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Added 3 mins ago
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Director, Enterprise Integration Services – OneRBC: CNB Integration
RBC
Toronto, ON
- Full-time
Align with modern SDLC practices: Collaborate with development teams to integrate CI/CD pipelines and cloud-native patterns.
Added 18 mins ago
TA
Sr Manager/ Associate Director - HR Analytics
Tiger Analytics
Canada
- Full-time
…embrace Generative AI, agentic AI, intelligent automation, and cloud-native data platforms. A global presence across North America, Latin America, Europe, and…
Added 19 mins ago
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Observability Engineer
Gala Solutions
Montreal, QC
- Contract
…fleet, which focuses on delivering tools in private and public cloud environments. The role focuses on developing and modernising observability platforms for cloud-native and hybrid…
Added 1 hour ago
C
AVP Senior Java Developer
Citi
Mississauga, ON
- Full-time
Strong experience with cloud-native technologies such as Kubernetes and Docker.
Added 1 hour ago
ZC
Engineering Lead
Zaya Care
Toronto, ON
- Full-time
People-first and AI-native: You give direct feedback, measure yourself by how much your engineers grow, and have a real point of view on where AI tooling helps and where it doesn’t.
Added 1 hour ago
Solution Architect III, Platform, FSI, Google Cloud
Google
Toronto, ON
10 years of experience with cloud native architecture in a customer-facing or support role.
Added 1 hour ago
Platform Solution Architect III, Google Cloud
Google
Calgary, AB · Vancouver, BC
10 years of experience with cloud native architecture in a customer-facing or support role.
Added 1 hour ago
ML
AI Engineer
MACHINE LEARNING TECHNOLOGIES LLC
Toronto, ON
- Full-time
The candidate will lead and actively contribute to the development of scalable Gen AI products, architectures, and cloud-native solutions within an Agile environment.
Added 2 hours ago
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Winter 2027: Software Developer Co-op, Front End (8 months)
Intuit
Toronto, ON
- Internship
Work across the stack: Use Java and cloud-based APIs to integrate front-end and mobile experiences with backend services.
Added 3 hours ago
AI Outcome Customer Developer, Forward Deployed Development
Google
Toronto, ON
7 years of experience with cloud native architecture in a customer-facing or support role.
Added 4 hours ago
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CHIEF DEVELOPER FULLSTACK - PYTHON
National Bank of Canada
Montreal, QC
- Full-time
A career as a Full Stack Developer on the Information Technology Delivery – Capital Markets team at National Bank means acting as a specialist in software development and cloud solutions.…
Added 4 hours ago
NB
LEAD PYTHON DEVELOPER – IT TREASURY PLATFORMS
National Bank of Canada
Montreal, QC
- Full-time
Advanced knowledge of software architecture, cloud-native design, application programming interfaces, integration patterns, scalability, resiliency, observability, and security.
Added 4 hours ago
Salesforce Technical Architect - Financial Services Cloud, Marketing Cloud & Data360 - Manager
EY
Toronto, ON · Montreal, QC
We're looking for a senior, hands-on technical architect - someone with deep Financial Services Cloud implementation experience who still configures, codes, and builds, not just designs on…
Added 8 hours ago
O
Sr. Software Developer
OpenText
Richmond Hill, ON
- Full-time
…across its established codebase while helping move it toward a cloud-native…
Added 10 hours ago
M
RQ11819 - Software Developer - Senior
Maarut
Toronto, ON
- Contract
Additional Skills for Oracle Software Developer:
Added 10 hours ago
Sr. Network Designer
Rogers Communications
Brampton, ON · Toronto, ON
Contribute to the evolution of AI-assisted, cloud-native, and automated RAN operations, including closed-loop automation with human-in-the-loop governance.
Added 11 hours ago
C
Application Programmer
Collabera
Mississauga, ON
- $70 to $80 USD / hour
- Full-time
…engineering and customer-facing role requires hands-on development, cloud-native deployment, CI/CD expertise, and the ability to translate ambiguous business requirements into scalable,…
Added 12 hours ago
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Program Manager - Retail Technology & AI
Cogniify
Vancouver, BC
- $175,000 to $183,000 CAD / year
- Full-time
Exposure to Snowflake or similar data platforms and cloud-native product development.
Added 13 hours ago
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Sr. Salesforce Administrator/ Business Analyst
Recfront
Toronto, ON
- Contract
…company specializes in technology recruiting with a focus on cloud, data and analytics, AI/ML, cybersecurity, ERP, product, software engineering, infrastructure, and digital…
Added 13 hours ago
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Full Stack Engineer
Ultrassure
Toronto, ON
- Full-time
…PDFs, spreadsheets, email and legacy software. We build AI-native software that helps insurers, reinsurers, MGAs and brokers turn complex, unstructured insurance data into structured…
Added 13 hours ago
SF
Senior AI Engineer
Safe Fleet
Coquitlam, BC
- Full-time
You will also apply AI-Native Engineering and Agentic SDLC practices to your own work - using AI coding agents, Spec-Driven Development and automation to accelerate delivery while holding a…
Added 13 hours ago
M
Kubernetes Engineer (Container security and GKE focus)
Mehbooba
ON · Ontario, Canada
- Contract
Stay updated with emerging security threats and industry best practices related to container security and cloud-native technologies.
Added 13 hours ago
C
Senior Software Developer
Cavtera
Ottawa, ON · Kanata, ON
- Full-time
We’re looking for a Senior Software Developer to join Cavtera’s growing development team.
Added 13 hours ago
C
Senior Full-Stack Engineer / Technical Lead - Onsite
Cognizant
Toronto, ON
- Full-time
…to design and develop scalable enterprise applications and cloud-native solutions. The ideal candidate will combine strong hands-on development experience with technical leadership and…
Added 13 hours ago
O
Staff FullStack Engineer, Secures AI
Okta
Toronto, ON
- $160,000 to $220,000 CAD / year
- Full-time
This role requires deep expertise in distributed systems and a commitment to AI-native engineering as our standard. You will rethink backend design, validation, and delivery through…

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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