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AI Architect

Exclusive opportunity

Onsite

AI Architect

HCLTech

AI Architect

Skills

Google Cloud PlatformBig DataDeep LearningPythonData ScienceData VisualizationJavaPyTorchTensorFlowRKafkaData AnalysisMachine LearningAIAWSHadoopComplianceAzure

2 months ago

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Important information


Contract type:

Permanent

Salary:

CA$100,000 – CA$110,000 / year

Location:

Vancouver, BC, Canada

Work mode:

Onsite

Published on:

31 August 2026

What they need


JD for AI architect role.

Role Description:

  • This is a senior strategic and technical leadership role. Talent will convert business requirements into scalable and effective AI solutions. He will bridge the gap between complex business challenges and scalable, production-ready AI solutions.
  • Design end-to-end data workflows, choose appropriate model architectures, manage infrastructure costs, and govern the full ML lifecycle without getting bogged down in basic code implementation.
  • Involve in strategic planning, system design, algorithm development, and performance optimization to provide innovative AI solutions that satisfy company goals.

Key Responsibilities:

  • Architectural Design : Create blueprints for scalable AI applications, ensuring robust data pipelines and model deployment patterns.
  • Infrastructure & Platform Selection : Evaluate and select infrastructure frameworks, databases, and high-performance computing clusters.
  • ML Ops Governance : Own the deployment lifecycle, automated retraining pipelines, model observability, and validation.
  • Stakeholder Alignment : Collaborate closely with multiple stakeholders to translate business goals into technological maps.
  • Risk & Compliance : Enforce responsible AI practices, strict data privacy, and mitigation frameworks for bias or security vulnerabilities

Required Technical Skills:

  • Machine Learning and Deep Learning: Proficiency in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and model development.
  • Data Science: Strong foundation in data analysis, statistics, and data visualization techniques.
  • Programming: Expertise in programming languages such as Python, R, Java, and proficiency in using AI libraries and tools.
  • Cloud Computing: Knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI services.
  • Big Data Technologies: Familiarity with big data processing tools like Hadoop, Spark, and Kafka.

Experience Level : 10 to 15

  • years of total experience in technology, with at least 5+ years dedicated strictly to building and designing production-grade AI/ML applications.

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