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Added 15 days ago
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Senior software engineer: Applied AI
Morningstar
Toronto, ON
- Full-time
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,…
Added 15 days ago
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Member of Technical Staff (General Software Engineer, Infrastructure)
Perplexity
Toronto, ON
- $220,000 to $405,000 USD / year
- Full-time
Strong software engineering skills in Python or other systems or backend languages such as Go, Rust, C++, or Java.
Added 15 days ago
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Lead Software Engineer – AI, Data Visualization & Platform
Astucemedia
Montreal, QC
- Full-time
As Lead Software Engineer – AI, Data Visualization & Platform, you will help bridge architectural vision, product innovation, advanced visualization, and day-to-day engineering execution.
Added 15 days ago
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Software Development Engineer
Nokia
Ottawa, ON
- Full-time
Experience with scripting languages such as Python or Shell scripting is desirable.
Added 15 days ago
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Ingénieur(e) de données principal(e) | Senior Data Engineer
ValPay
Montreal, QC · Saint-Laurent, QC
- Full-time
As a Senior Data Engineer, you'll design, build and operate the data platform behind Valpay's analytics, reporting, product development and day-to-day operational decisions. Payments data…
Added 15 days ago
GS
Software Engineer II
Guidewire Software
Toronto, ON · Mississauga, ON
- Full-time
Guidewire’s development team is looking for a smart, proactive, and results-oriented Software Engineer II to build elegant solutions for the property & casualty insurance industry’s…
Added 15 days ago
Associate, DevOps Engineer
BMO
Toronto, ON · FCP
We are seeking an experienced DevOps Engineer to join our Data Cognition Team at BMO Capital Markets. In this role, you will design, build, and maintain robust DevOps pipelines and…
Added 15 days ago
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Senior Data Engineer – Capital Markets
Synechron
Mississauga, ON
- Full-time
Seeking a motivated, proactive, and reliable Data Engineer to join the Data Sourcing and Analytics team. This role will support the design, development, implementation, and ongoing…
Added 15 days ago
Cybersecurity Firmware Engineer
indie
Toronto, ON
The Senior Cybersecurity Firmware Engineer is responsible for the security architecture and secure implementation of firmware running on indie’s SoCs. In this role, you will partner with…
Added 15 days ago
EG
Rail Requirements Management Specialist
Egis Group
Toronto, ON
- $150,000 to $180,000 CAD / year
- Full-time
…on Systems Engineering) guideline, AREMA (American Railway Engineer and Maintenance of way Association) Manual of Railway Engineering, Agency Design Standards, NFPA-130, National Electric…
Added 15 days ago
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Senior Software Engineer
Elective
Vancouver, BC
- Full-time
As a Senior Software Engineer at Elective, nothing you build is invisible and you'll be in the room for planning, speccing, and debating architectural direction rather than just receiving…
Added 15 days ago
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Technology Lead - GenAI Lead
Infosys
Mississauga, ON
- Full-time
…and Agentic AI frameworks. This role is ideal for a mid-level engineer with strong technical depth, a passion for building, and the ability to lead small teams or workstreams in a…
Added 15 days ago
I
Technology Lead - GenAI Lead
Infosys
Mississauga, ON
- Full-time
…and Agentic AI frameworks. This role is ideal for a mid-level engineer with strong technical depth, a passion for building, and the ability to lead small teams or workstreams in a…
Added 15 days ago
I
Technology Lead - GenAI Lead
Infosys
Mississauga, ON
- Full-time
…and Agentic AI frameworks. This role is ideal for a mid-level engineer with strong technical depth, a passion for building, and the ability to lead small teams or workstreams in a…
Added 15 days ago
I
Technology Lead - GenAI Lead
Infosys
Mississauga, ON
- Full-time
…and Agentic AI frameworks. This role is ideal for a mid-level engineer with strong technical depth, a passion for building, and the ability to lead small teams or workstreams in a…
Added 15 days ago
I
Technology Lead - GenAI Lead
Infosys
Mississauga, ON
- Full-time
…and Agentic AI frameworks. This role is ideal for a mid-level engineer with strong technical depth, a passion for building, and the ability to lead small teams or workstreams in a…
Added 15 days ago
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Intermediate Python Engineer
Citi
Mississauga, ON
- Full-time
4+ years of hands-on experience applying deep professional experience in Python for backend development, with the ability to design and build scalable, high-performance systems.
Added 15 days ago
CG
Senior Data Platform Engineer - Zonda - Toronto, ON
CoStar Group
Toronto, ON
- $140,000 to $170,000 CAD / year
- Full-time
Senior Data Platform Engineer: Senior Data Platform Engineer – Zonda – Toronto, ON
Added 15 days ago
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Senior Data Quality Engineer - Zonda - Toronto, ON
CoStar Group
Toronto, ON
- $120,000 to $150,000 CAD / year
- Full-time
Senior Data Quality Engineer: Senior Data Quality Engineer – Zonda – Toronto, ON
Added 15 days ago
CG
Senior Data Engineer - Zonda - Toronto, ON
CoStar Group
Toronto, ON
- $120,000 to $150,000 CAD / year
- Full-time
Senior Data Engineer: Senior Data Engineer – Zonda – Toronto, ON
Added 15 days ago
AI Engineer
NetBrain
Toronto, ON
We’re looking for a Senior AI Engineer to design and build production-grade agent and RAG systems that power intelligent, reliable automation across our platform. This role combines…
Added 15 days ago
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Python Developer
Ascendion
Toronto, ON
- Full-time
We are looking for a Senior Software Engineer with experience in building highly scalable solutions based on a microservices architecture. As a Senior Software Engineer, you will be working…
Added 15 days ago
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Architect - Machine Learning
Quantiphi
Canada
- Full-time
Lead Agentic Workflows: Engineer the orchestration layers for agentic AI, including planning, tool-use, and multi-step reasoning capabilities.
Added 15 days ago
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Full-Stack Engineer, AI Platform
Thumbtack
Remote, Canada
- Full-time
- Remote
…and why. Without that, automation stays stuck in pilots. This engineer owns the product surface that turns agent capability into something teams will actually rely on for business-critical…
Added 15 days ago
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Senior Engineer
Experis
Toronto, ON · Greater Toronto Area, Canada
- $110 to $180 CAD / hour
- Contract
Senior Engineer / Architect – Electronic Trading, Market Data & Smart Order Routing

