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Added 6 mins ago
OA
AI Automation Engineer
Outlier AI
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
Added 6 mins ago
OA
AI Agent Engineer
Outlier AI
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
Added 22 mins ago
EG
Construction Manager, Land Development
Egis Group
Edmonton, AB
- $130,000 to $170,000 CAD / year
- Full-time
…payments in a timely manner and maintains compliance with the prompt payment requirements defined by contract documents and statutory…
Added 36 mins ago
E
Senior QE + AI Engineer
enableIT
Toronto, ON
- $75 to $80 CAD / hour
- Contract
We are seeking a Senior QE + AI Engineer with around 8 years of experience in Quality Engineering, Test Automation, or Software Engineering. The role focuses on building AI-powered…
Added 36 mins ago
PI
MLOps Engineer
Planitar Inc.
Waterloo, ON
- $120,000 to $150,000 CAD / year
- Full-time
Planitar's Advanced Research Group builds the AI that turns 360° scans into floor plans. We are hiring our first MLOps Engineer to build the infrastructure that trains, evaluates, deploys…
Added 37 mins ago
P
MLOps Engineer
Planitar
Waterloo, ON
- Full-time
Planitar's Advanced Research Group builds the AI that turns 360° scans into floor plans. We are hiring our first MLOps Engineer to build the infrastructure that trains, evaluates, deploys…
Added 2 hours ago
1
Applied AI Engineer - Evaluation & Reliability
15Rock
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Applied AI Engineer - Evaluation & ReliabilityThe problem you'd own
Added 4 hours ago
SP
Software Engineering LMTS
Salesforce Partner Canada
Vancouver, BC
- Full-time
The software engineer role at Salesforce encompasses architecture, design, implementation, and testing to ensure we build products right and release them with high quality. Equally…
Added 7 hours ago
ST
AI Engineer Intern
Soft Techniques
Engineer, BC
- Internship
Description Join Soft Techniques as an AI Engineer Intern and work on cutting-edge AI systems used by real businesses. You will collaborate with our engineering team to build and improve AI…
Added 13 hours ago
WU
Technical Customer Support 2
West Unified Communications Services (formerly known as InterCall Asia Pacific)
Montreal, QC
- Full-time
Added 16 hours ago
IL
Technical Customer Support 2
Intrado Life & Safety, Inc.
Montreal, QC · Saint-Laurent, Quebec
- Full-time
Added 17 hours ago
S
Software Engineer
Spellbook
Canada
- Full-time
Added 17 hours ago
ZS
Quality Engineer / SDET – AI Chatbot Validation
Zodiac Solutions, Inc
Toronto, ON
- Full-time
Added 17 hours ago
SF
Application Security Engineer II
Spring Financial Inc.
Vancouver, BC
- Full-time
As an Application Security Engineer II, you are an experienced practitioner who works independently to secure Spring’s applications, services, and APIs. You take ownership of application…
Added 18 hours ago
KG
QE / SDET – AI Chatbot & GenAI Validation
K&K Global Talent Solutions INC.
ON · Ontario, Canada
- Full-time
We are seeking an experienced Quality Engineer (QE) / SDET specializing in AI Chatbot Validation to lead the quality assurance, accuracy testing, and response analysis of our conversational…
Added 18 hours ago
YD
Senior Machine Learning Engineer (Consulting)
Yeji Data Lab
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
We are looking for a Senior Machine Learning Engineer to design, build, and deploy scalable ML solutions for our clients. You will work across diverse projects, collaborating with…
Added 18 hours ago
II
Software Engineer
Intouch Insight
Ottawa, ON
- Full-time
Clear written communication, whether in a ticket, a design note, a code review, or a prompt
Added 18 hours ago
SF
Application Security Engineer II
Spring Financial
Vancouver, BC
- Full-time
As an Application Security Engineer II, you are an experienced practitioner who works independently to secure Spring’s applications, services, and APIs. You take ownership of application…
Added 18 hours ago
TH
AI Engineer | Full time | AI Innovations
Trillium Health Partners
ON · ON, Canada
- Full-time
Reporting to the Director, AI & Digital Planning, the AI Engineer will be responsible for using the latest AI tools to design, prototype, build, evaluate, and scale AI solutions including…
Added 18 hours ago
ZS
Quality Engineer / SDET – AI Chatbot Validation
Zodiac Solutions, Inc
Toronto, ON
- Full-time
Job TitleQuality Engineer (QE) / SDET – AI Chatbot ValidationKey Roles & Responsibilities• Validate chatbot responses for accuracy, relevance, completeness, and consistency.• Create and…
Added 19 hours ago
S
Junior AI-Accelerated Developer
Spare
Remote, Canada
- $70,000 to $101,000 CAD / year
- Full-time
- Remote
Apply checklists and QA steps before senior engineer review
Added 20 hours ago
V
Forward Deployed Engineer - Full Stack AI Solutions
VistaVu
Calgary, AB
- Full-time
As a Forward Deployed Engineer - AI Solutions at VistaVu Solutions, you will work alongside customers to understand their business problems, learn how their teams operate, and build AI…
Added 21 hours ago
M
Technical Architect- AI
Mphasis
Toronto, ON
- Full-time
Generative AI & LLMs: Gemini, Vertex AI, OpenAI, Llama, Foundation Models, Prompt Engineering, Conversational AI, Agentic AI / Multi-Agent Architectures, AI Model Evaluation and Monitoring
Added 21 hours ago
Q
ML Architect
Quantiphi
Canada
- Full-time
Prompt Engineering: Engineer prompts and optimize few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations.
Added 21 hours ago
VS
Forward Deployed Engineer - Full Stack AI Solutions
VistaVu Solutions
Calgary, AB
- Full-time
As a Forward Deployed Engineer - AI Solutions at VistaVu Solutions, you will work alongside customers to understand their business problems, learn how their teams operate, and build AI…

