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Added 48 mins ago
TC
Senior L3 Network Engineer (Network SME and Automation Lead)
Tata Consultancy Services
Toronto, ON
- $100,000 to $120,000 CAD / year
- Full-time
…is enabling its clients to transform themselves across the full AI stack, from infrastructure to…
Added 1 hour ago
AS
Forward-Deployed Software Engineer (AI Integration & Modernization)
Andromeda Software Inc.
Toronto, ON
- Full-time
Design and build AI-enabled systems and full-stack components including APIs, integrations, data pipelines, retrieval systems, and user-facing interfaces.
Added 3 hours ago
R
Software Engineer
RBC
Toronto, ON
- Full-time
You will be a full stack developer on a team focused on web applications that support internal and external RBC users. This role supports the modernization and enhancement of enterprise…
Added 3 hours ago
M
Senior Full Stack Java Engineer - Workforce Management (WFM)
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to join the Workforce Management product stream and build enterprise-scale solution supporting forecasting, capacity planning, scheduling,…
Added 5 hours ago
Applied AI Engineer
ContactMonkey
Toronto, ON
Our stack, concretely: Ruby on Rails and Vue.js in a production SaaS codebase; Amazon Bedrock for model inference; AWS on EKS, provisioned with Terraform and Terragrunt across regions;…
Added 6 hours ago
M
Innovative Data Platform Solution Engineer
Microsoft
Toronto, ON
- Full-time
As an Innovative Data Platform Solution Engineer (SE), you will play a pivotal role in helping enterprises unlock the full potential of Microsoft’s cloud database and analytics stack across…
Added 9 hours ago
M
Senior Full Stack Java Engineer
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to design, develop, and support scalable cloud-native applications that power Workforce Management (WFM), Customer Experience (CX), and…
Added 9 hours ago
M
Senior Full Stack Java Engineer - Workforce Management (WFM)
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to join the Workforce Management product stream and build enterprise-scale solution supporting forecasting, capacity planning, scheduling,…
Added 9 hours ago
M
Senior Full Stack Java Engineer
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to design, develop, and support scalable cloud-native applications that power Workforce Management (WFM), Customer Experience (CX), and…
Added 9 hours ago
M
Senior Full Stack Java Engineer - Workforce Management (WFM)
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to join the Workforce Management product stream and build enterprise-scale solution supporting forecasting, capacity planning, scheduling,…
Added 10 hours ago
EG
Développeur(-euse) de logiciels sénior(e) (contenu) / Senior Software Development Engineer
Expedia Group
Montreal, QC · Canada - Quebec - Montreal
- Full-time
Added 10 hours ago
U
Senior Software Engineer, Applied AI & Customer Solutions
Udemy
Toronto, ON
- Full-time
As a Senior Software Engineer, you will join a fast-paced innovation team that builds and deploys AI-powered solutions directly with Coursera's enterprise and campus customers. You will sit…
Added 10 hours ago
CO
Intern, Full Stack Software Engineer - Summer 2027
Capital One
Toronto, ON
- Full-time
161 Bay Street (93021), Canada, Toronto,Toronto, Ontario,Intern, Full Stack Software Engineer - Summer 2027
Added 11 hours ago
IC
Cloud Infrastructure & DevSecOps Engineer
InfoTrack Canada
Toronto, ON
- Full-time
As the Cloud Infrastructure and DevSecOps Engineer, you will own the end-to-end cloud infrastructure and deployment pipeline for InfoTrack Canada. You will unblock critical environment…
Added 13 hours ago
M
Senior Full Stack Java Engineer - Workforce Management (WFM)
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to join the Workforce Management product stream and build reliable solutions for forecasting, staffing, scheduling, real-time adherence,…
Added 13 hours ago
M
Senior Full Stack Java Engineer
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to design, build, test, and maintain reliable full-stack applications. You will use Java and Spring Boot to develop scalable backend…
Added 13 hours ago
M
Senior Full Stack Java Engineer - CX & Contact Center Solutions
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to provide hands-on technical leadership across CX and contact center solutions. You will shape scalable solutions using Java, Spring Boot,…
Added 13 hours ago
M
Senior Full Stack Java Engineer
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to design, build, test, and maintain reliable full-stack applications. You will use Java and Spring Boot to develop scalable backend…
Added 13 hours ago
M
Senior Full Stack Java Engineer - Workforce Management (WFM)
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to join the Workforce Management product stream and build reliable solutions for forecasting, staffing, scheduling, real-time adherence,…
Added 14 hours ago
M
Senior Full Stack Java Engineer - Workforce Management (WFM)
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to join the Workforce Management product stream and build reliable solutions for forecasting, staffing, scheduling, real-time adherence,…
Added 14 hours ago
M
Senior Full Stack Java Engineer - CX & Contact Center Solutions
Miratech
Canada
- Full-time
We are looking for a Senior Full Stack Engineer to provide hands-on technical leadership across CX and contact center solutions. You will shape scalable solutions using Java, Spring Boot,…
Added 14 hours ago
A
Senior Full Stack Developer/AI Builder
adidas
Woodbridge, ON
- Full-time
We are seeking a highly skilled Senior Full-Stack Front-End/Back-End Developer who can design, build, test, deploy, and support enterprise-grade web solutions using technologies such as…
Added 15 hours ago
Senior Software Engineer, Applied AI & Customer Solutions
Coursera
Toronto, ON
As a Senior Software Engineer, you will join a fast-paced innovation team that builds and deploys AI-powered solutions directly with Coursera's enterprise and campus customers. You will sit…
Added 20 hours ago
AI Engineer Intern (Masters)
Electronic Arts
Vancouver, BC
…application. Our team employs a state-of-the-art, cloud-based tech stack equipped with top-tier tools to support initiatives such as data modeling, model training and fine-tuning, and agent…
Added 22 hours ago
M
Full-Stack Software Engineer
Manulife
Toronto, ON · Waterloo, ON
- Full-time
…web-based life insurance illustration experience. We are seeking a Full-Stack Software Engineer to join our Calculations Squad and develop capabilities that help advisors and customers make…