NetBrain

AI Engineer

Toronto, ON, Canada

Apply About employer

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Job details

Experience: 3+ years of experience in software engineering, machine learning, or applied AI, including 2+ years building, deploying, and operating production-
Posting language: English
Posted: Sep 18, 2026

Original job description

Founded in 2004, NetBrain is the leader in no-code network automation. Its ground-breaking Next-Gen platform provides IT operations teams with the ability to scale their hybrid multi-cloud connected networks by automating the processes associated with Diagnostic Troubleshooting, Outage Prevention and Protected Change Management. Today, over 2,500 of the world’s largest enterprises and managed services providers leverage NetBrain’s platform.

What We Need

We’re looking for a Senior AI Engineer to design and build production-grade agent and RAG systems that power intelligent, reliable automation across our platform. This role combines hands-on engineering with system-level thinking - owning everything from architecture and evaluation to scalability, observability, and reliability in production. The ideal candidate thrives in ambiguity, moves quickly from prototype to production, and brings a strong focus on quality, safety, and real-world impact.

What You'll Do

Agent Platform Architecture

Design and implement core capabilities for an enterprise-grade Agent platform, including orchestration patterns such as ReAct, Plan-and-
Execute, and Supervisor, as well as tool execution, context and memory management, and safety guardrails.
Design enterprise-grade Agent execution and governance mechanisms, including Human-in-the-Loop approval workflows, multi-tenant
permission isolation, policy enforcement, and secure execution controls.
Build reusable Agent Skills, standardized tool interfaces, and a scalable tool ecosystem deeply integrated with NetBrain platform
capabilities and business workflows.

