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Added 1 min ago
GM
Software Engineering Manager - Vehicle Data Platform
General Motors
Oshawa, ON · Markham, ON
- Full-time
The Data Engineering organization at General Motors is building a unified Vehicle Data Platform that moves data and configuration between vehicle ECUs and the cloud. Our team is the only…
Added 1 min ago
Bilingual Senior Specialist, Software Engineering (Environment Management)
CMHC - SCHL
Ottawa, ON · Montreal, QC
Join the Platform Engineering team, in the Senior Specialist, Software Engineering & Environment Management position, where we’re modernizing how CMHC builds and operates software…
Added 1 min ago
AG
Manager, ESG Reporting & Compliance
Alamos Gold Inc.
Toronto, ON
- Full-time
Identify and implement opportunities to strengthen reporting processes, data quality, system capabilities, and disclosure practices in line with industry leading practices and stakeholder…
Added 1 min ago
Software Development Engineer II, S3 Shard Store
Amazon
Vancouver, BC
…talented engineers and leaders to hand deliver changes to our system that delight our customers, and in turn improve the lives of their…
Added 14 mins ago
BS
Senior Business Systems Analyst
Brainhunter Systems Ltd
Toronto, ON
- Contract
Minimum 5-10+ years of experience as a Business Systems Analyst, Technical Business Analyst, Solution Analyst or in a comparable role delivering complex digital products or platforms.
Added 14 mins ago
AI
Full Stack Engineer
Apptoza Inc.
Toronto, ON
- Contract
Build Gen AI system frameworks, Prompt Engineering, including designing and refining prompts to optimize LLM outputs, implementing Gen AI systems into production.
Added 14 mins ago
K
Senior Product Manager - Social Experience
Kraken
Canada
- Full-time
…most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial…
Added 14 mins ago
PL
Infrastructure Engineer – Network, Security & IoT/OT
PineQ Lab Technology
Montreal, QC
- Contract
…offices. This will include working closely with many technology engineering teams such as Networks, SecDesign, Proxy, Risk and Windows, in order to implement systems that meet the Firms…
Added 14 mins ago
IG
Instrumentation & Controls Engineer
Insight Global
Regina, SK · Greater Regina Metropolitan Area
- Contract
Reporting to the Lead I&C Engineer, this individual will act as part of the owner's engineering team, providing technical oversight of engineering, design, automation, and instrumentation…
Added 14 mins ago
PI
Relays Electrical Engineer IV
People Integra (A Business Integra Group Company)
Markham, ON
- Contract
Support power system simulation and microgrid-related engineering activities, including RTDS or equivalent platforms.
Added 14 mins ago
T
IAM (SailPoint) Software Engineer
Teamrecruiter.com
Ottawa, ON
- Contract
…organization. The successful candidate will have strong software engineering capabilities combined with hands-on experience in IAM technologies, identity lifecycle management,…
Added 14 mins ago
AS
System Designer
AgileGrid Solutions
Canada
- Full-time
As a Jetson System Designer, you will play a crucial role in transforming signed customer agreements into detailed, installable plans. Your primary responsibility will be to conduct virtual…
Added 14 mins ago
H
Bilingual QE Engineer – Contact Center
HRConnects
Toronto, ON
- Full-time
As a QE with CC Tools & Contact Center Platforms, you will serve as a vital technical leader responsible for testing, automation, and support of contact center platforms. You’ll leverage…
Added 14 mins ago
LC
Supply Chain, Business Intelligence Developer
Loblaw Companies Limited
Brampton, ON
- Full-time
Support business users with systems and process related inquiries to help troubleshoot potential system errors or process gaps and to train users on forecasting standard methodologies
Added 16 mins ago
YI
Software Developer - Internal Automation
YuJa Inc.
Toronto, ON · North York, Ontario
- $80,000 to $90,000 CAD / year
- Full-time
This is an excellent opportunity for someone who enjoys solving complex technical problems, building internal platforms, automating repetitive processes, and working at the intersection of…
Added 16 mins ago
YI
AI Engineer
YuJa Inc.
Toronto, ON · North York, Ontario
- Full-time
…We’re looking for a passionate AI Engineer to join our core engineering team and help design, build, and scale our AI infrastructure and…
Added 16 mins ago
AM
Logistics Coordinator
Avl manufacturing
Hamilton, ON
- Up to $25 CAD / hour
- Full-time
Founded in 1998, AVL has grown into a North American leader in turnkey engineering, manufacturing, and assembly solutions. For over 25 years, we've combined in-house mechanical, structural,…
Added 44 mins ago
RH
Java Software Engineer
Robert Half
Toronto, ON
- $100,000 to $130,000 CAD / year
- Full-time
…senior leaders, product teams, operations, compliance, and engineering stakeholders to help build and enhance critical payment platforms supporting ACH, Wires, Real-Time Payments (RTP),…
Added 1 hour ago
M
Senior Cloud Engineer -Hybrid
Manulife
Toronto, ON · Waterloo, ON
- Full-time
…this role, you'll design, build, automate, and optimize cloud platforms while partnering closely with engineering teams to deliver secure, reliable, and efficient…
Added 1 hour ago
R
Architecte de données / Data Architect
RTX
Longueuil, QC
- Full-time
Added 1 hour ago
TI
Test Lead - Healthcare
Teckhorizon Inc
Toronto, ON
- Contract
…testing strategy, API validation, automation, and healthcare system integrations while ensuring compliance with healthcare interoperability standards such as HL7 FHIR and SMART on FHIR.…
Added 1 hour ago
ÉD
Postdoctoral Fellow – Automation and Decision Support, Distributed Systems and Multi-Agent Systems – C5I Centre
École de technologie supérieure
Montreal, QC
- $80,000 to $88,000 CAD / year
- Full-time
Design, model, and validate the integration of heterogeneous subsystems into a unified system, including interoperability, communication, and data synchronization.
Added 1 hour ago
ZS
Python Full-Stack Developer with Django & AI Experience
Zodiac Solutions, Inc
Toronto, ON
- Full-time
Experience with agent frameworks and orchestration platforms
Added 1 hour ago
TR
2027 January Project Engineering Co-op Student
Teck Resources Limited
Kamloops, BC
- $4,833 to $5,592 CAD / month
- Full-time
For this position we are specifically targeting students who have a background in Engineering. This exciting opportunity will allow students to acquire the knowledge and skills required to…
Added 1 hour ago
A
Software Engineer (Python + Frontend)
Apptad
Montreal, QC
- Contract
Role focus: Full-stack engineering for surveillance technology platforms and business-facing applications.

Dayforce

AI Engineer Sr

Canada

Apply About employer

Applications open in a new tab.

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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