Total Exp : 8 to 12 Years
Location : Delhi / NCR Region
Key Responsibilities
GenAI Solution Development
- Design and implement GenAI-based applications for telecom network domains (e.G., NOC copilots, automated RCA assistants, network testing script generators).
- Build and fine-tune domain-specific LLMs and prompt libraries for telecom operations, planning, and assurance.
- Develop RAG (Retrieval-Augmented Generation) pipelines integrating GenAI with OSS / BSS, network data, and knowledge bases.
- AI / ML Engineering
- Collaborate with data engineers to build telecom-specific feature stores and data pipelines.
- Train ML models for predictive maintenance, anomaly detection, KPI forecasting, and integrate them with GenAI workflows.
- Optimize models for low-latency inference in real-time network environments.
Telecom Domain Collaboration
Work with SMEs from Wireless, Transport, Cloud, and Core to contextualize GenAI solutions for network challenges.Translate domain requirements into AI / GenAI workflows (e.G., “alarm storm reduction assistant,” “energy optimization recommender”).Develop APIs, microservices, or integration layers with OSS / BSS, orchestration, and ITSM platforms.Innovation & Delivery
Contribute to building the AI / GenAI Practice Team IP (prompt repositories, reusable GenAI frameworks).Evaluate emerging GenAI models and tools for relevance to telecom (e.G., LLaMA, GPT, Claude, Gemini, Mistral).Support pre-sales, PoCs, and client workshops to showcase GenAI use cases in telecom networks.Required Skills & Experience
Core Technical Skills
Strong hands-on experience with GenAI frameworks : LangChain, LlamaIndex, HuggingFace Transformers, RAG implementations.Proficiency in Python (must-have), with experience in building APIs / microservices (FastAPI / Flask / Django).Knowledge of Vector Databases (Pinecone, Weaviate, Milvus, FAISS).Cloud experience with Azure OpenAI, AWS Bedrock, or GCP Vertex AI.Experience in fine-tuning / few-shot prompting for LLMs.Familiarity with MLOps / LLMOps pipelines (MLflow, Kubeflow, or equivalent).Telecom Network Skills
Understanding of OSS / BSS systems and telecom network data flows.Exposure to domains such as RAN KPIs, Transport performance, Fault / Event / Alarm management, Network Planning, Telco Cloud orchestration.Experience in applying AI / ML to telecom datasets (KPI prediction, anomaly detection, alarm correlation, capacity planning).Professional Skills
Strong problem-solving mindset with ability to design domain-aware GenAI solutions.Experience in client-facing roles (workshops, solutioning, PoC presentations).Ability to collaborate with cross-functional teams (data engineers, network SMEs, cloud architects).Good communication skills with ability to simplify complex AI concepts for business stakeholders.Qualifications
Bachelor’s or Master’s degree in Computer Science, Telecommunications, Data Science, or related field.Certifications in AI / ML, Cloud (Azure / AWS / GCP), or Telecom (TM Forum, 5G, Open RAN) preferred.