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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Solutions Architect - AI and Core Networks - **Company:** CapGemini - **Location:** Oxford, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** 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, Feature Engineering, Large Language Models, Prompt Engineering, Caching, Generative AI, Kubernetes, Optimization Algorithms, Machine Learning Operations, Virtual Agents, Restful APIs, Open Network Automation Platform - **Published:** August 11, 2026 - **Apply:** https://jobsthamesvalley.co.uk/jobs/apply/ats-redirect/?id=2921092172-2 ## 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 This is a specialized role focused on designing and implementing autonomous network use-case solutions for mobile & fixed telecommunications environments, network programmability, APIs, scalable AI architectures, and token-efficient agentic systems using modern AI frameworks (Google Vertex AI or similar, LangGraph, LangChain)., * 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) ## Related Videos - [Your Next AI Needs 10,000 GPUs. 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