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Added 20 mins ago
VP of Engineering
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Full-time
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Added 37 mins ago
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Lead cloud-based initiatives leveraging AWS services and cloud-native architectures.
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Cloud native technology experience, preferably Microservice-based architecture
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Our client is seeking a contract based Full Stack Developer with strong mobile development experience across Swift and React Native, combined with backend development expertise in Node.js,…
Added 1 hour ago
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Build secure, scalable, and high-performance cloud-native applications.
Added 1 hour ago
Senior Machine Learning Engineer // Toronto, ON // Hybrid : FTE
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Deploy ML models and services using cloud-native architectures and enterprise deployment practices.
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Technical Program Manager Retail industry background
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Lead cloud-based initiatives leveraging AWS services and cloud-native architectures.
Added 1 hour ago
Junior Software Engineer
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Build and deploy cloud-native applications on AWS or Azure using Java and React, optimizing for performance, scalability, and resilience.
Added 1 hour ago
Technical Program Manager (Retail industry)
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Vancouver, BC
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Lead cloud-based initiatives leveraging AWS services and cloud-native architectures.
Added 1 hour ago
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…inference speeds; over 10 times faster than GPU-based hyperscale cloud inference…
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…secure, and reliable ML and AI infrastructure, leveraging Google Cloud Platform, containerized workloads, K8s,and modern cloud-native engineering…
Added 1 hour ago
Lead AI engineer
Hays
Halifax, NS
$150,000 to $175,000 CAD / year
Full-time
Our client is seeking an experienced AI Engineering Team Lead to lead the design, development, and support of secure, cloud-native, AI-enabled applications within a highly regulated…
Added 2 hours ago
AI-Aware Data Engineer (Oracle, PostgreSQL & Azure)
Cognizant
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Exposure to cloud-native analytics and reporting solutions on Azure.
Added 2 hours ago
Senior Python Developer
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Toronto, ON
Full-time
· Develop cloud-native applications (AWS preferred)
Added 2 hours ago
Student Intern, SCM Data Scientist
Celestica International LP
Toronto, ON
$23 to $30 CAD / hour
…Celestica enables critical data center infrastructure for AI, cloud, and hybrid cloud and advances technologies in high-growth markets. Working with the world’s leading technology companies…
Added 3 hours ago
Senior SDET (Java & API Automation)
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Toronto, ON · North York, ON
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…in building and managing REST APIs (5-7 yrs); Experience of Cloud Native Development targeting a major Cloud Provider (5-7 yrs); Experience of modern frontend frameworks such as Angular or…

Hays

Lead AI engineer

Halifax, NS, Canada

Pay: $150,000 to $175,000 CAD / year
Job type: Full-time
Apply by: Oct 28, 2026
Experience: 8+ years of software engineering experience with strong expertise in Python development.
Posting language: English
Posted: Sep 28, 2026

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Original job description

AI Engineering Team Lead

Location: Halifax, NS (Hybrid)

Job Type: Full-Time, Permanent

Our client is seeking an experienced AI Engineering Team Lead to lead the design, development, and support of secure, cloud-native, AI-enabled applications within a highly regulated enterprise environment.

As a key member of the technology organization, you will lead a cross-functional team responsible for delivering machine learning, generative AI, document intelligence, and intelligent automation solutions. This role combines people leadership, technical strategy, hands-on engineering oversight, and stakeholder engagement to drive the adoption of AI across the business.

You will be responsible for establishing technical direction, engineering standards, delivery practices, and governance frameworks while partnering with business leaders to identify opportunities for AI-driven transformation and operational efficiency.

Responsibilities

Team Leadership

Lead, mentor, and develop a high-performing AI Engineering team through coaching, hiring, and capability development.
Foster a culture of collaboration, accountability, continuous improvement, and engineering excellence.
Support career development and provide ongoing performance feedback and mentorship.

Technical Leadership

Guide the design, development, and deployment of cloud-native, machine learning, and generative AI solutions in production environments.
Define engineering standards, architecture patterns, and implementation best practices.
Partner with architects and senior engineering leaders on AI services, machine learning platforms, agent-based workflows, data pipelines, and application integrations.
Ensure appropriate selection of AI technologies, frameworks, models, and cloud services based on business and operational requirements.

Business Partnership

Collaborate closely with stakeholders to identify automation opportunities and prioritize AI initiatives with measurable business value.
Translate business requirements into scalable technical solutions and long-term AI roadmaps.
Communicate delivery progress, risks, priorities, and trade-offs to senior leadership.

