Autonomous Network AI Architect (Hybrid)

Capgemini Engineering; England; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Capgemini Engineering is seeking a specialist to design and implement autonomous network use-case solutions for mobile and fixed telecom environments. The role emphasizes network programmability, APIs, scalable AI architectures, and token-efficient agentic systems using modern AI frameworks.

You will work on hands-on network automation, RAG systems, vector DBs, and semantic search, with a focus on reducing computational overhead while maintaining decision accuracy.

Qualifications

• Experience in telecom/mobile network architecture with hands-on autonomous use cases.
• Proven network programmability expertise with REST APIs and YANG models.
• Programming in Python or Go for network automation and data tasks.
• Familiarity with NETCONF/RESTCONF, gRPC and modern API technologies.
• Track record in self-optimizing/self-healing networks and autonomous use cases.
• Experience implementing RAG systems, data fusion, and entity mapping.
• Knowledge of vector DBs and semantic search for AI agents.
• Exposure to cloud AI platforms (Vertex AI or equivalent) and LangChain tooling.
• Strong understanding of graph databases for topology and context management.
• Awareness of telemetry optimization, caching, and context window strategies.

Skills

Telecom network architecture

Network Programmability

RESTful APIs

YANG models

Python/Go

NETCONF/RESTCONF

gRPC

Autonomous Networks

RAG systems

Vector databases

LangChain/LangGraph

Token optimization for LLM

Graph databases

Kubernetes

Semantic search

Tools

Google Vertex AI

Pinecone

Weaviate

Milvus

Qdrant

ChromaDB

BigQuery

LangChain

LangGraph

Job description

Capgemini Engineering is seeking a specialist to design and implement autonomous network use-case solutions for mobile and fixed telecom environments. The role emphasizes network programmability, APIs, scalable AI architectures, and token-efficient agentic systems using modern AI frameworks.

You will work on hands-on network automation, RAG systems, vector DBs, and semantic search, with a focus on reducing computational overhead while maintaining decision accuracy.