Senior Design Engineer – AI / LLM / RAG Platform
Role Summary
- Design and build AI-powered Service Assurance solutions for telecom operations.
- Develop LLM, RAG, and Agentic AI capabilities to automate troubleshooting, RCA, and operational workflows.
- Build production-grade Python services and AI platforms that support autonomous network operations.
Key Responsibilities
AI / GenAI
- Design and develop LLM-powered operational assistants and copilots.
- Build and optimise RAG pipelines using enterprise knowledge, alarms, KPIs, logs, tickets, and documentation.
- Develop Agentic AI workflows for RCA, alarm analysis, incident triage, and recommendation generation.
- Implement prompt engineering, embeddings, semantic search, and response evaluation.
- Improve AI accuracy, grounding, and explainability.
Python Engineering
- Develop scalable backend services using Python.
- Build APIs and microservices using FastAPI/Flask.
- Create automation pipelines for data ingestion, analysis, and AI orchestration.
- Deliver production-quality, maintainable, and testable code.
Cloud & Platform
- Develop and deploy applications on Kubernetes/OpenShift.
- Work with containerised microservices and cloud-native architectures.
- Implement observability, monitoring, logging, and CI/CD integration.
Telecom Service Assurance
- Apply AI to alarm correlation, KPI analytics, RCA, and incident management.
- Work with OSS, FM/PM systems, topology, inventory, alarms, logs, and telemetry data.
- Collaborate with telecom SMEs to convert domain knowledge into AI playbooks and workflows.
Job Requirements
Experience
- 4-8 years of software/platform engineering experience.
- 1-3 years of hands-on experience in GenAI, LLM, RAG, AI Assistants, or Agentic AI solutions.
Mandatory Skills
Programming
- Python (Expert Level)
- REST APIs
- FastAPI / Flask
- Microservices Architecture
- Git & CI/CD
AI / LLM
- Large Language Models (LLMs)
- RAG Architecture
- Prompt Engineering
- Vector Databases
- Embeddings
- Semantic Search
- AI Evaluation & Guardrails
AI Frameworks
- LangChain
- LangGraph
- LlamaIndex
- Semantic Kernel
- Azure OpenAI / OpenAI APIs
- Hugging Face
Cloud Native
- Docker
- Kubernetes
- OpenShift
Preferred Skills
- Telecom domain knowledge (4G/5G/IMS/OSS).
- Knowledge Graphs.
- AI-driven root cause analysis.
- AIOps and observability platforms.
- Multi-Agent AI systems.
- Incident management and service assurance.
Ideal Candidate
- Strong Python developer with hands-on LLM/RAG implementation experience.
- Has built real-world AI copilots, chatbots, or knowledge assistants.
- Can design end-to-end AI solutions rather than only consume AI APIs.
- Comfortable handling telecom operational data such as alarms, logs, KPIs, and tickets.
- Able to mentor junior engineers and drive technical architecture decisions.