ContactMonkey

Applied AI Engineer

Toronto, ON, Canada

The salary range for this role is $140,000-$160,000.

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Job details

Pay: The salary range for this role is $140,000-$160,000.
Experience: 3+ years of professional software engineering experience, including hands-on work with AI/ML or LLM-powered features.
Posting language: English
Posted: Oct 7, 2026

Original job description

Hey there! We're ContactMonkey 👋

Our mission? To power measurable employee engagement worldwide. And we'd love for you to join us!

About the job - Applied AI Engineer

Join the Engineering Team, where you'll help build our agentic future.

You'll work alongside senior engineers, Product, and our Chief Product & Technology Officer (CPTO) to design, prototype, and ship AI-powered capabilities quickly. This role is hands-on and iterative, focused on building production-grade agentic workflows that improve how internal communications are curated, designed, delivered, measured, and orchestrated.

This is an AI engineering role with real infrastructure ownership. You won't be handed a platform - you'll help build the one our AI features run on. If you like being close to both the model and the metal, this is that job.

Our stack, concretely: Ruby on Rails and Vue.js in a production SaaS codebase; Amazon Bedrock for model inference; AWS on EKS, provisioned with Terraform and Terragrunt across regions; Sidekiq for background work; MySQL and PostgreSQL. We're mid-migration to a GitOps deployment model with Argo CD and Karpenter. You'll touch most of this.

This is not "call an LLM and hope it works." It's careful system design, honest measurement, and shipping production systems that people rely on every working day.

This is a great fit if you've shipped LLM features in production, you're comfortable when the answer involves a Terraform plan rather than a prompt tweak, and you're ready to go deeper - with senior engineers around you to learn from.

Your impact

Agentic Design & Orchestration: Build agentic workflows and orchestration patterns (dynamic routing, tool-using agents, feedback loops) - contributing to the design and owning the implementation of well-scoped components.

Evals & Measurement: Own the eval harness for the features you ship. Build the datasets, the automated grading, and the offline regression suites that tell us whether a prompt or model change actually made things better. Raise the bar for evaluation across the team - judge design, offline and online metrics, and the judgment to know when a number is real. Turn production failures into evals that catch that class of failure next time.

Infrastructure for AI: Own work with SRE and build the infrastructure your features depend on, as code. Build the deployment path for AI workloads on EKS alongside our SRE and platform engineers.

