AI Engineer

Start date: ASAP

End date: October 31, 2027

Work Location: downtown Toronto, ON - Hybrid (2-3 days per week onsite)

Project Background

You will work across complex client engagements designing and implementing AI/ML and agentic AI solutions end to end. You will work closely with business stakeholders, AI Architect, AI Platform Engineers, and Data Scientists to translate complex business challenges into practical, scalable, and responsible AI solutions through maintainable architectural. You will have the opportunity to influence executive stakeholders and help clients responsibly adopt agentic AI to drive measurable business outcomes.

As AI Engineer, you will design and build production-grade AI and agentic AI solutions that solve real business problems. You are the core builder on the delivery team, responsible for AI/ML pipelines, agentic workflows, multi-agent coordination, evaluation frameworks, observability and governance that ensure AI solutions work in production.

Key Responsibilities

Design and implement production-grade agentic AI workflows using open frameworks such as LangGraph, CrewAI, proprietary cloud-based agentic platforms, including agent orchestration, AI gateways (i.e. MCP, A2A), observability, controls and guardrails.

Build and optimise retrieval pipelines for Retrieval Augmented Generation (RAG) and agentic workflows, including chunking strategies, embedding models, vector store integration, and re-ranking to ground agent outputs in accurate, current enterprise data.

Develop and integrate Generative/Agentic AI solutions using large and small language models (LLMs and SLMs).

Build evaluation frameworks to measure AI solution quality, consistency, and implement telemetry and monitoring to track model drift, latency, output quality,



and cost metrics in production.

Implement best practices for MLOps, LLMOps, across experimental and production environments, including AI pipeline and microservices deployment into cloud environments, APIs, CI/CD, ensuring high availability and low latency.

Build AI governance and responsible AI controls for AI systems

Contribute to AI assets, accelerators, delivery standards, and go-to-market offerings in agentic and generative AI

Required Qualifications

A degree in Computer Science, Software Engineering, Data Science, or a related field.

3-5+ years of AI development experience, with at least 2 years focused on building and maintaining production grade AI/ML or agentic AI solutions.

Advanced object-oriented coding skills in Python for production-level codebases. Familiarity with Java, TypeScript/JavaScript is a plus.

Hands-on experience building and deploying AI agents and AI/ML solutions.

Hands-on experience with containerisation (Docker, Kubernetes), CI/CD pipelines, and version control for AI systems; working knowledge of LLM observability and monitoring tools.

Experience in API integration and development.

Consulting or qualified services experience is strongly preferred.

Skills and Attributes for success:

Deep experience designing and building agentic AI systems in enterprise environments.

Analytical mindset to troubleshoot AI-specific failure modes, model hallucinations, retrieval gaps, context overflow, agent looping, and system latency and engineer reliable solutions around them.

Experience with AI governance, model risk management, and regulatory considerations in complex or regulated industries.

Adapts quickly to fast-moving environments with frequent updates in AI frameworks, agentic tool patterns, LLM capabilities, and cloud platform services

📌 AI Engineer (Toronto)
🏢 Experis
📍 Toronto