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Added 1 hour ago
M
AI Engineer
maru.ai
Engineer, BC
- Full-time
We are an early stage startup developing cutting-edge AI technology. We are looking for a talented AI engineer to join our small but growing team. You will have the opportunity to take on a…
Added 2 hours ago
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Security Engineer II - Identity and Access Management
Marqeta
Remote, Canada
- Full-time
- Remote
We’re seeking an experienced Security Engineer II with a strong passion for Identity and Access Management (IAM) and expertise in cloud-native environments, particularly AWS. You'll build,…
Added 6 hours ago
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Software Engineer- Inference Performance
Baseten
Montreal, QC
- $180,000 to $360,000 USD / year
- Full-time
…Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models…
Added 6 hours ago
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Software Engineer- Inference Platform
Baseten
Montreal, QC
- $180,000 to $360,000 USD / year
- Full-time
…Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models…
Added 9 hours ago
PC
Senior Associate -Cyber Security Forward Deployed(Bilingual FR/EN)
PwC Canada
Ottawa, ON
- Full-time
…position offers an opportunity to build your expertise in cloud infrastructure security, secure application development, DevSecOps and emerging capabilities/skills in AI, while growing your…
Added 10 hours ago
Senior Platform Engineer, AI & Fabrics
BMO
Toronto, ON · FCP
BMO is building the platform capabilities that make enterprise AI safe, governed, and scalable. We are seeking experienced Senior Engineers to help build and operate the core infrastructure…
Added 10 hours ago
S
Senior DevOps Engineer – AI & Data Platform
Systematix
Canada
- Contract
We are Systematix and we are currently looking for a Senior DevOps Engineer – AI & Data Platform to help modernize and automate the engineering practices supporting a rapidly growing…
Added 10 hours ago
B
Senior Platform Engineer, AI & Fabrics
BMO
Toronto, ON
- Part-time
BMO is building the platform capabilities that make enterprise AI safe, governed, and scalable. We are seeking experienced Senior Engineers to help build and operate the core infrastructure…
Added 11 hours ago
AI Engineer Sr
Dayforce
Canada
Our award-winning Cloud HCM platform offers a unified solution database and continuous calculation engine, driving efficiency, productivity and compliance for the global workforce.
Added 13 hours ago
Senior Software Engineer, Security Engineering - Platform (Auth0)
Okta
Toronto, ON
We are looking for a Senior Software Engineer that will join the Auth0 Security Engineering organization. In this role, you will join a team of Software Engineers dedicated to building and…
Added 16 hours ago
SL
Sr. Analytics and Automation Engineer
Sun Life
Toronto, ON · Waterloo, ON · Sun Life Toronto One York
- Full-time
Sr. Analytics and Automation Engineer - Focus on Micro segmentation Policy-as-a-Code.
Added 16 hours ago
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Quality Engineer
Hays
Toronto, ON
- Contract
As a Senior Quality Engineer, you will be responsible for defining and implementing quality assurance processes, developing automated tests, identifying and mitigating risks, and ensuring…
Added 18 hours ago
XI
Senior Data Engineer, Network Intelligence
Xplore Inc.
Canada
- Full-time
As a Senior Data Engineer on the Network Intelligence team, you will own the end-to-end data pipeline function that powers Xplore's network analytics, observability, and AI capabilities…
Added 18 hours ago
C
AI Product Scaling Director
CIBC
Toronto, ON
- Full-time
You are a hands-on senior engineering leader. You have atleast 5+ experience operating at a Staff, Principal, Lead Engineer, or equivalent level, and you enjoy both designing systems and…
Added 1 day ago
Q
Backend Developer (Kotlin)
Quartz
Open Hall, NL
- Full-time
Quartz is reimagining wealth management through personalised intelligence. It's the first wealth platform that truly learns from you, understands your goals, and helps you make confident,…
Added 1 day ago
P
Senior Backend Engineer .NET & Python
PosiTrace
Vancouver, BC
- Full-time
PosiTrace builds a real-time GPS fleet tracking SaaS platform -- vehicle location, telemetry processing, reporting, dispatching, and fleet management tools for SMB and enterprise customers…
Added 2 days ago
H
Senior Software Engineer, Machine Learning
hive.co
Remote, Canada
- Full-time
- Remote
As a Senior Data Engineer, you’ll play a vital role in evolving our data platform, which directly determines what our customers can do, how fast our product moves, and how confidently…
Added 2 days ago
R
Senior Director, Program Delivery
RBC
Toronto, ON
- Full-time
…managing dependencies across research teams, engineering teams, platform groups, and business…
Added 2 days ago
M
Senior Cloud Infrastructure Engineer
Mecka
Remote, Canada
- $165,000 to $200,000 CAD / year
- Full-time
- Remote
Every video frame we capture, label, and deliver to customers moves through AWS infrastructure this team builds and runs. We're hiring a Senior Cloud Infrastructure Engineer to help design,…
Added 3 days ago
MT
Technical Staff Engineer-Applications
Microchip Technology Inc.
Burnaby, BC · Canada - Burnaby
- Full-time
Microchip Technology Inc. is seeking a Principle Engineer – Applications to join our rapidly expanding DCS organization in Burnaby, Canada. Our products are widely deployed by top AI server…
Added 3 days ago
Software Engineer
ExaCare AI
Toronto, Ontario
As a Software Engineer, you will help shape exacare’s platform by delivering features, improving existing systems, and taking increasing ownership as you grow. Working closely with…
Added 3 days ago
WT
Senior Software Developer, ML Platform & Infrastructure
Wealthsimple Technologies
Toronto, ON
- $152,000 to $189,000 CAD / year
- Full-time
We are looking for an experienced MLOps or ML Platform Engineer who is excited to pivot their deep background in model orchestration, serving, and platform tooling toward solving the unique…
Added 3 days ago
TS
Artificial Intelligence Engineer
Triunity Software, Inc.
Toronto, ON
- Full-time
1 year of professional experience with GCP/ Azure cloud infrastructure
Added 3 days ago
E
Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova
Evinova
Mississauga, ON
- Full-time
As a Senior Cloud Platform Engineer on the ML/AI Ops team, you will design, build and operate the AWS platform that runs our production Generative AI, agentic AI and conversational AI…
Added 3 days ago
Robotics Engineer - Edge Runtime, Physical AI Hub, Kitchener
Siemens
Kitchener, ON
We are seeking a Robotics Engineer - Edge Runtime to help build and optimize the edge software layer for the Physical AI Runtime. This engineer will work on edge development, robotics…