Reliability, Cost & Safety: Keep our AI layer trustworthy as it grows. Instrument token spend, latency, and failure rates as first-class metrics. Design for the failure modes that matter - hallucination, timeout, rate limit, cost blowout - and make sure the system degrades gracefully instead of falling over. Respond when things behave unexpectedly in production.

Prompts & Model Configuration as Code: Treat prompts as versioned, reviewable, rollback-able artifacts rather than strings someone edited in a console. Own how we move a prompt or model change from idea to production safely, and how we back it out when it turns out worse.

Data Residency & Trust: We run regional deployments because our customers require it. Help make sure AI features respect those boundaries - that customer data stays in-region, model invocations are logged, and what we send to a model is what we intended to send. Think about prompt injection and PII exposure before an auditor does.

Execution & Experimentation: Take a defined problem and run with it. Contribute to our quarterly AI roadmap, run experiments to benchmark model value, and iterate systematically on prompts, retrieval, and model configurations based on what the data tells you.

Cross-Functional Partnership: Work closely with Product Management to turn product ideas into concrete technical work - both customer-facing features and internal workflow automation.

Grow With the Team: Participate actively in design discussions and code reviews. Ask questions early, escalate blockers, and share what you learn. Contribute to documentation practices (agents, markdown, Knowledge Bases) as we figure them out together.

Cultural Stewardship: Be a full participant in helping the engineering culture evolve as we grow.

About you

You hold a Bachelor's degree (or higher) in Computer Science, Statistics, Mathematics, or Engineering, or equivalent practical experience.
3+ years of professional software engineering experience, including hands-on work with AI/ML or LLM-powered features.
Strong fullstack experience - Ruby on Rails (or any other backend language/framework) and Vue.js/React (or any other framework) preferred. You're comfortable in a production SaaS codebase and can navigate unfamiliar systems without needing everything explained first.
You've written and applied infrastructure as code yourself. Terraform preferred - you've authored modules, read a plan carefully before applying it, and recovered from state that didn't match reality. Terragrunt, CloudFormation, or CDK experience transfers.
Working knowledge of AWS beyond the console: IAM (roles, policies, least privilege), VPC and networking basics, secrets management, and how a containerized workload gets deployed and observed. Kubernetes familiarity is a strong plus.
You've taken LLM work past a prototype at least once - you've thought about output quality, iterated on prompts against real usage, and dealt with the gap between "works in the notebook" and "works for customers."
You've built evaluation beyond trial and error - you can measure accuracy, safety, and latency, and you know when a benchmark win is real and when it's noise.
You understand how to structure LLM calls for reliability: using function calling and structured outputs to ground results, testing responses systematically, and designing for failure modes (hallucinations, latency, cost).
You can reason about what an AI feature costs to run - tokens, context size, retries, caching - and you treat that as an engineering constraint rather than someone else's problem.
You have familiarity with RAG architectures and vector stores, and an interest in multi-agent orchestration frameworks - you don't need to have run them at scale, but you should know the landscape.
You default to AI in your own workflow. You've already integrated modern AI tools into how you work, and you use them to move faster rather than as a crutch.
You prioritize a "question first, then answer" approach, thinking critically about problems before committing to a code path.
You bring intellectual humility, empathy, and strong listening skills to the team.
You are able to work collaboratively and independently.
You are comfortable with agile development.
You have excellent oral and written communication skills.

How you can stand out

You've built something agentic - an LLM reasoning across multiple steps, making decisions from tool outputs, adapting to feedback. Side projects count.
You've built an eval harness that changed a decision - where the numbers told you to ship, hold, or roll back, and you listened.
You've operated AI in production - you've been on the other side of a cost spike, a provider outage, a model deprecation, or a quality regression that only showed up under real traffic.
You have a bias toward simplicity - you're pleased when a well-structured baseline beats something more complex, and you know when not to reach for a model at all.
You've worked with Amazon Bedrock, or have opinions about model routing and provider abstraction earned the hard way.
You've worked within the email ecosystem or a similar high-scale communication platform.
You've built with AI coding agents and have a view on what they're good and bad at - we use them, and we're still figuring out the right practices.
You prototype fast, iterate quickly, and use data to change direction when the evidence says so.
You share what you learn with peers - writeups, demos, docs, internal talks.

