> Markdown version of [/jobs/ext/4679565-autonomous-network-ai-architect-telecom](https://www.wearedevelopers.com/jobs/ext/4679565-autonomous-network-ai-architect-telecom). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Autonomous Network & AI Architect (Telecom)

- **Company:** Capgemini
- **Location:** Abingdon, United Kingdom
- **Salary:** £69,694
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, BigQuery, Extract Transform Load (ETL), Distributed Systems, Entity Relationship Models, Graph Database, Network Topologies, Python (Programming Language), Netconf, Cloud Services, Search Technologies, Data Streaming, Wireless Networks, Pinecone, Qdrant, Feature Engineering, LangChain, Retrieval-Augmented Generation, Transfer Learning, Large Language Models, Prompt Engineering, Google Vertex AI, Llamaindex, Caching, Generative AI, Agentic-AI, Kubernetes, Weaviate, AutoGen, Milvus, Machine Learning Operations, Google Gemini, Restful APIs, Open Network Automation Platform, ChromaDB
- **Published:** November 12, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5962144910

## About the Role

* Experience in telecom/mobile network architecture including hands-on experience developing and deploying autonomous network use cases, * TM Forum Open API Certification (at least one domain: RAN, Core, OSS, etc.)
 * TM Forum Autonomous Network Practitioner certification (or equivalent)
 * Or equivalent advanced TMForum training in DigitalOps and Autonomous Networks

Nice-to-Have Qualifications

 * Experience with Generative AI frameworks (LangChain, LangGraph, LlamaIndex, AutoGen)
 * Exposure to Google Vertex AI or similar cloud solutions, Gemini APIs, BigQuery or similar platforms
 * Knowledge of network telemetry optimization (gRPC telemetry, streaming telemetry)
 * Knowledge of distributed systems and Kubernetes-based deployments

## Description

* RESTful APIs and YANG models
 * Python, Go, or similar languages for network automation
 * NETCONF/RESTCONF protocols
 * gRPC and other modern APIs

Autonomous Networks:

 * Demonstrated expertise in self-optimizing/self-healing network implementations
 * Portfolio of successful autonomous network use cases

Agentic AI & Data Optimization:

 * Data correlation and entity relationship mapping
 * Data quality assessment and cleansing methodologies
 * Token optimization techniques for LLM-based agents
 * Resource-constrained AI model deployment
 * Vector databases and semantic search (e.g., Pinecone, Weaviate, Milvus, Qdrant, and ChromaDB)
 * Prompt engineering for efficient agent reasoning
 * LLM fine-tuning and instruction optimization
 * Graph databases for network topology and context management
 * Feature engineering for network telemetry
 * ETL pipeline design for real-time network data
 * Caching strategies (semantic, temporal, hierarchical)
 * Context window optimization techniques

 * Experience implementing RAG systems or retrieval frameworks
 * Demonstrated expertise in relevant use-case development:
 * Experience reducing computational overhead while maintaining decision accuracy in AI systems
 * Portfolio demonstrating optimized agentic implementations (inference cost reduction, latency improvements)