Document Intelligence & AI Solutions

Define and lead the roadmap for document intelligence and intelligent automation initiatives.
Oversee development of solutions involving:
Document classification
Information extraction
Workflow automation
Retrieval-Augmented Generation (RAG)
AI-assisted operational processes
Intelligent document processing

AI Governance & Quality

Establish governance practices for model evaluation, monitoring, testing, fine-tuning, responsible AI, and production risk management.
Ensure solutions are secure, observable, scalable, and production-ready.
Define standards for model validation, prompt evaluation, regression testing, drift detection, monitoring, and operational support.
Promote responsible use of AI tools and AI-assisted development practices while maintaining human review and approval processes.

Delivery & Operations

Lead agile delivery activities including sprint planning, capacity management, prioritization, and execution.
Manage dependencies, risks, and delivery commitments across multiple initiatives.
Support incident management, root cause analysis, post-mortems, and continuous improvement activities.
Ensure solutions meet performance, reliability, security, and operational support requirements.

Innovation

Evaluate emerging AI technologies, frameworks, tools, and platforms.
Recommend adoption strategies while balancing quality, security, governance, scalability, and cost considerations.
Support the development of enterprise AI capabilities and long-term innovation initiatives.

Qualifications

Required Experience

Bachelor's degree in Computer Science, Engineering, Data Science, or a related discipline.
8+ years of software engineering experience with strong expertise in Python development.
Experience leading engineering teams delivering AI, machine learning, NLP, intelligent automation, or cloud-native solutions in production environments.
Proven people management experience, including hiring, coaching, mentoring, and team development.
Experience working directly with business stakeholders to identify and deliver AI-driven solutions.

Technical Expertise

Strong understanding of:
Generative AI
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Natural Language Processing (NLP)
Intelligent Document Processing
AI Governance
MLOps and Model Lifecycle Management
Software Quality and DevOps Practices
Hands-on experience with technologies such as:
Python
LangChain
LlamaIndex
PyTorch
TensorFlow
Scikit-Learn
SQL and NoSQL databases
Vector databases
Cloud-native application architectures

Cloud Platforms

Experience with AWS, Azure, Google Cloud, or similar public cloud platforms.
Experience with AI platforms such as:
Amazon Bedrock
Azure OpenAI
Azure AI Services
Azure Machine Learning
Anthropic APIs
Comparable foundation model platforms

Leadership Skills

Experience leading agile delivery teams and managing competing priorities.
Strong stakeholder management and communication skills.
Ability to balance business outcomes, engineering quality, operational risk, and delivery timelines.
Experience defining technical strategy, roadmaps, and governance standards.

Preferred Experience

Financial services, fintech, banking, insurance, or other regulated industries.
Experience with document intelligence and enterprise automation platforms.
Experience developing AI strategies involving LLMs, retrieval systems, model fine-tuning, and intelligent automation.
Experience implementing AI evaluation frameworks, monitoring solutions, safety controls, and governance processes.

What You'll Bring

Strong technical leadership and problem-solving skills.
A passion for building and growing engineering teams.
Deep interest in AI innovation and emerging technologies.
The ability to drive strategic initiatives while remaining focused on quality, security, and business value.
A collaborative approach with a strong focus on mentorship, accountability, and continuous improvement.

Salary - $150,000 - $175,000

This posting is for an existing vacancy with the organization.

AI may be used to screen, assess or select applicants for the position.

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More about this job

Responsibilities

Lead and develop an AI engineering team delivering secure, cloud-native machine learning, generative AI, document intelligence, and automation solutions. Set technical direction and governance, partner with business stakeholders on AI roadmaps, and oversee delivery, quality, security, and operational support.

Requirements

Requires a bachelor's degree in a related discipline, at least 8 years of software engineering experience with strong Python expertise, and proven experience leading teams that deliver production AI or cloud-native solutions. Candidates should have people-management and stakeholder-partnership experience, knowledge of generative AI, LLMs, RAG, NLP, MLOps, and AI governance, and experience with cloud platforms and relevant AI tools.

Skills

Python
Generative AI
Large Language Models
Retrieval-Augmented Generation
Natural Language Processing
Machine Learning
MLOps
AI Governance
Cloud-Native Architecture
AWS
Azure
Google Cloud
Agile Delivery
Team Leadership
Stakeholder Management

Visa sponsorship

Not detected in the job text

Keywords

Python
LangChain
LlamaIndex
PyTorch
TensorFlow
Scikit-Learn
SQL
NoSQL
Vector Databases
AWS
Azure
Google Cloud
Amazon Bedrock
Azure OpenAI
Azure AI Services
Azure Machine Learning
Anthropic APIs
Generative AI
Large Language Models
Retrieval-Augmented Generation
Natural Language Processing
Document Classification
Information Extraction
Workflow Automation
MLOps
Model Lifecycle Management
AI Governance
Responsible AI
Agile Delivery

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