Digital Catapult is seeking a talented and motivated Future Network Technologist to support the design, implementation, and delivery of AI-native observability and self-healing frameworks within the scope of advanced 6G research. The successful candidate will contribute to projects around AI for Networks, leveraging Large Language Models (LLMs) for automated monitoring, orchestration, and remediation in cloud-native, disaggregated telecom infrastructures to shape the next generation of intelligent, resilient networks.

This role involves designing, implementing, and deploying intelligent networking systems powered by large language models, intent-based automation, and cloud-native architectures. The candidate will collaborate with interdisciplinary experts in a fast-paced environment to help define future networks.

This is a 1-year contract.

Responsibilities

1. AI-Assisted Observability Development: Design and implement telemetry pipelines using Prometheus, OpenTelemetry, and Elastic. Ingest and analyze metrics, logs, and traces from CNFs, edge nodes, and service mesh environments.
2. LLM-Based Self-Healing Systems: Deploy and fine-tune open-source LLMs (e.g., LLaMA, Mistral) to detect anomalies and misconfigurations. Integrate with frameworks like LangChain for Retrieval-Augmented Generation (RAG) diagnostics. Translate AI outputs into executable Kubernetes remediation actions.
3. Platform Orchestration & Integration: Extend and integrate with Digital Catapult’s orchestration frameworks (e.g., CAMINO, ANEMOS). Design self-healing loops and automation flows aligned with ETSI ZSM and AI-native networking principles.
4. System Evaluation & Testbed Deployment: Use failure injection techniques in 6G testbeds to assess detection and resolution latency (e.g., MTTR). Benchmark against rule-based or static baselines.
5. Collaboration & Dissemination: Work with academic and industry partners (King’s College London, Hull, Brunel). Contribute to publications, reports, open-source projects, and community activities.

Minimum Qualifications

• Hands-on experience with machine learning, data preprocessing, and deploying/fine-tuning LLMs (Transformers, RAG, LangChain).
• Proficiency with Kubernetes, Docker, Helm, and observability tools like Prometheus, Grafana, OpenTelemetry.
• Strong Python skills (PyTorch, tokenization) and understanding of networking protocols (TCP/IP, HTTP).
• Knowledge of AI-driven, intent-based networking, service meshes, CNFs, and 5G/6G architectures (OpenRAN, RICs, DU/CU).
• Excellent communication skills, ability to work across disciplines, and thrive in innovative environments.

Application deadline: 8th August 2025.

Our Commitment

We value diversity and inclusion, welcoming applications from neurodivergent candidates, minorities, and those with varied experience. We guarantee interviews for disabled applicants meeting minimum criteria. We are an equal opportunities employer.