Lead Azure Data Scientist (AI/ML & Agentic AI)

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

• Bachelor's 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