GM - IT Analytics

Position Overview

Vodafone Idea is seeking an experienced AI Architect to design, develop, and scale advanced AI and Generative AI solutions for enterprise use. This role involves shaping the technical framework and roadmap for AI systems operated on the Cloudera Data Platform (CDP versions 7.1.9 and 7.3.1). The ideal professional will connect complex big data environments with state-of-the-art machine learning and large language model workflows. Key expertise includes model selection, lifecycle management, prompt engineering, and integration of MLOps/AIOps practices within contemporary DevOps setups.

Key Responsibilities

• Lead comprehensive design and integration of Predictive AI and Generative AI applications leveraging CDP infrastructure.
• Develop efficient, low-latency data pipelines and feature stores using CDP tools such as Spark, Hive, Impala, Kafka, and Apache Iceberg.
• Create frameworks for retrieval-augmented generation, fine-tuning strategies, and vector search systems linked to enterprise big data assets.
• Assess and pick appropriate foundational models—including LLMs, SLMs, and both open-source and proprietary options—and traditional machine learning techniques for telecom-related challenges like customer churn, network optimization, personalization, and fraud detection.
• Implement AI governance including model drift monitoring, explainability, bias mitigation, privacy, and regulatory compliance.
• Administer model registries, versioning, and policy enforcement over various runtime conditions.
• Develop standardized prompt engineering practices, managing context windows and agent workflows (e.g., LangChain, LlamaIndex, AutoGen).
• Enhance token efficiency, reduce latency, improve throughput, and optimize inference cost for LLM operations.
• Deploy safety mechanisms such as guardrails, output validations, and filters to minimize hallucinations, data leaks, and security vulnerabilities in LLM communications.
• Design and operate resilient MLOps and AIOps pipelines for automated model lifecycle processes including training, CI/CD/CT, deployment, and monitoring.
• Collaborate with DevOps teams to launch containerized AI microservices via Kubernetes and Docker on hybrid or on-premises setups.
• Set up monitoring, logging, and observability using tools like Prometheus, Grafana, MLflow, and Weights & Biases to ensure operational excellence.

Required Qualifications & Experience

• Bachelor’s or Master’s in Computer Science, Data Science, AI or related quantitative disciplines.
• Minimum 10 years’ experience in Data Science or Software Engineering with at least 4 years as an AI/ML Architect managing enterprise-scale systems.
• Extensive hands-on experience with Cloudera Data Platform (CDP 7.1.9/7.3.1), PySpark, HDFS, Hive, and Impala.
• Proven skill in developing, fine-tuning, and deploying LLMs, RAG architectures, multi-agent frameworks, and standard ML models.
• Strong background in MLOps and AI governance including MLflow, model registries, feature stores, drift monitoring, and AI ethical frameworks.
• Proficient in DevOps tools such as Docker, Kubernetes, Jenkins, GitLab CI, GitHub Actions, Terraform, Ansible, and Git workflows.
• Advanced programming in Python, PySpark, SQL, and bash scripting.
• Familiarity with AI/ML frameworks like PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, vLLM, and Triton Server.

Preferred Qualifications

Previous experience in the Telecom or Communication Service Provider sector managing large volumes of subscriber and network event data is highly desirable.