Lead AI/ML Solutions Architect & Data Engineer

Are you a visionary technologist who loves shaping high-level AI strategies but still gets excited about writing production-grade code and deploying models? We are looking for a Lead AI/ML Solutions Architect & Data Engineer to bridge the gap between business strategy and cutting-edge technical execution.In this role, you won't just draw architectures on a whiteboard—you will actively build, govern, and scale them. You will design enterprise-grade AI/ML architectures, establish robust data governance, implement MLOps pipelines, and write the core code that powers our advanced analytics engine.Key ResponsibilitiesAI/ML Solution Architecture: Design, build, and deploy scalable, secure, and high-performance AI/ML architectures. Turn complex business problems into robust technical solutions.Hands-on Development: Actively write clean, maintainable, and optimized code using Python, SQL, and R to develop data pipelines, statistical models, and machine learning algorithms.Technology & Data Strategy: Define the long-term technology roadmap for our data and AI initiatives. Evaluate emerging tools, frameworks, and cloud capabilities to keep our stack ahead of the curve.Data Strategy & Governance: Establish and enforce framework standards for data quality, privacy, security, and compliance. Ensure our data assets are organized, accessible, and structured for advanced analytics.Data Science & Advanced Analytics: Apply advanced statistical modeling, data mining, and machine learning techniques to uncover deep insights and drive automated decision-making.MLOps & Model Lifecycle Management: Build and manage end-to-end MLOps pipelines. Oversee the entire model lifecycle—from data ingestion and training to deployment, monitoring, CI/CD automation, and retraining.Cloud Infrastructure (Azure Databricks): Serve as the hands-on expert for our Azure Databricks environment, optimizing workspace configurations, managing Delta Lake architectures, and ensuring efficient compute utilization.Required Skills & QualificationsExperience: 6+ years of experience in Data Engineering, Data Science, or Solution Architecture, with at least 2+ years in a hands-on architectural or lead role.Core Technical Stack: Mastery of Python and SQL is required; strong proficiency in R for statistical modeling is highly preferred.Platform Expertise: Deep, hands-on experience building and optimizing pipelines within Azure Databricks (including Delta Lake, MLflow, and Spark).MLOps Mastery: Proven track record of implementing MLOps frameworks (e.g., MLflow, Azure Machine Learning, Kubeflow) to manage model drift, versioning, and deployment.Strategic Thinking: Strong understanding of data governance principles (lineage, metadata management, security) and the ability to align technical design with business outcomes.Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Information Systems, or a related quantitative field.If you have a background as one or more of these (Principal Architect - AI & Data Engineering, Enterprise Data & Machine Learning Architect, Director of AI/ML Architecture (Hands-on), Technology Strategy Architect – Data & AI, Principal AI/ML Engineer, MLOps Architect & Data Infrastructure Lead, Lead Azure Databricks Engineer & Solutions Architect, Senior Data Science Architect & Engineer, Lead AI/ML Governance & Solutions Architect, Head of Model Lifecycle Management & Data Strategy, Director of Data Strategy, Analytics & Governance), we would love to see your application!