Morningstar

Senior Software Engineer- Applied AI

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Experience: 5+ years of software engineering experience, including production API and data-pipeline design.
Posting language: English
Posted: Sep 18, 2026

Original job description

Job Description

About Morningstar

Morningstar unites problem solvers with a clear goal: helping investors achieve their financial objectives. As a leading investment research and data company, we stand out by how we apply our insights to serve a broad range of users. Our independent investment research, powered by cutting-edge technology and design, provides tailored solutions that meet users' needs. With a strong foundation in data and innovation, we deliver comprehensive services to investors worldwide, empowering better decisions for individuals and those managing money for millions.

The Role

We are seeking a Senior Software Engineer to build the applied systems that bring AI capabilities into production: the data pipelines, LLM integrations, agentic workflows, tool interfaces, and evaluation frameworks that make AI-driven products reliable enough to depend on. This is applied engineering rather than research; success is measured in shipped, maintainable systems. You may be a strong fit if you love working within a landscape that changes quickly, creating durable architectures with swappable parts, so new models and techniques are adopted on evidence.

The role encompasses fluency across cloud architecture and local model inference, evaluation design, agentic workflows and orchestration, API and tool design, and AI-assisted data enrichment. It also requires the engineering rigor to establish reliable sources of truth, detect regressions, and recognize when a deterministic solution is more appropriate than an AI-driven one.

Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.

This position is based in our Toronto office. We follow a hybrid policy of at least 4 days onsite.

Job Responsibilities

Integrate with hosted LLM inference (via centralized model gateway infrastructure) for extraction, classification, and agent orchestration workloads; evaluate open-weight models against hosted options for cost and performance tradeoffs.

Design and maintain adapters that sync source systems (CMS, event platforms, editorial, research libraries) into a governed dataset without duplicating source-of-record logic.

Build and maintain an eval harness: curate golden questions, catch regressions before release, and treat eval results as the gate for shipping.

Design MCP tools and API/GraphQL interfaces that separate "fuzzy" retrieval (ranked candidates, confidence scores) from "exact" governed lookups (deterministic, provenance-carrying).

Build and extend the pipeline that validates, resolves, and versions governed entities into a serving layer.

Design and operate LLM-driven extraction and classification agents that propose structured data for human review rather than auto-publishing unreviewed AI output.