Dayforce

AI Engineer Sr

Canada

Apply About employer

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Job details

Apply by: Dec 6, 2026
Posting language: English
Posted: Oct 5, 2026

Original job description

Dayforce is a global human capital management (HCM) company headquartered in Toronto, Ontario, and Minneapolis, Minnesota, with operations across North America, Europe, Middle East, Africa (EMEA), and the Asia Pacific Japan (APJ) region.

Our award-winning Cloud HCM platform offers a unified solution database and continuous calculation engine, driving efficiency, productivity and compliance for the global workforce.

Our brand promise - Makes Work Life Better™ - Reflects our commitment to employees, customers, partners and communities globally.

About the opportunity

We are looking for an AI Engineer - Agentic Systems Evaluation to help define how we measure, test, and improve the quality of enterprise AI systems.

As AI evolves from conversational assistants and Retrieval-Augmented Generation (RAG) into tool using agents, multi-agent systems, and autonomous business workflows, evaluating only the final response is no longer enough.

An agent may reach the right answer while choosing the wrong tool, taking unnecessary steps, retrieving incorrect context, failing to escalate to a human, or violating business rules.

This role will build the evaluation frameworks needed to understand not only whether an AI system succeeded, but how it succeeded, how reliably it can repeat that outcome, and whether the architecture is appropriate for the problem.

What you’ll get to do

Build Agentic Evaluation Frameworks

Design evaluation methodologies covering the complete AI execution lifecycle:

Intent → Planning → Retrieval → Tool Use → Reasoning → Action → Business Outcome

Evaluate systems across dimensions including:

task and business outcome accuracy
planning and decision quality
retrieval quality and groundedness
tool selection and execution
agent routing and delegation
human escalation decisions
reliability and failure recovery
safety and policy compliance
latency, token consumption, and cost

Evaluate Agentic Design Patterns

Design experiments and benchmarks that help engineering teams determine which architecture works best for a given problem.

Evaluate patterns such as:

Single-agent vs. multi-agent systems
Supervisor/router architectures
Planner–executor patterns
Sequential and parallel workflows
Tool-using agents
Human-in-the-loop workflows
Long-running agents with state and memory

Measure whether additional agent complexity actually improves task success, reliability, and business outcomes enough to justify increased latency, cost, and operational complexity.

Advance RAG & Knowledge Evaluation

Build rigorous evaluation approaches for enterprise retrieval and knowledge systems, including:

retrieval precision and relevance
groundedness and citation accuracy
source authority and freshness
chunking, metadata, and indexing strategies
semantic vs. hybrid search and reranking
permission-aware retrieval

Evaluate how retrieval decisions ultimately impact downstream agent performance, rather than treating RAG evaluation as an isolated problem.

Build Automated Evaluation & Regression Testing

Develop scalable evaluation infrastructure including:

golden and synthetic datasets
scenario and adversarial test suites
deterministic graders
LLM-as-a-Judge evaluation
human evaluation workflows
trace-based evaluation
automated regression testing

Integrate evaluations into AI development and release pipelines so changes to models, prompts, retrieval, tools, or agent architectures can be measured before reaching production.

Build Agent Trace & Failure Analysis

Analyze complete agent execution traces including planning, retrieved context, tool calls, handoffs, retries, exceptions, latency, and cost.

Develop failure taxonomies that distinguish between:

Turn production failures and user feedback into measurable regression tests and engineering improvements.

Define Production AI Quality

Establish measurable quality standards and release criteria for AI systems.

Metrics may include Task Success Rate, First-Pass Success Rate, Tool Selection Accuracy, Agent Routing Accuracy, Plan Execution Fidelity, Failure Recovery Rate, Human Escalation Accuracy, Business Outcome Accuracy, Cost / Latency per Successful Task

Help teams answer a fundamental question:

Is this AI system reliable, safe, efficient, and valuable enough to operate in production?

