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Added 1 hour ago
DL
Kubernetes Engineer (Container Security)
Diverse Lynx
ON · Ontario, Canada
- Contract
7+ years of experience with Google cloud computing platform.
Added 2 hours ago
E
AI DevOps Specialist (AI Enablement & Secure DevOps)
Experis
Canada
- Contract
This specialist will bridge the gap between AI development pipelines, secure networking infrastructure, and cloud platform services. They will take a hands-on lead in configuring…
Added 2 hours ago
SF
Senior Site Reliability Engineer
Safe Fleet
Coquitlam, BC
- Full-time
The Senior Site Reliability Engineer owns reliability, resilience and operational health across SafeFleet’s cloud-native product ecosystem. This is a hands-on engineering role with…
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ES
Expert(e) Réseaux & Sécurité Senior - Senior Network & Security Expert - Montréal
Equans Services Canada & US
Montreal, QC
- Full-time
SLS Infrastructure provides Cloud Platform Services (AWS and Azure) as well as centrally managed Network & Security Services, including:
Added 2 hours ago
PG
Cloud Engineer
Pacer Group
Calgary, AB
- $46 to $50 CAD / hour
- Contract
Strong hands-on experience with Microsoft Azure, AWS, or Google Cloud Platform (GCP).
Added 2 hours ago
M
Senior CyberArk Security Engineer
Manulife
Toronto, ON · Waterloo, ON
- Full-time
Microsoft Azure or another enterprise cloud platform.
Added 2 hours ago
GC
GRC Engineer
GRC Concierge
Ottawa, ON
- Full-time
Knowledge of SaaS and cloud platforms (AWS, Azure, GCP).
Added 2 hours ago
AI
Cloud Platform Engineer – Azure, AWS, or GCP
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Calgary, AB
- Full-time
Cloud Engineer – Azure/AWS/GCP, Cloud Security & IAM
Added 2 hours ago
T
Service Desk - System & Security Tier 2
TEEMA
Calgary, AB
- Full-time
They are not looking for an AI engineer or someone who will build their platform. They are looking for a technician who already uses AI as part of how they work - for scripting,…
Added 2 hours ago
MK
ERP Integration & Transformation Lead
Moose Knuckles Canada
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
Hands-on integration delivery across Azure integration technologies, Power Platform, APIs, middleware platforms, or comparable solutions.
Added 2 hours ago
SF
Senior AI Engineer
Safe Fleet
Coquitlam, BC
- Full-time
We are looking for a hands-on Senior AI Engineer to build the platform that makes that possible - the shared services, agent framework, standards and tooling that allow every engineer on…
Added 2 hours ago
LM
Senior Software Engineer - Product Lead - ISS Team
Lockheed Martin
Ottawa, ON
- $102,750 to $134,750 USD / year
- Full-time
Familiarity with cloud platforms such as AWS, Azure or GCP.
Added 2 hours ago
M
Kubernetes Engineer (Container security and GKE focus)
Mehbooba
ON · Ontario, Canada
- Contract
7+ years of experience with Google cloud computing platform.
Added 2 hours ago
L
Murex DevOps Jun/Mid - Murex Collocated Pool
Luxoft
Toronto, ON
- Full-time
As a DevOps Engineer, you will design, build, and operate automated platforms that enable reliable, secure, and scalable delivery of the MX platform across SaaS, cloud, and on-premises…
Added 2 hours ago
AC
Data Engineer
Amphenol Communications Solutions
Markham, ON
- Full-time
We are seeking a Data Engineer with strong hands-on engineering and software development capabilities to build, integrate, and operate the enterprise data platform. The role will develop…
Added 2 hours ago
MT
DevOps and Security Engineer
Martello Technologies
Ottawa, ON · Greater Ottawa Metropolitan Area
- Full-time
As our DevOps & Security Engineer, you’ll own how Vantage DX and MPA are built, deployed, and secured. That means running the CI/CD pipelines, hardening our AWS and Azure environments, and…
Added 2 hours ago
E
Solutions Engineer
EXFO
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
Added 2 hours ago
E
Solutions Engineer
EXFO
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
Added 2 hours ago
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Senior AI Engineer
Guidepoint
Toronto, ON
- Full-time
We are looking for a hands-on Senior AI Engineer to take working prototypes into production and shape the architecture as the product grows. You will have broad ownership across agent…
Added 2 hours ago
LM
Senior Software Engineer - Product Lead
Lockheed Martin
Ottawa, ON
- Full-time
Familiarity with cloud platforms such as AWS, Azure or GCP.
Added 2 hours ago
ML
IT Security Consultant
Maple Leaf Foods Inc.
Mississauga, ON
- $96,000 to $141,000 CAD / year
- Full-time
Design and implement security measures for the protection of computer systems, networks and information both on-premise and cloud-based.
Added 3 hours ago
T
Technical Lead AI Delivery
TechDoQuest
Brampton, ON
- Contract
They will possess deep expertise in Oracle AI Agent Studio, Oracle Fusion Cloud Applications, AI architecture, GenAI technologies, and enterprise integration patterns. This individual will…
Added 3 hours ago
Y
Technical Lead - AI Delivery
Yochana
Brampton, ON
- Contract
They will possess deep expertise in Oracle AI Agent Studio, Oracle Fusion Cloud Applications, AI architecture, GenAI technologies, and enterprise integration patterns. This individual will…
Added 4 hours ago
TI
Application Release Engineer
Themesoft Inc.
Toronto, ON
- Contract
Cloud providers – Google Cloud Platform, Microsoft Azure
Added 4 hours ago
TI
Application Release Engineer / DevOps Engineer
Themesoft Inc.
Toronto, ON
- Contract
Support multi-cloud environments across Azure, GCP, and AWS.

