Senior Data Engineer (AI & LLM Solutions)

Senior Data Engineer (AI & LLM Solutions) Location: Remote(Pakistan, Mexico, India, Morocco) Department: Digital Solutions / Data Engineering & AI Reports To: Technical Lead / Director Job Type: Full-time About AIM Architecture in Motion Inc. (AIM) is a Canadian technology consulting firm that supports organizations across public and private sectors with software engineering, cloud platforms, API integration, data engineering, and enterprise technology solutions. We specialize in delivering scalable, secure, and modern digital solutions leveraging Microsoft technologies, helping our clients drive operational efficiency, data modernization, and digital transformation. Role Overview AIM is seeking a Senior Data Engineer (AI & LLM Solutions) to design, develop, and optimize modern data platforms that support analytics, artificial intelligence, machine learning, and Generative AI solutions. This is a hands-on senior role requiring strong expertise in Microsoft Fabric, Azure Data Services, Azure Databricks, Python, PySpark, and enterprise data architecture, along with practical experience supporting AI and LLM initiatives. The ideal candidate will build scalable and secure data solutions while enabling advanced AI capabilities, including Retrieval-Augmented Generation (RAG), vector search, Azure OpenAI, Copilot, and enterprise LLM solutions. The successful candidate will work closely with Solution Architects, AI Engineers, Cloud Engineers, Data Scientists, and client stakeholders to deliver secure, scalable, and business-driven data platforms. Key Responsibilities Modern Data Platform Development • Design and develop enterprise-scale data solutions using Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and Azure Databricks. • Build and optimize scalable ETL/ELT pipelines for structured, semi-structured, and unstructured data. • Develop modern Lakehouse, Data Warehouse, and Medallion Architecture solutions. • Design and implement batch and real-time data processing frameworks. • Lead data modernization, migration, and integration initiatives from legacy platforms. AI, LLM & Data Enablement • Develop data foundations that support AI, Machine Learning, and Generative AI solutions. • Prepare, transform, and optimize datasets for AI applications, model training, and fine-tuning. • Design and implement Retrieval-Augmented Generation (RAG) architectures and vector search solutions. • Support Azure OpenAI, Microsoft Copilot, and enterprise LLM implementations. • Develop data pipelines and architectures that enable AI-driven applications. • Collaborate with Data Scientists and AI Engineers to operationalize AI and machine learning solutions. Advanced Data Engineering • Build distributed data processing solutions using PySpark and Spark SQL. • Develop automated data integration frameworks connecting APIs, SaaS applications, databases, and cloud services. • Design reusable data engineering frameworks, components, and standards. • Optimize large-scale workloads for performance, scalability, reliability, and cost efficiency. • Implement data quality, validation, monitoring, and error-handling processes. Data Governance & Security • Implement data governance and cataloging solutions using Microsoft Purview and related technologies. • Establish and maintain data lineage, classification, cataloging, and access controls. • Ensure data platforms align with enterprise security, privacy, and compliance requirements. • Support governance and security requirements across frameworks such as SOC 2, NIST, and CMMC. • Implement secure data access and protection practices across cloud data platforms. Reporting & Analytics Support • Design and support semantic data models for Power BI and enterprise analytics. • Enable self-service analytics while maintaining appropriate governance and data quality standards. • Support KPI frameworks, executive dashboards, reporting, and predictive analytics initiatives. • Collaborate with analytics teams to ensure reliable and high-quality data availability. Technical Leadership & Collaboration • Provide technical guidance and mentorship to junior and mid-level data engineers. • Participate in solution architecture, technical design reviews, and implementation planning. • Work directly with clients and stakeholders to understand requirements and translate business needs into scalable technical solutions. • Collaborate with cross-functional teams including AI Engineers, Cloud Engineers, Solution Architects, Data Scientists, and Business Analysts. • Participate in technical discussions and presales activities where required. • Develop technical documentation, engineering standards, and reusable implementation patterns. Support & Continuous Improvement • Troubleshoot and resolve data pipeline, platform, and integration issues. • Monitor and optimize data workloads and cloud resources. • Support enhancements, upgrades, ...