Director of AI

Jobtailor; Toronto; On-site; CAD 180,000 - 240,000; Full time

Job summary

Jobtailor in Toronto, Ontario, is seeking a senior AI engineering leader to drive the technical strategy, architecture, and delivery of AI applications from discovery through production and scale.

You will collaborate with client executives, product leaders, architects, and engineering teams to identify AI opportunities and craft technical roadmaps, designing AI apps that blend models, enterprise data, APIs, and human workflows.

Qualifications

• 10+ years in software/data/ML with leadership of AI/ML solutions.
• Experience building AI/Ml apps in production environments.
• Strong foundations in system design, data, APIs, security, cloud ops.
• Hands-on Python with modern AI engineering frameworks.
• Familiar with LLMs, RAG, context engineering, and model evaluation.
• Experience grounding AI in enterprise data and evaluating probabilistic outputs.
• Ability to balance quality, latency, cost, and user experience.
• Experience with cloud-native deployment on GCP/AWS/Azure.

Responsibilities

• Lead technical strategy, architecture, and delivery of AI applications from discovery to production.
• Collaborate with executives, product leaders, architects, and engineers to roadmap AI opportunities.
• Design AI apps combining models, data, APIs, and human workflows.
• Guide RAG, enterprise search, predictive models, and capabilities in digital products.
• Decide when to use deterministic software, ML, LLMs, or human review.
• Establish evaluation-driven development with datasets, error analysis, and business metrics.
• Ensure production reliability, observability, security, latency, and cost targets.
• Oversee CI/CD, model/prompt versioning, monitoring, and regression testing.
• Provide hands-on leadership through prototyping, architecture/code reviews, and delivery oversight.
• Use AI-assisted development with verification and human oversight.
• Support proposals, workshops, solution design, estimates, and exec presentations.
• Develop reusable AI engineering patterns and reference architectures.
• Contribute to hiring and mentoring to grow APPLY's AI capability.

Skills

AI Solutions Leadership

Python

System Design

Data Architecture

Cloud Infrastructure

MLOps

LLMs & RAG

Communication

Education

Bachelor's degree in CS / Software Eng / AI / Data Science or related field

Tools

GCP

AWS

Azure

Containers

CI/CD Tools

MLOps

LLMOps

Job description

• Lead technical strategy, architecture, and delivery of AI applications from discovery through production and scale
• Work with client executives, product leaders, architects, and engineering teams to identify AI opportunities and create technical roadmaps
• Design AI applications combining models, enterprise data, APIs, software components, user experiences, and human workflows
• Guide agentic workflows, RAG, enterprise search, predictive models, and AI capabilities embedded in digital products
• Decide when to use deterministic software, machine learning, LLMs, human review, or combinations
• Establish evaluation-driven development with test datasets, error analysis, deterministic checks, model-based evaluation, and business outcome measurement
• Ensure production reliability, observability, scalability, latency, maintainability, security, and cost requirements
• Guide CI/CD, model and prompt versioning, monitoring, tracing, regression testing, and optimization
• Provide hands‑on technical leadership through prototyping, architecture reviews, code reviews, troubleshooting, and delivery oversight
• Use AI-assisted development and coding agents with verification, security, and human oversight
• Support proposals, discovery workshops, solution design, estimates, and executive presentations
• Develop reusable AI engineering patterns, reference architectures, accelerators, and delivery standards
• Contribute to hiring, technical mentorship, and growth of APPLY's AI capability

Requirements

• 10+ years of experience across software engineering, data engineering, machine learning, or related technology disciplines, including significant experience leading AI or ML solutions
• Experience designing, building, and operating AI or machine learning applications in production
• Strong foundation in system design, APIs, data architecture, testing, security, cloud infrastructure, and production operations
• Hands‑on proficiency in Python and modern application, data, and AI engineering frameworks
• Understanding of LLMs, RAG, context engineering, agentic workflows, tool use, structured outputs, and model evaluation
• Experience grounding AI systems in enterprise data, including structured data, documents, semantic models, vector stores, or knowledge graphs
• Experience establishing evaluation and error‑analysis practices for probabilistic-output systems
• Ability to balance model quality, reliability, latency, cost, security, and user experience
• Experience with cloud‑native architecture and production deployment on GCP, AWS, or Azure
• Familiarity with containers, CI/CD, observability, and MLOps or LLMOps
• Success in consulting, professional‑services, or complex client‑facing environments
• Ability to work across executive conversations, product decisions, architecture discussions, and detailed technical problem‑solving
• Excellent communication skills with technical and non‑technical audiences
• Degree in computer science, software engineering, artificial intelligence, data science, or related field—or equivalent professional experience
• Preferred: experience in regulated, privacy‑sensitive, or large‑scale enterprise environments; model fine‑tuning; open‑source models; multimodal AI; voice agents; computer‑use agents; enterprise AI security controls; internal AI platforms; organizational AI strategy; certifications or delivery experience with GCP, Snowflake, Databricks, or comparable platforms

Core Competencies

Demonstrates expertise in leading the technical strategy and architecture of AI applications, with a strong foundation in system design, data architecture, and production operations. Proficient in Python and modern AI engineering frameworks, with a focus on ensuring production reliability, scalability, and security.

Highest-signal resume keywords

• AI Application Development
• Machine Learning Solutions Leadership
• Cloud Infrastructure Deployment (GCP, AWS, Azure)
• System Design and Data Architecture
• CI/CD and MLOps Practices

ATS Optimization Keywords

Hard Skills

• Python
• AI Engineering Frameworks
• Machine Learning
• Data Architecture
• System Design
• Model Evaluation
• Error Analysis
• Production Operations
• API Development
• Cloud‑Native Architecture

Soft Skills

• Excellent Communication Skills
• Client‑Facing Experience
• Technical Mentorship

Industry Keywords

• AI Applications
• Machine Learning
• Enterprise Data
• Regulated Environments
• Privacy‑Sensitive Environments
• Organizational AI Strategy

Tools & Technologies

• GCP
• AWS
• Azure
• Containers
• CI/CD Tools
• MLOps
• LLMOps