Job Title: Senior Data/Machine Learning Engineer Location: Bogotá IDT Corporation is an American telecommunications company founded in 1990 and headquartered in New Jersey. Today, it is an industry leader in prepaid communication and payment services and one of the world's largest international voice carriers. We are looking for a skilled Data/ML Engineer to join our Business Intelligence team and take an active role in designing, building, and maintaining the end-to-end data pipeline, architecture, and design that powers our warehouse, LLM-driven applications, and AI-based Business Intelligence. Responsibilities: - Design, develop, and maintain scalable data pipelines to support ingestion, transformation, and delivery into centralized feature stores, model-training workflows, and real-time inference services. - Build and optimize workflows for extracting, storing, and retrieving semantic representations of unstructured data to enable advanced search and retrieval patterns. - Architect and implement lightweight analytics and dashboarding solutions that deliver natural language query experience and AI-backed insights. - Define and execute processes for managing prompt engineering techniques, orchestration flows, and model fine-tuning routines to power conversational interfaces. - Oversee vector data stores and develop efficient indexing methodologies to support retrieval-augmented generation (RAG) workflows. - Partner with data stakeholders to gather requirements for language-model initiatives and translate into scalable solutions. - Create and maintain comprehensive documentation for all data processes, workflows, and model deployment routines. Requirements: - 8+ years of experience as a Data Engineer with 2+ years focused on MLOps. - Excellent English communication skills. - Effective oral and written communication skills with the BI team and user community. - Demonstrated experience in utilizing Python for data engineering tasks, including transformation, advanced data manipulation, and large-scale data processing. - Deep understanding of vector databases and RAG architectures, and how they drive semantic retrieval workflows. - Skilled at integrating open-source LLM frameworks into data engineering workflows for end-to-end model training, customization, and scalable inference. - Experience with cloud platforms like AWS or Azure Machine Learning for managed LLM deployments. - Hands-on experience with big data technologies including Apache Spark, Hadoop, and Kafka for distributed processing and real-time data ingestion. - Experience designing complex data pipelines extracting data from RDBMS, JSON, API, and Flat file sources. - Demonstrated skills in SQL and PLSQL programming, with advanced mastery in Business Intelligence and data warehouse methodologies, along with hands-on experience in one or more relational database systems and cloud-based database services such as Snowflake/Redshift. - Understanding of software engineering principles and skills working on Unix/Linux/Windows Operating systems, and experience with Agile methodologies. - Proficiency in version control systems, with experience in managing code repositories, branching, merging, and collaborating within a distributed development environment.