Docker, optimise prompts, and ensure secure, auditable workflows while improving latency and cost efficiency across data pipelines and OSS integrations.

Qualifications

• Experience in AI/ML engineering or related field.
• Hands-on with LLMs, RAG, semantic search, or agentic AI systems.
• Strong Python programming skills.
• Experience with LangChain, LangGraph, MCP, or similar frameworks.
• Vector databases and graph databases knowledge.
• Data pipelines integrating structured/unstructured data.
• Understanding of AIOps and telecom network operations.
• Experience deploying AI services with Kubernetes and Docker.

Responsibilities

• Design and develop LLM-based AI solutions for autonomous network operations.
• Build RAG frameworks using network data and KPIs.
• Develop multi-agent workflows and semantic retrieval systems.
• Implement vector search, graph-enhanced retrieval, and hybrid search.
• Create AI agents for diagnosis, KPI analysis, and incident summarisation.
• Optimize prompts, context, caching, and response generation.
• Integrate LLM solutions with OSS, inventory, graph/vector DBs, and pipelines.
• Collaborate with security teams to ensure safe AI workflows.

Skills

Python

ML basics

Deep learning

LLMs & transformers

LangChain / LangGraph

Vector databases

Graph APIs / knowledge graphs

Data pipelines

Docker & Kubernetes

Prompt engineering

Tools

LangChain

LangGraph

MCP

LlamaIndex

Job description

## **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*** 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.## **Your Profile*** 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.**Required Technical Skills*** 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.**Preferred Certifications*** 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.**Nice-to-Have Qualifications*** Experience with Google Vertex AI, Gemini APIs, BigQuery, or equivalent platforms.* Experience with telecom network data including RAN, Core, IP/MPLS, SD-WAN, OSS, alarms, KPIs, and inventory.* Experience developing LLM agents for network operations, incident management, or service assurance.* Experience with AI model optimisation, inference cost reduction, latency optimisation, and scalable AI serving.If you're excited about this role but don’t meet every requirement, we stillencourage you to apply, your unique experience could be just what we need.## **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@CapgeminiCapgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government’s Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who:* Declare they have a disability, and * Meet the minimum essential criteria for the role.* Please opt in during the application process.Capgemini. Make it real.## **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.