HCLTech
AI Architect
Skills
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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