Own structured content modeling against a headless CMS, including schema and versioning decisions that other teams depend on.

Instrument pipelines and served surfaces for freshness, adoption, and answer-quality telemetry.

Participate in and help run the weekly eval review and the biweekly skill-library session, harvesting reusable agent tooling for the team.

Mentor engineers being reskilled into applied AI work, particularly around eval design and agentic-coding practices.

Contribute governance and vocabulary decisions upstream to org-wide standards where relevant, rather than duplicating them.

Qualifications

5+ years of software engineering experience, including production API and data-pipeline design.

Comfort working with agentic coding tools daily as a core part of the workflow.

Hands-on production experience integrating LLMs: Skills, MCP, RAG, structured outputs, and tool/function calling.

Strong proficiency in Python across eval tooling, service-level code, and API development (FastAPI or similar), plus working proficiency in TypeScript/Node.js for application integrations.

Experience deploying and operating production services in AWS (or equivalent), including containerized workloads and infrastructure-as-code.

Security and privacy judgment in AI systems: handling sensitive data appropriately, and designing against failure modes like prompt injection, data leakage through prompts, and unsafe or unattributed model output.

Experience operating production systems against latency, reliability, and cost targets, including token-cost management for inference workloads.

Evaluation literacy: you can describe an eval you built, what it caught, and how you handled canonical truth, variance, and regression cases.

Experience with REST/GraphQL API design.

Solid understanding of data pipeline patterns: idempotency, versioning, and staged architectures.

Explicitly not required: formal model training or ML research credentials (e.g., pretraining, fine-tuning research). This is an applied systems role; we're looking for builders, not researchers.

Strong written communication. You can write a clear design doc, explain a tradeoff to a non-engineer, and document decisions others will build against.

Creative problem solver comfortable operating in ambiguity, with a builder's bias toward shipping over ceremony.

Nice to have

Experience evaluating or benchmarking open-weight models for cost/performance (inference-time evaluation, not training).

Experience with cloud-hosted inference services (e.g., Amazon Bedrock, Azure AI/Cognitive Services) and centralized LLM gateways (e.g., LiteLLM).

Experience with headless CMS platforms and structured content modeling.

Experience in a regulated or compliance-sensitive domain where provenance and auditability matter.

Total Cash Compensation (Base Plus Bonus Target) : 101,800.00 - 207,000.00 CAD

If you receive and accept an offer from us, we require that personal and any related investments be disclosed confidentiality to our Compliance team (days vary by region). These investments will be reviewed to ensure they meet Code of Ethics requirements. If any conflicts of interest are identified, then you will be required to liquidate those holdings immediately. In addition, dependent on your department and location of work certain employee accounts must be held with an approved broker (for example all, U.S. employee accounts). If this applies and your account(s) are not with an approved broker, you will be required to move your holdings to an approved broker.

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More about this job

Responsibilities

The role involves building and maintaining applied AI systems, including data pipelines, LLM integrations, and agentic workflows to ensure reliable production performance. You will also design evaluation harnesses, manage structured content, and mentor engineers on AI-driven development practices.

Requirements

Candidates must have at least 5 years of software engineering experience with strong proficiency in Python and production-level API development. Hands-on experience with LLM integration, cloud infrastructure, and data pipeline design is required, along with excellent written communication skills.

Skills

Python
TypeScript
Node.js
LLM integration
AWS
FastAPI
GraphQL
REST API
Data pipelines
Agentic workflows
Cloud architecture
Infrastructure-as-code
Evaluation design
System architecture
Structured content modeling
Telemetry

Benefits

Hybrid work environment
Flexibility

Visa sponsorship

Not detected in the job text

Keywords

Software Engineering
Applied AI
LLM
Python
TypeScript
Node.js
AWS
FastAPI
GraphQL
REST
Data Pipelines
Agentic Workflows
Cloud Architecture
Infrastructure-as-Code
Evaluation Harness
Telemetry
Headless CMS
Prompt Engineering
RAG
MCP
Containerization
System Reliability
Token-cost Management
Governance
Provenance
Auditability
Investment Research
Data Enrichment
Regression Testing
Version Control

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