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Added 4 months ago
R
Principal Platform Engineer, Machine Learning
RAVL
Toronto, Ontario
- Full-time
Architect and lead development of ML platforms on Azure Databricks
Added 3 months ago
A
Senior Professional Services Consultant
Ataccama
Toronto, ON
- Full-time
Have several years in customer-facing or consulting roles (technical consultant, software consultant/architect, services presales) and have owned complex engagements independently
Added 2 months ago
Solutions Architect
Databricks
Toronto, ON
As a Solutions Architect at Databricks within the Field Engineering org you will partner with our customers to design scalable data architectures using Databricks technology and services.…
Added 4 months ago
C
Full Stack Java Developer Lead
CGI
Toronto, Ontario
- Full-time
Architect and implement cloud-native insurance platforms on AWS, Azure, or GCP.
Added 3 months ago
M
Lead Solution Architect, Customer Analytics, EDW & AI
McKesson
Mississauga, ON
- Full-time
Job Title: Lead Solution Architect – Customer Analytics, Enterprise Data Warehouse & AI
Added 3 months ago
M
Principal Software Engineer
Morningstar
Toronto, ON
- Full-time
Architect the platform consolidation strategy, migrating legacy feed products onto a unified, governed, cloud-native architecture.
Added 3 months ago
Junior to Intermediate Data Engineer
Talents LGS
Montreal, QC
You will be supported in your professional development to progress toward an autonomous Data Engineer role and eventually toward a Data Architect or Data Specialist position.
Added 5 months ago
KC
Manager, Data Platform(s) Architect, Data & AI
KPMG Canada
Toronto, Ontario
- Full-time
Architect and develop overall end-to-end design of data and analytics solutions across Data Lakes, Data Warehouses, Data Lakehouses, pipelines on modern data platforms such as Microsoft…
Added 5 months ago
KC
Manager, Data Platform(s) Architect, Data & AI
KPMG Canada
Vancouver, British Columbia
- Full-time
Architect and develop overall end-to-end design of data and analytics solutions across Data Lakes, Data Warehouses, Data Lakehouses, pipelines on modern data platforms such as Microsoft…
Added 5 months ago
KC
Manager, Data Platform(s) Architect, Data & AI
KPMG Canada
Calgary, Alberta
- Full-time
Architect and develop overall end-to-end design of data and analytics solutions across Data Lakes, Data Warehouses, Data Lakehouses, pipelines on modern data platforms such as Microsoft…
Added 1 month ago
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Credit Tech senior Manager
PwC
Toronto, ON
- Full-time
Architect and oversee production grade data pipelines and model operationalization across a range of platforms, which may include credit decisioning and scoring platforms (for example,…
Added 5 months ago
LA
Value Engineer (Forward Deployed Engineer)
Lumi AI
Remote, Canada
- $100,000 to $120,000 USD / year
- Full-time
- Remote
…mission-critical operations on SAP, Oracle, Snowflake, and Databricks. They trust Lumi to find the insights their analyst teams…
Added 2 months ago
AI Engineer
Guidepoint
Toronto, ON
…primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s…
Added 2 months ago
Senior Data/AI Engineer
Guidepoint
Toronto, ON
…primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s…
Added 3 months ago
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Global Lead, Digital Procurement
''
Toronto, Ontario
- Full-time
- Other
Acting as the architect and owner of the Global Digital Procurement Strategy and Roadmap, the Global Lead, Digital Procurement ensures that our technology ecosystem, data foundation, and…
Added 3 months ago
A
Part Time - Data Architect
Architech
Toronto, ON
- Part-time
Data Architect (Microsoft Azure / Microsoft Fabric / AWS/ Databricks)
Added 1 month ago
A
Tech Delivery Lead-AI&Data
Accenture
Toronto, ON
- Full-time
…the morning and a technical design review with a client Chief Architect in the afternoon and be equally credible in both rooms. As a Technology Delivery Lead within our AI-Ready Data tower,…
Added 1 month ago
A
Director-Technology Delivery-AI&Data
Accenture
Toronto, ON
- Full-time
…confidence the program is on track, and the person a client Chief Architect calls when a technical decision needs an experienced second…
Added 1 month ago
Senior Specialist, Data & Cloud Platform & Microsoft Azure
PowerCo SE
St. Thomas, ON
This senior expert role is pivotal in advancing PowerCo’s data-driven and cloud transformation. You will architect and lead Azure-based data and compute platforms that support predictive…
Added 3 months ago
RM
Data Team Lead
Redpath Mining Contractors and Engineers
Vaughan, Ontario
- Full-time
The role operates within a project-based delivery model and works closely with the Project Manager and Data Architect to translate priorities and designs into delivered outcomes.
Added 3 months ago
Machine Learning Engineer III, Data
ACV
Toronto, Ontario
Architect and maintain high-throughput, containerized microservices for model serving using REST/gRPC to ensure low-latency performance.
Added 3 months ago
Machine Learning Engineer IV, Data
ACV
Toronto, Ontario
Architect and maintain high-throughput, containerized microservices for model serving using REST/gRPC to ensure low-latency performance.
Added 4 months ago
Z
Solutions Integration Architect - SAP Ariba
Zip
Remote, Canada
- Full-time
- Remote
We’re looking for a Solutions Architect to help build the technical foundation that powers Zip’s ERP and integration ecosystem. This role focuses on internal technical enablement,…
Added 2 months ago
A
Senior AI Lead: Databricks
Accenture
Remote, Canada
- Full-time
- Remote
Architect AI-native solutions on Databricks (Mosaic AI, Vector Search, Model Serving, MLflow) with Unity Catalog governance, scaling reusable patterns across customer engagements.
Added 4 months ago
MI
Full Stack Developer
Magna International
Brampton, Ontario
- Full-time
The Full Stack Developer will work with the IoT architect, technical product owner and a team of developers (Sr full stack, software, IoT, data science) to ensure the efficient and…

Guidepoint

AI Engineer

Toronto, ON, Canada

Apply About employer

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Job details

Experience: Production AI Application Experience: 2+ years of experience building applications that leverage large language models from providers like OpenAI, Anthropic, or Google Gemini.
Posting language: English
Posted: Aug 18, 2026

Original job description

Overview:

Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products.

