SR AI ENGINEER CONSULTANT II-INDIA

Lumen is the trusted network for the AI‑powered world, connecting people, data, and applications through our expansive fiber network and connected ecosystem. We enable secure, high‑performance connectivity across cloud, edge, and AI workloads for enterprises, governments, and communities. At Lumen, you’ll work on infrastructure customers rely on today and build for what’s next, where performance, security, and resilience matter. This is a high accountability environment where bold ideas drive real innovation for our customers, partners, and industry. The work is challenging, expectations are clear, and trust is built into how we operate. If you’re ready to take ownership, deliver meaningful impact, and help shape the future of AI‑ready connectivity, join us today. The Role 
 We are seeking a highly skilled Senior AI Engineer (P4-II) to design, develop, and deploy enterprise-scale Artificial Intelligence, Generative AI, and Agentic AI solutions. The ideal candidate will possess strong expertise in machine learning, large language models (LLMs), AI application engineering, cloud-native architectures, and MLOps practices. This role requires hands-on technical leadership, the ability to drive projects independently, mentor junior engineers, and collaborate with business stakeholders to translate business problems into scalable AI solutions. The Main Responsibilities 
 Key Responsibilities AI Solution Development Design, develop, and deploy AI/ML and Generative AI solutions for enterprise use cases. Build and optimize Retrieval Augmented Generation (RAG) applications. Develop Agentic AI workflows using frameworks such as LangGraph, CrewAI, Semantic Kernel, AutoGen, or equivalent. Create scalable AI APIs and microservices using Python and modern backend frameworks. Integrate AI capabilities into enterprise platforms and business applications. Machine Learning & Data Science Develop and deploy predictive models using supervised and unsupervised learning techniques. Perform feature engineering, model training, evaluation, and optimization. Build NLP, classification, recommendation, forecasting, and anomaly detection solutions. Implement model monitoring and performance measurement frameworks. Generative AI & LLM Engineering Work with Azure OpenAI, OpenAI, Gemini, Claude, Llama, and other foundation models. Design prompt engineering strategies and evaluation frameworks. Implement advanced RAG, GraphRAG, memory systems, and agent collaboration patterns. Fine-tune models when applicable and evaluate model quality, safety, and performance. Drive Responsible AI practices and governance requirements. Platform Engineering & MLOps Design AI deployment pipelines using CI/CD best practices. Implement MLOps and LLMOps frameworks for model lifecycle management. Build observability, logging, tracing, and performance monitoring capabilities. Optimize model costs and infrastructure utilization. Work with Kubernetes, Docker, and cloud-native deployments. Technical Leadership Mentor junior AI engineers and data scientists. Establish engineering standards, code quality practices, and reusable AI components. Collaborate with architects, product owners, and business stakeholders.   Mandatory Skills Programming Python (Expert) SQL REST APIs Git/GitHub AI & Machine Learning Machine Learning Deep Learning NLP LLMs Generative AI Prompt Engineering Agentic AI LangGraph CrewAI Semantic Kernel AutoGen Multi-Agent Architectures RAG Technologies Azure AI Search Vector Databases Knowledge Graphs Cloud Platforms Azure (Preferred) AWS GCP MLOps / LLMOps MLflow Azure ML Databricks CI/CD Pipelines Docker Kubernetes Data Platforms Databricks Spark Delta Lake Data Warehousing Concepts   Preferred Skills Microsoft Copilot Studio Enterprise Agent Platforms Shared Memory Architectures AI Governance & Compliance GraphRAG Implementations Knowledge Graphs Event-Driven Architectures API Gateway Integration OAuth & Security Frameworks What We Look For in