Guidepoint

Senior AI Engineer

Toronto, ON, Canada

$175,000 - $210,000 CAD · Full-time

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Job details

Pay: $175,000 - $210,000 CAD
Job type: Full-time
Apply by: Nov 28, 2026
Experience: 8+ years of software engineering experience, including 3+ years building and operating production AI or LLM-powered products.
Posting language: English
Posted: Oct 29, 2026

Original job description

Overview

Guidepoint is investing in applied AI across its research platform. We are building production AI systems that help research teams interact with our global expert network and proprietary knowledge assets. These systems combine multi-agent workflows, conversational AI, retrieval, and structured data to support reliable, high-quality research experiences.

We are looking for a hands-on Senior AI Engineer to take working prototypes into production and shape the architecture as the product grows. You will have broad ownership across agent design, evaluation, APIs, and cloud deployment, working closely with product, engineering, and compliance stakeholders.

This is a hybrid role based in our Toronto office.

What You’ll Do:

Build multi-agent workflows: Design and ship systems where specialized agents collaborate to complete research tasks, including task planning, tool use, delegation, handoffs, and result synthesis.
Make agent behavior dependable: Enforce permissions, domain rules, workflow boundaries, and output requirements in application code. Design for safe tool use, clear failure handling, and human review when needed.
Own orchestration and state: Build reliable multi-turn workflows with explicit state management, memory and context strategies, timeouts, retries, and recovery from partial failures.
Develop production APIs: Build and maintain Python services and APIs that connect agents to Guidepoint products, internal data, and third-party providers.
Ground responses in trusted data: Build retrieval and search pipelines over large internal knowledge assets. Return structured, traceable results and make it clear which sources support an answer.
Build the evaluation system: Define and maintain evaluations for task success, factual accuracy, groundedness, completeness, policy adherence, latency, and cost. Use representative test sets, regression checks, and production feedback to guide improvements and rollout decisions.
Deploy and operate AI services: Own services from design through production deployment and operations, using containers, Kubernetes, Azure, and Databricks where appropriate.
Tune the full AI pipeline: Select models and tools, engineer context, define structured outputs, and manage tradeoffs among quality, latency, reliability, and cost.
Integrate providers cleanly: Put model, retrieval, and voice providers behind clear interfaces so the system can evolve as products and requirements change.
Set engineering practices: Establish patterns for code review, testing, observability, incident response, and production readiness as the team grows.