What we bring to the table

🏥 100% employer-paid benefits + a Health Spending Account from day one
🌎 Work from anywhere in the world for up to 4 weeks
💰 Stock option plan-own a piece of our success
💲 RRSP Group Savings Plan to plan for your future
🏝 Generous vacation package to recharge and relax
📚 Personal development budget to fuel your growth
🧖 One personal day + two volunteering days to give back
🎂 Your Birthday off-celebrate on us!
🍎 Five health days per year to stay at your best
💼 Beautiful downtown Toronto office for hybrid work-fully stocked with all the best snacks

Compensation & Work Details

The salary range for this role is $140,000-$160,000. Compensation is thoughtfully determined based on your experience, skill set, and alignment with our internal compensation framework and internal equity.

We're always happy to answer questions about compensation throughout the hiring process.

This is a net new position for our AI Engineering Team based out of our downtown Toronto office, at King and Spadina. Our team works in the office 3x per week or as needed to promote collaboration.

Who We Are

Imagine being part of a team of brilliant minds, all shaping the future of workplace communication. Here at ContactMonkey, we're not just sending out traditional emails with our internal comms software; we're changing the way companies connect and communicate with their people. Brands like IKEA, Roku, KPMG, and countless others are using our solution to transform employee engagement.

Our all-in-one platform-featuring a drag-and-drop email builder, engagement tools, and analytics-makes it easy for businesses to create, send, and measure their internal email campaigns directly within Outlook or Gmail. This way, internal communications go from being ignored to binge-worthy, sparking more opens, clicks, and conversations.

We've been on an explosive growth streak over the past few years, and we're not slowing down anytime soon. Here's a bit of what we're proud of:

Ranked by the Globe & Mail as one of Canada's fastest-growing companies
Recognized in 2023, 2024 and 2025 Deloitte Technology Fast 50™ awards for revenue growth over the past four years
Recognized in 2023, 2024 and 2025 Deloitte Technology Fast 500™ as one of the fastest-growing companies in North America
Raised $55 million Series A financing in 2023

Diversity is our strength

At ContactMonkey, we are building diverse products and we need a diverse team to do that. We strongly encourage applications from everyone regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.

We are committed to creating an accessible experience for all candidates. If you require any accommodations or adjustments during the interview process or beyond, please inform us, and we will work with you to ensure the necessary support is in place. We are continually striving to enhance our accessibility practices and welcome any feedback or suggestions on how we can better serve candidates with accessibility.

AI Disclosure

We use AI to take notes during our interview. Applications and interviews are reviewed by our Talent Acquisition team. Our applicant tracking system utilizes AI for workflows and hiring process efficiencies.

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More about this job

Responsibilities

You will design, prototype, and ship AI-powered agentic workflows while owning the underlying infrastructure and evaluation harnesses. You will collaborate with product and engineering teams to ensure AI features are reliable, cost-effective, and performant in a production environment.

Requirements

Candidates must have at least 3 years of professional software engineering experience with hands-on work in AI/ML or LLM-powered features. A bachelor's degree in a technical field is required, along with strong full-stack proficiency and experience with infrastructure as code.

Skills

Ruby on Rails
Vue.js
Amazon Bedrock
AWS
Terraform
Kubernetes
LLM
Agentic workflows
Infrastructure as code
GitOps
Argo CD
MySQL
PostgreSQL
System design
Evaluation metrics
RAG

Benefits

Employer-paid benefits
Health spending account
Stock option plan
RRSP group savings plan
Vacation package
Personal development budget
Personal days
Volunteering days
Birthday off
Health days

Visa sponsorship

Not detected in the job text

Keywords

Applied AI
Ruby on Rails
Vue.js
Amazon Bedrock
AWS
EKS
Terraform
Terragrunt
Sidekiq
MySQL
PostgreSQL
GitOps
Argo CD
Karpenter
LLM
Agentic workflows
Infrastructure as code
SRE
Kubernetes
RAG
Vector stores
Prompt engineering
Evaluation harness
SaaS
Data residency
PII
Latency
Token spend
System design
Agile

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