Senior AI / ML Engineer (Cloud, GenAI & Analytics)

Key Responsibilities

AI / ML & Generative AI (Primary)

• Design, build, and deploy enterprise-grade AI / ML solutions using: Machine Learning, Deep Learning, NLP, LLMs, Generative AI
• Develop and operationalize end-to-end ML pipelines including: Feature engineering, Training Deployment, Monitoring
• Build and optimize LLM-based architectures including: Prompt engineering, Retrieval-Augmented Generation (RAG), Production inference workflows
• Lead AI experimentation and rapid prototyping to solve business problems.
• Implement MLOps, CI/CD, governance, observability, and security best practices.

Data Engineering & Analytics (Secondary)

• Design scalable data pipelines supporting AI and analytics use cases.
• Build and manage cloud data platforms using Snowflake.
• Develop ETL / ELT pipelines using: Azure Data Factory (ADF), Equivalent tools
• Create dashboards and analytical reporting using: Power BI, Tableau
• Ensure data quality, reliability, and performance.

Must Haves

• 7+ years of experience in AI / ML / Data Engineering / GenAI.
• 5+ years Telecom domain experience required.
• Strong Python programming skills for AI / ML development.
• Hands-on expertise in: AI / ML, Deep Learning, NLP, LLMs, Generative AI
• Proven experience delivering production-grade AI solutions.
• Strong experience with: Cloud platforms (Azure preferred), Snowflake, ADF or equivalent ETL tools
• Knowledge of: CI/CD, DevOps, Model deployment pipelines

Nice to Have:

• Experience with: MLOps, Model monitoring, Observability tools
• Familiarity with: Vector databases, Embeddings, RAG frameworks
• Experience integrating LLMs into enterprise systems.
• Large-scale telecom or enterprise data experience.
• Agile delivery environment experience.