Skills and experience we value

Strong experience with:

Python and software engineering
LLM application development
AI/ML evaluation and experimentation
automated testing and data analysis
RAG, embeddings, hybrid search, and reranking
tool/function calling and structured outputs
agent orchestration and multi-agent workflows
AI observability and tracing
APIs and enterprise integrations

Experience with platforms or frameworks such as Agents SDK, LangGraph/LangChain, Microsoft AI Foundry, Amazon Bedrock, or similar agent platforms is valuable.

You should be comfortable working with evaluation techniques such as offline/online evals, deterministic graders, model-based graders, human evaluation, synthetic datasets, adversarial testing.

What would make you stand out

You don't stop when an agent successfully completes a task. You ask:

Did it choose the right approach?
Did it use the right tools and information?
Can it succeed consistently?
Can it recover when something fails?
Did adding more agents improve the outcome?
Could a simpler architecture achieve the same result?
What did the successful outcome cost?

You turn those questions into measurable experiments that help engineering teams build better AI systems.

Why This Role Matters

Enterprise AI is moving from systems that answer questions to systems that make decisions and perform work.

That changes how quality must be measured.

The next generation of AI evaluation must measure:

What the system understood → what it retrieved → what it decided → what it did → and whether the business outcome was correct.

This role will help establish the engineering discipline required to make those systems measurable, reliable, and production-ready.

What’s in it for you

Dayforce is fueled by the diversity of our talented employees. We are an equal opportunity employer and consider and embrace ALL individuals and what makes them unique. We believe our employees should be happy and healthy, with peace of mind and a sense of fulfillment.

We encourage individuals to apply based on their passions.

Dayforce encourages personal and professional growth. We offer excellent time away from work programs, comprehensive wellness initiatives and recognition through competitive pay and benefits.

With a commitment to community impact, including volunteer days and our charity, Dayforce Cares we provide opportunities for you to thrive both in your career and personal life. Our focus is not just on your job but on supporting you to be the best version of yourself.

This job posting is for an existing vacancy

Artificial intelligence may be used in the screening, assessment, or selection of applicants for this position.

About the Salary Ranges

Please note that the salary range mentioned in this job description should serve simply as a guide. The final compensation offered may vary based on a variety of factors, including bonuses and/or incentives, or a candidate’s experience, skills, budget and location. Our company is committed to providing a fair, equitable, and competitive package that reflects the value an individual brings to the organization.

Proficiency in English is required for this position as this role will regularly interact with English-speaking stakeholders, co-workers, managers and/or clients across the world. Further, our back office support teams, including but not limited to Human Resources, are primarily English speaking. Employees need to be able to communicate with these departments in English to appropriately administer their business relationship. Due to the significant high volume of interactions with these English-speaking co-workers, managers, stakeholders and/or clients, which is inherent to this position, it is not possible to reorganize the company's activities to avoid this requirement.

Fraudulent Recruiting

Beware of fraudulent recruiting. Legitimate Dayforce contacts will use an @dayforce.com email address. We do not request money, checks, equipment orders, or sensitive personal data during the recruitment process. If you have been asked for any of the above, or believe you have been contacted by someone posing as a Dayforce employee, please refer to our fraudulent recruiting statement found here: https://www.dayforce.com/be-aware-of-recruiting-fraud

Dayforce actively monitors all job applications to ensure authenticity. Submissions determined to be fraudulent or misleading will be declined from the recruitment process

Pour consulter cette offre d'emploi en français, veuillez utiliser le lien: https://jobs.dayforcehcm.com/fr-CA/mydayforce/alljobs

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More about this job

Responsibilities

You will design and build evaluation frameworks to measure the quality, reliability, and performance of agentic AI systems throughout their execution lifecycle. This involves creating automated regression testing, failure analysis, and benchmarking to ensure AI systems are production-ready.

Requirements

The role requires strong experience in Python, software engineering, and LLM application development, specifically with RAG and agent orchestration. Candidates should be comfortable with evaluation techniques such as offline/online evals, deterministic graders, and synthetic datasets.

Skills

Python
Software engineering
LLM application development
AI/ML evaluation
Automated testing
Data analysis
RAG
Embeddings
Hybrid search
Reranking
Tool calling
Agent orchestration
Multi-agent workflows
AI observability
Tracing
Enterprise integrations

Benefits

Time away from work programs
Wellness initiatives
Competitive pay
Charity programs

Visa sponsorship

Not detected in the job text

Keywords

AI Engineer
Agentic Systems
Python
LLM
RAG
Machine Learning
Evaluation Frameworks
Automated Testing
Data Analysis
Embeddings
Hybrid Search
Reranking
Agent Orchestration
Multi-agent Workflows
AI Observability
Tracing
Enterprise Integrations
LangGraph
LangChain
Microsoft AI Foundry
Amazon Bedrock
Synthetic Datasets
Adversarial Testing
Regression Testing
Human-in-the-loop
Cloud HCM
Software Engineering
API
Failure Analysis
Production AI

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