Full-time jobs in Canada

Explore full-time jobs across Canada. Choose a location and read the full job details.

190,576 listings · 19,749 employers Counted Oct 6, 2026. How we count

About these jobs

Employers hiring include Walmart Canada (4,962 listings), Starbucks Coffee Company (1,933 listings), Loblaw Companies Limited (1,524 listings).

Common roles: Project manager, Sales representative, Store manager.

21,265 of these listings include employer-provided pay. Open a job to see its currency and pay period.

Advertised starting pay
Pay period	Median starting pay	Listings
CAD / year	81,600.00	12,263
CAD / hour	24.00	6,287
USD / year	95,500.00	1,062
USD / hour	20.00	425
CAD / month	5,692.25	247
CAD / week	625.00	26
GBP / hour	35.00	15
USD / month	5,000.00	15
CAD / day	380.00	14
GBP / year	40,000.00	12

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Workplace classifications: 2% remote, 18% hybrid, 80% on-site, 0% not specified. Hybrid and on-site classifications may be inferred from descriptions. Check the original ad.

Based on the dated count above. Listings can change. How we count

Full-time jobs in Canada

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Guidepoint

Senior AI Engineer

Toronto, ON, Canada

Apply About employer

Applications open in a new tab.

Job details

Posting language: English
Posted: Oct 5, 2026

Original job description

Overview:

Guidepoint is investing in applied AI across its research platform. We're building conversational AI systems that interact with our global expert network at scale - combining real-time voice, LLM-driven orchestration, and retrieval over large proprietary datasets.

You'll be an early engineer on a new initiative: taking working prototypes to production and shaping the architecture as the product scope grows. This is a hands-on role with broad ownership, close to product and leadership.

This role is hybrid in our Toronto Office

What You'll Do:

Real-time conversational AI: voice- and chat-based agents with low-latency requirements, built on modern telephony and real-time media infrastructure.
LLM orchestration: agentic systems that pursue goals over multi-turn conversations, with hard behavioral guarantees enforced in code - not just prompts.
Multi-channel session management: stateful user interactions that move seamlessly across channels.
Retrieval and grounding: connecting LLM systems to large internal knowledge assets, with structured data flowing back.
Evaluation infrastructure: measuring conversational quality against human baselines and gating rollouts on metrics, not vibes.
Own services end-to-end: design, implementation, deployment (Kubernetes/Azure), and operations, including latency-sensitive real-time workloads.
Design and tune LLM pipelines: context engineering, structured outputs, model selection, cost/latency tradeoffs across vendors.
Build the eval loop and treat quality as a number: define metrics, run experiments, gate releases on them.
Integrate third-party AI and voice vendors behind clean abstractions so providers stay swappable.
Partner with product and compliance stakeholders to encode domain rules into the system.
Set engineering patterns for a growing team: code review, observability, incident habits.

What You Have:

6+ years of software engineering, with 2+ years building LLM-powered products in production (not notebooks): orchestration, RAG/grounding, structured outputs, eval-driven iteration.
Strong TypeScript or Python; comfortable working across both.
Real-time or streaming systems experience: WebSockets, WebRTC, audio pipelines, or comparable low-latency work.
Cloud-native production experience: containers, Kubernetes, CI/CD, observability. Azure a plus.
Familiarity with agent/LLM frameworks such as LangGraph, LangChain, or CrewAI - hands-on exposure is enough; we care that you know the landscape and when plain code beats a framework.
Working familiarity with vector databases and embedding-based retrieval.
Pragmatic product judgment: you scope prototypes, kill weak approaches with data, and ship.

Nice-to-have:

Voice AI: telephony platforms, conversational agent frameworks, STT/TTS, turn-taking/VAD.
Knowledge graphs or large-scale search/retrieval systems.
Regulated or compliance-sensitive domains (healthcare, finance).
Eval harnesses or LLM-as-judge systems.

What We Offer:

The annual base salary range for this position is 175,000-210,000 CAD. Additionally, this position is eligible for an annual discretionary bonus based on performance.

You will also be eligible for the following benefits:

Paid time off
Comprehensive benefits plan
Company RRSP match
Development opportunities through the LinkedIn Learning platform

About Guidepoint:

Guidepoint powers end-to-end research workflows for the world’s best research teams.

Backed by a global network of more than 2 million experts and over 1,600 employees, Guidepoint delivers real-time access to expertise, primary research, and actionable knowledge that help organizations make informed decisions. Through consultations, surveys, events, proprietary content, and AI-enabled tools, we support every stage of the decision-making process - from developing hypotheses and gathering insights to validating assumptions and building conviction for critical decisions.

At Guidepoint, our success relies on the diversity of our employees, experts, and clients, which enables us to foster meaningful connections and a broad range of perspectives. We are committed to creating an inclusive and welcoming environment where individuals of all backgrounds, identities, and experiences can contribute and succeed.

This job posting is for an existing vacancy. The salary offered will be based on the successful candidate’s skills, experience, qualifications, and location.

Compensation

$175,000 - $210,000 CAD

Apply About employer

More about this job

Responsibilities

You will design, implement, and deploy real-time conversational AI systems and LLM orchestration pipelines. Additionally, you will build evaluation infrastructure to measure conversational quality and set engineering patterns for a growing team.

Requirements

Candidates must have 6+ years of software engineering experience, including 2+ years building production-grade LLM-powered products. Proficiency in TypeScript or Python and experience with real-time systems and cloud-native infrastructure are required.

Skills

TypeScript
Python
LLM orchestration
RAG
Kubernetes
Azure
WebSockets
WebRTC
Audio pipelines
CI/CD
Observability
LangGraph
LangChain
Vector databases
Conversational AI

Benefits

Paid time off
Comprehensive benefits plan
Company RRSP match
Development opportunities

Visa sponsorship

Not detected in the job text

Keywords

Senior AI Engineer
Conversational AI
LLM
Orchestration
Retrieval-Augmented Generation
TypeScript
Python
WebSockets
WebRTC
Kubernetes
Azure
CI/CD
Observability
LangGraph
LangChain
CrewAI
Vector Databases
Embeddings
Voice AI
STT
TTS
Knowledge Graphs
Software Engineering
Cloud-native
Real-time systems
Data pipelines
Evaluation infrastructure
Production systems
Hybrid work
Research platform

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