This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products.

Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services.

This is a hybrid position based in Toronto.

What You'll Do:

Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems.
Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production environments like Databricks and Azure Kubernetes Service (AKS).
Optimize RAG Pipelines: Continuously improve retrieval and generation quality through techniques like retrieval optimization (tuning k-values, chunk sizes), using re-rankers, advanced chunking strategies, and prompt engineering for hallucination reduction.
Integrate Intelligent Systems: Engineer solutions that seamlessly combine LLMs with our proprietary knowledge repositories, external APIs, and real-time data streams to create powerful copilots and research assistants.
Champion LLMOps and Engineering Best Practices: Collaborate with data science and engineering teams to establish and implement best practices for LLMOps, including automated evaluation using frameworks like LLM Judges or MLflow, AI observability, and system monitoring.
Evaluate and Implement AI Strategies: Systematically evaluate and apply advanced prompt engineering methods (e.g., Chain-of-Thought, ReAct) and other model interaction techniques to optimize the performance and safety of proprietary and open-source LLMs.
Mentor and Lead: Provide technical leadership to junior engineers through rigorous code reviews, mentorship, and design discussions, helping to elevate the team's engineering standards.
Influence the Roadmap: Partner closely with product and business stakeholders to translate user needs into technical requirements, define priorities, and shape the future of our AI product offerings.

What You Have:

Experience: 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.
Strong Software Engineering Fundamentals: Deep expertise in Python, a major backend framework (e.g., FastAPI, Flask), and asynchronous programming (e.g., asyncio). Proficiency in designing RESTful APIs, microservices, and the complete operational lifecycle, including comprehensive testing, CI/CD (e.g., ArgoCD), observability, monitoring, alerting, maintaining high uptime, and executing zero-downtime deployments.
Cloud & Infrastructure Proficiency: Hands-on experience deploying and managing applications on a major cloud platform (Azure preferred, AWS/GCP acceptable) using containerization (Docker) and orchestration (Kubernetes, Helm).
Production AI Application Experience: 2+ years of experience building applications that leverage large language models from providers like OpenAI, Anthropic, or Google Gemini. Direct experience with modern LLM patterns such as retrieval-augmented generation (RAG), hybrid search using vector databases (e.g., Pinecone, Elasticsearch), multi-agent AI systems with tool calls, and prompt engineering is required.
AI System Design and Evaluation: Experience designing and implementing robust evaluation frameworks for LLM-based systems, including rubric-based scoring, LLM Judges, or using tools like MLflow, alongside monitoring for performance and drift.
Large-Scale Data Processing: Familiarity with large-scale data processing platforms and tools (e.g., Databricks, Apache Spark).
Familiarity with the Modern AI Stack: Practical experience with libraries and frameworks like LangChain or LlamaIndex for building LLM-powered applications.
Leadership and Mentorship: Demonstrated ability to lead complex technical projects and foster the growth of other engineers.

What We Offer:

The annual base salary range for this position is $135,000 - $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

Guidepoint's Interview Process:

We respect your time and aim to keep the process transparent and efficient. Our Talent Acquisition team members act as advisors throughout the process and help ensure everything runs smoothly so you have a seamless candidate experience. Our goal is to make sure this is a mutual fit for both you and our teams.

Talent Acquisition Screen (Virtual, 30 minutes)
Hiring Manager Interview (Virtual, 1 hour)
Live Coding & System Design Test (On-site, 2 hours)
Technical Leadership Interview (Virtual, 1 hour)
Reference Checks (3 professional references)
Offer

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 post is for a live vacancy. Base salary may vary depending on job-related knowledge, skills, and experience, as well as geographic location.

Compensation

$135,000 - $210,000 CAD

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More about this job

Responsibilities

Architect and build scalable production systems and APIs to serve Generative AI features and RAG pipelines. Lead the end-to-end AI application lifecycle, including deployment, monitoring, and the implementation of LLMOps best practices.

Requirements

Requires a Bachelor's or Master's degree with 4-6+ years of experience in backend software engineering and Generative AI. Must have proven expertise in Python, cloud infrastructure (Azure preferred), and building production-grade LLM applications.

Skills

Python
Generative AI
LLM
RAG
FastAPI
Kubernetes
Azure
Databricks
MLOps
PyTorch
LangChain
LlamaIndex
Vector Databases
System Design
CI/CD
Asynchronous Programming

Benefits

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

Visa sponsorship

Not detected in the job text

Keywords

Generative AI
Large Language Models
LLM
RAG
Retrieval-Augmented Generation
Databricks
Azure
Kubernetes
Docker
FastAPI
Flask
Asyncio
MLflow
LangChain
LlamaIndex
Pinecone
Elasticsearch
Apache Spark
CI/CD
ArgoCD
LLMOps
Prompt Engineering
Chain-of-Thought
ReAct
Microservices
RESTful APIs
Vector Databases
AI Observability
System Design
Distributed Systems

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