AI LLM Engineer - Autonomous Network

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.

• 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 Lang Chain, Lang Graph, 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 Lang Chain, Lang Graph, Llama Index, Auto Gen, 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
• Lang Chain, Lang Graph, 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, Big Query or data engineering certification
• Kubernetes certification
• TM Forum Autonomous Networks or Open API certification

• Experience with Google Vertex AI, Gemini APIs, Big Query 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 still encourage you to apply; your unique experience could be just what we need.

• Exposure to top global companies working with Capgemini (145 of the Fortune 500 companies)
• Open access to digital learning platforms
• Active employee networks promoting diversity, equity and inclusion like Out…