AI Architect

HCLTech; Vancouver; On-site; CAD 180,000 - 260,000; Full time

Job summary

HCLTech in Canada seeks a senior AI/ML architect and leader to translate business challenges into scalable, production-ready AI solutions. You will design end-to-end data workflows, select infrastructure, govern the ML lifecycle, and align with stakeholders to meet strategic goals.

Lead architecture decisions, manage cost-efficient platforms, ensure responsible AI practices and compliance, and drive innovative analytics across the organization with 10–15+ years in tech and 5+ years in production

Qualifications

• 10–15+ years in technology and AI/ML field.
• At least 5+ years building production-grade AI/ML applications.

Responsibilities

• Architectural Design: Create blueprints for scalable AI applications with robust data pipelines.
• Infrastructure & Platform Selection: Evaluate infra frameworks, databases, and HPC clusters.
• ML Ops Governance: Own deployment lifecycle, retraining pipelines, observability, and validation.
• Stakeholder Alignment: Translate business goals into technological maps with stakeholders.
• Risk & Compliance: Enforce responsible AI, data privacy, bias, and security measures.

Skills

ML & DL

Data Science

Programming (Python/R/Java)

Cloud Computing

Big Data Tools

Tools

TensorFlow

PyTorch

AI libraries & tools

Job 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 learningalgorithms, 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.