What You Have:

8+ years of software engineering experience, including 3+ years building and operating production AI or LLM-powered products.
A Bachelor’s degree in Computer Science, Engineering, or a related technical field with 6+ years of professional experience; or a Master’s degree with 4+ years of professional experience in backend software engineering and Generative AI. This must include a proven track record of designing, building, and scaling distributed, production-grade systems.
Demonstrated experience designing and shipping multi-agent or agentic workflows in production, including orchestration, tool use, state management, and failure handling.
Strong Python skills and experience building production APIs and backend services. TypeScript experience is useful.
Hands-on experience with cloud-native deployment, including containers, Kubernetes, CI/CD, and production observability.
Experience working with Azure and/or Databricks in production environments.
Practical experience with LLM evaluation: creating test sets, measuring quality and accuracy, analyzing failures, and using results to improve systems or gate releases.
Experience with retrieval-augmented generation, embeddings, vector databases, or large-scale search systems.
Understanding of model and workflow risks, including unsupported answers, prompt injection, unsafe tool calls, and data access boundaries - and experience addressing them through system design and code.
Experience operating services with production requirements for reliability, latency, and cost.
Product judgment: you can scope a useful first version, compare approaches with evidence, and ship iteratively.

Nice to Have:

Experience with agent and orchestration frameworks such as LangGraph, LangChain, or similar, along with the judgment to use plain code when it is a better fit.
Experience with Databricks, including its data, machine learning, or deployment workflows.
Real-time or streaming systems experience, such as WebSockets, WebRTC, audio pipelines, or other low-latency services.
Voice AI experience, including telephony platforms, speech-to-text, text-to-speech, turn-taking, or voice-agent frameworks.
Knowledge graphs or large-scale information retrieval experience.
Experience in regulated or compliance-sensitive industries such as healthcare or finance.
Experience with LLM-as-judge methods, human review workflows, or production monitoring for AI quality.

What We Offer:

The annual base salary range for this position is 175,000-210,000. 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

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More about this job

Responsibilities

Design, build, and operate production AI systems, including multi-agent workflows, reliable orchestration, Python APIs, and retrieval pipelines grounded in trusted data. Establish evaluation and engineering practices, deploy and monitor services in cloud environments, and improve AI quality, reliability, latency, and cost in collaboration with product, engineering, and compliance teams.

Requirements

Requires 8+ years of software engineering experience, including 3+ years building and operating production AI or LLM products, with a relevant bachelor's degree and 6+ years of professional experience or a master's degree and 4+ years. Candidates should have production experience with agentic workflows, Python backend services, cloud-native deployment, Azure and/or Databricks, LLM evaluation, retrieval systems, and designing for reliability, safety, and cost.

Skills

Python
Multi-Agent Workflows
Agent Orchestration
Production APIs
Distributed Systems
LLM Evaluation
Retrieval-Augmented Generation
Vector Databases
Kubernetes
Azure
Databricks
CI/CD
Cloud-Native Deployment
Production Observability
AI Safety and Risk Management
State Management

Benefits

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

Visa sponsorship

Not detected in the job text

Keywords

Python
TypeScript
Generative AI
Large Language Models
Multi-Agent Workflows
Agent Orchestration
LangGraph
LangChain
Retrieval-Augmented Generation
Embeddings
Vector Databases
Information Retrieval
Knowledge Graphs
Azure
Databricks
Kubernetes
Containers
CI/CD
Production APIs
Distributed Systems
LLM Evaluation
LLM-as-Judge
Prompt Injection
Human Review
Observability
WebSockets
WebRTC
Voice AI
Speech-to-Text
Text-to-Speech

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