Full-time jobs in Canada

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

191,192 listings · 19,863 employers Counted Oct 6, 2026. How we count

About these jobs

Employers hiring include Walmart Canada (4,927 listings), Starbucks Coffee Company (1,909 listings), Loblaw Companies Limited (1,519 listings).

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

21,411 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	81,765.30	12,391
CAD / hour	24.00	6,315
USD / year	95,500.00	1,061
USD / hour	20.00	423
CAD / month	5,538.94	239
CAD / week	1,200.00	30
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

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 4, 2026
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

Build and operate production conversational AI systems spanning real-time voice and chat, LLM orchestration, multi-channel sessions, and retrieval over proprietary data. Own services from design through deployment and operations, establish evaluation and release-gating practices, integrate AI and voice vendors, and set engineering patterns in partnership with product and compliance teams.

Requirements

Requires 6+ years of software engineering experience, including 2+ years building production LLM-powered products, and strong TypeScript or Python skills. Candidates should have experience with real-time or streaming systems, cloud-native production environments, retrieval and vector databases, and practical LLM evaluation; Azure and voice AI experience are advantageous.

Skills

TypeScript
Python
LLM Orchestration
Retrieval-Augmented Generation
Real-Time Systems
WebSockets
WebRTC
Kubernetes
Azure
Cloud-Native Development
Vector Databases
Embedding-Based Retrieval
Evaluation Infrastructure
Structured Outputs
Voice AI
Observability

Benefits

Paid Time Off
Comprehensive Benefits Plan
Company RRSP Match
Development Opportunities Through LinkedIn Learning

Visa sponsorship

Not detected in the job text

Keywords

Applied AI
Conversational AI
Real-Time Voice
Chat Agents
LLM Orchestration
Agentic Systems
Multi-Turn Conversations
Retrieval-Augmented Generation
Knowledge Retrieval
Structured Data
Evaluation Infrastructure
TypeScript
Python
WebSockets
WebRTC
Audio Pipelines
Kubernetes
Azure
Containers
CI/CD
Observability
LangGraph
LangChain
CrewAI
Vector Databases
Embeddings
Telephony
Speech-to-Text
Text-to-Speech

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