Artificial Intelligence Engineer

Job Title: AI Developer – Business-Focused Agentic AI Specialist

Location: Canada

Summary:

This role offers a unique opportunity to be at the forefront of agentic AI innovation while delivering tangible business value through intelligent automation and strategic AI implementation.

Position Overview

We are looking for a versatile AI Developer who can bridge advanced AI/ML technologies with real-world business challenges. This role requires a blend of strong technical expertise and business acumen to design and implement intelligent, autonomous AI agents while defining and tracking meaningful business metrics.

The ideal candidate is passionate about emerging AI architectures such as Model Context Protocol (MCP) and thrives in a fast-evolving, innovation-driven environment.

Key Responsibilities

1. AI Development & Architecture

Design and build autonomous AI agents capable of reasoning, decision-making, and multi-step planning

Develop and manage multi-agent systems with inter-agent communication

Integrate large language models (LLMs) and leverage multi-modal capabilities

Utilize industry-standard APIs to consume AI/ML models

Contribute to tool integration within microservice-based architectures

Provide constructive feedback and maintain a solution-oriented mindset

2. Business Analysis & Metrics Definition

Understand complex business challenges and identify AI-driven solutions

Define, implement, and monitor KPIs for AI system performance and operational efficiency

Collaborate with data teams, DBAs, and business analysts to build dashboards and reporting solutions

Translate technical outputs into actionable business insights

Ensure ethical implementation and clear communication of AI solutions

3. Microservices & System Integration

Integrate AI solutions into existing microservice-based ecosystems

Develop scalable APIs for seamless system integration

Work with backend technologies including databases, message queues, and cloud platforms

Ensure deployment readiness, observability, and security in enterprise environments

4. Innovation & Continuous Learning

Stay updated with emerging AI frameworks, especially MCP and related advancements

Participate in R&D initiatives focused on agentic AI

Prototype and evaluate new AI capabilities

Document architectures, processes, and best practices

Required Qualifications

Education & Experience

Bachelor’s degree in Computer Science, AI, Data Science, Mathematics, or related field (Master’s preferred)

3–5 years of experience in AI/ML development

1–2 years of experience working with agent-based systems

Experience collaborating with business stakeholders or performing business analysis

Technical Skills

Programming: Python, JavaScript/TypeScript, SQL (plus Java, C++, Rust, or Go is a bonus)

AI Frameworks: Transformers, OpenAI API, TensorFlow, PyTorch

Agent Frameworks: CrewAI, LangGraph, Semantic Kernel or similar

Architecture: APIs, microservices, and system integration

Cloud & DevOps: Google Cloud, Docker, Kubernetes, MLOps tools

Databases: PostgreSQL, Oracle, and vector databases (e.g., Qdrant, Turbopuffer)

Data Analysis: Strong SQL and large dataset handling

Business & Soft Skills

Strong communication skills with the ability to simplify complex technical concepts

Analytical thinking and problem-solving mindset

Experience defining and tracking KPIs and business metrics

Collaborative approach to working with cross-functional teams

Familiarity with IT service management (ITIL preferred)

Attention to detail, especially in system design and documentation

Preferred Qualifications

Experience in telecommunications or enterprise environments

Familiarity with MCP or similar emerging AI standards

Certifications in AI/ML or LLM technologies

Experience with observability tools and security compliance

Background in business process optimization or digital transformation

What We Offer

Opportunity to work on cutting-edge AI technologies in a business-critical setting

Collaborative, cross-functional team environment with leadership exposure

Continuous learning and upskilling opportunities

A chance to drive AI strategy and deliver measurable business impact

Other Requirements

Commitment to continuous learning in a rapidly evolving AI ecosystem

Ability to quickly adapt to new tools, frameworks, and architectures