Data & Ai Architect (Riviere-des-Prairies—Pointe-aux-Trembles)

Data & AI ArchitectWe are seeking a Data & AI Architect to provide deep technical leadership across modern data and AI engagements. In this role, you will design, build, and guide implementation of enterprise‑grade data and AI solutions, ensuring architectural integrity, technical excellence, and successful delivery. You will work closely with senior architects, engineers, and delivery teams to create scalable platforms and AI systems that are both technically sound and aligned with client objectives. This is a hands‑on technical leadership role for someone who thrives in designing complex architectures, mentoring teams, and bridging across data, AI, and cloud technologies. Key ResponsibilitiesArchitecture Design & Technical Leadership Lead the architecture, design, and implementation of enterprise data and AI platforms using cloud-native and hybrid architectures. Define end‑to‑end architectures that span data ingestion, storage, processing, analytics, ML/AI, and governance. Establish architectural standards, patterns, and reference models for data modernization and AI enablement. Provide technical direction and mentorship to data engineers, ML engineers, and solution developers. Data Platform Engineering Design and oversee modern data platforms using technologies such as Databricks, Snowflake, Synapse, BigQuery, and Azure Data Lake. Define and implement data architectures (data lakehouse, mesh, fabric) optimized for performance, scalability, and governance. Lead data integration, pipeline automation, and orchestration using Spark, Data Factory, Glue, or equivalent tools. Guide teams on best practices in data quality, metadata management, and lineage. AI & Machine Learning Architecture Architect and implement machine learning and AI systems, including model training, deployment, monitoring, and lifecycle management. Apply MLOps and LLMOps principles to automate and scale ML/AI workloads. Design solutions leveraging Generative AI (LLMs, RAG, fine‑tuning) and Agentic AI frameworks for intelligent automation and decisioning. Integrate AI models with enterprise systems and APIs securely and efficiently. Cross-Technology Integration & Oversight Provide technical oversight across multiple technology domains: data engineering, cloud infrastructure, AI/ML, APIs, and security. Collaborate with infrastructure and cloud teams to ensure robust, secure, and compliant deployments. Lead troubleshooting and performance optimization for complex distributed systems. Innovation & Enablement Evaluate emerging tools and architectures in AI, data, and automation to continuously improve solutions and delivery approaches. Create reusable frameworks, accelerators, and best practices to enhance delivery efficiency. Mentor technical teams, fostering a culture of innovation, quality, and collaboration. Who You AreRequired Experience & Skills 8+ years of experience designing and implementing data and AI solutions in enterprise or consulting environments. Proven expertise building cloud‑native data platforms on Azure, AWS, or GCP. Strong hands‑on experience with: Data engineering: Spark, Databricks, Snowflake, Synapse, BigQuery, or Redshift. Data orchestration & integration: Airflow, Data Factory, Glue, or similar. ML/AI technologies: Python, TensorFlow, PyTorch, scikit‑learn, Azure ML, SageMaker, Vertex AI. Generative AI: LLM integration, RAG, vector databases (Pinecone, FAISS), prompt engineering. MLOps/LLMOps frameworks: MLflow, Kubeflow, or similar. Solid foundation in data architecture, governance, and security best practices. Demonstrated ability to lead or oversee technical delivery teams and ensure architectural consistency across projects. Excellent problem‑solving and collaboration skills, with the ability to work across disciplines and technologies. Preferred Qualifications Certifications in one or more cloud platforms (Azure Solutions Architect, AWS Data Analytics, or GCP Professional Data Engineer). Experience integrating data and AI platforms with enterprise applications and APIs. Knowledge of containerization and orchestration (Docker, Kubernetes). Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field. What You Can ExpectOur career path emphasizes growth and professional development. We provide hybrid-friendly culture, well‑being programs, and learning opportunities, including certifications across major tech vendors. You will work on impactful projects, receive continuous feedback, and have access to coaching and hands‑on experience to advance your career. #J-18808-Ljbffr Apply on Kit Job: kitjob.ca/job/2okljt