Job Title

Title Lead Azure Data Scientist (AI/ML & Agentic AI) Location Canada (Remote) Duration of the Contract Long Term Contract Client Industry Retail / Beauty / Consumer Goods Skills Required Azure, AI/ML, Agentic AI, LLMs, RAG, MCP (Model Context Protocol), Open Source LLMs, LLMOps, Databricks, Spark, Kafka, Scala, Python, SQL/NoSQL, Kubernetes, Deep Learning (PyTorch/TensorFlow), Real-time ML Systems, ONNX/TF Serving, Distributed Systems, Feature Stores, CI/CD Job Description We are seeking a Lead Azure Data Scientist with strong experience in AI/ML and Agentic AI systems to lead enterprise-scale AI initiatives. This role is ideal for a technology-agnostic polymath committed to continuous learning and passionate about delivering impactful AI/ML capabilities at scale. You will lead AI/ML engineering efforts, architect scalable solutions, mentor teams, and collaborate cross-functionally to drive innovation in a fast-paced, product-focused environment. Key Responsibilities Lead and execute enterprise-wide AI/ML solutions from ideation to production Architect, build, and maintain scalable, secure, and cost-efficient ML systems on Azure Design and implement end-to-end batch and real-time ML solutions with monitoring, logging, automated testing, performance testing, and A/B testing frameworks Develop and operationalize LLM-based systems including Agentic AI workflows, RAG architectures, and MCP-based integrations Implement LLMOps best practices using open-source LLMs and cloud-native tooling Collaborate with Product, Engineering, Data Science, and Business teams to define and deliver AI capabilities Establish scalable and automated processes for data analysis, model development, validation, deployment, and monitoring Write efficient, production-grade software in iterative release environments Conduct code reviews and enforce best practices in software engineering and ML lifecycle management Prioritize epics and manage dependencies while proactively mitigating risks and blockers Mentor engineers and data scientists in production ML best practices and foster a culture of collaboration and knowledge sharing Contribute to engineering strategy and product roadmap development Identify opportunities to optimize business processes and enhance consumer experiences using AI-driven solutions Required Qualifications Bachelors or Advanced Degree in Engineering, Computer Science, Mathematics, or related field 5+ years of experience developing and deploying ML systems into production 8+ years of experience in Software Engineering Hands-on experience with Agentic AI systems, LLMs, and Retrieval-Augmented Generation (RAG) architectures Experience working with MCP (Model Context Protocol) Strong experience with open-source LLMs and LLMOps frameworks Proficiency with Azure cloud services and designing scalable, fault-tolerant systems Hands-on experience with Azure Databricks Experience working with Claude and other LLM platforms Strong programming skills in Python, Scala, Java, or C++ Experience with Spark, Kafka, relational and NoSQL databases Hands-on experience with PyTorch, TensorFlow, Keras, or similar deep learning frameworks Experience building and operationalizing feature stores Experience designing distributed systems, APIs, and service-oriented architectures Experience deploying real-time ML systems using ONNX, MLEAP, TF Serving, or similar frameworks Familiarity with data pipeline and workflow orchestration tools Strong knowledge of CI/CD, unit testing, automated testing, and code reviews Experience with Kubernetes