LLM and Model Optimization

Design and implement LLM post-training strategies, including domain-specific Supervised Fine-Tuning (SFT), DPO/RLHF-based
preference alignment, and parameter-efficient fine-tuning techniques such as LoRA, to continuously improve model performance in the
network operations domain.
Build an Agent self-learning feedback loop that converts production execution traces, user feedback, and evaluation results into high-
quality datasets for continuously improving prompts, skills, models, and retrieval strategies.
Analyze and optimize LLM behavior across areas such as instruction following, tool calling, structured output generation, contextual
understanding, reasoning stability, and hallucination mitigation.

Evaluation, Reliability, and Observability

Build production-grade LLM and Agent evaluation frameworks and automated regression pipelines, including benchmark datasets,
deterministic checks, LLM-as-a-Judge, tool-call validation, retrieval-quality evaluation, and end-to-end task success metrics.
Establish release quality gates and hallucination-detection mechanisms for AI features to prevent significant accuracy, reliability, and
performance regressions from reaching production.
Build comprehensive AI system observability capabilities, including distributed tracing, structured logging, metrics, dashboards, and
alerting.
Rapidly diagnose and resolve production AI failures, including hallucinations, incorrect tool selection, invalid tool parameters, Agent
loops, retrieval-quality degradation, structured-output failures, latency regressions, and unexpected model behavior changes.

Production Engineering and Technical Execution

Design and implement highly reliable backend services for production AI and Agent workloads, including asynchronous and concurrent
processing, retries, timeouts, caching, rate limiting, and fault isolation.
Continuously optimize latency, throughput, token consumption, and infrastructure cost to meet platform SLA requirements and support
large-scale production workloads.
Independently diagnose and resolve complex AI system issues spanning prompts, models, RAG, tools, Agent workflows, backend
services, and infrastructure.
Lead technical design for critical modules and system-level capabilities, ensuring solutions align with platform architecture, security
requirements, engineering standards, and product requirements.
Drive technical improvements based on production data, evaluation results, and benchmarks, and collaborate closely with Engineering,
Product, QA, and other teams to deliver solutions into production.

Applied Research and Technical Strategy

Prototype, benchmark, and productionize emerging technologies such as GraphRAG, Knowledge Graphs, MCP, LLM Post-Training, and
Agent Self-Learning to improve grounding, multi-hop reasoning, and domain expertise.
Continuously evaluate Agent frameworks and supporting infrastructure, including LangChain, LangGraph, AutoGen, and LlamaIndex,
and provide technical recommendations for platform architecture evolution and product technology strategy.
Stay current with developments in LLM and Agent technologies and rapidly translate promising technologies into measurable, testable,
and production-ready engineering capabilities.

What You Bring

Bachelor's degree or higher in Computer Science, Artificial Intelligence, Electrical Engineering, or a related technical field. Master's or Ph.D.
preferred; equivalent practical experience will also be considered.
3+ years of experience in software engineering, machine learning, or applied AI, including 2+ years building, deploying, and operating production-
grade LLM or Agent applications. Must have delivered at least one LLM-powered feature end-to-end and owned its ongoing operation and
improvement after production launch.
Deep understanding of Agent architectures and LLM behavioral characteristics, including instruction following, tool-calling behavior, and context
sensitivity, with hands-on experience building multi-step workflows involving reasoning, tool execution, state management, structured outputs,
validation, and error recovery.
Proven ability to diagnose and resolve production LLM/Agent failures, including hallucinations, incorrect tool calls, retrieval-quality degradation,
Agent loops, structured-output failures, latency regressions, and regressions introduced by prompt or model changes.
Strong Python and distributed backend engineering skills, including API and service development, asynchronous and concurrent programming,
retries, timeouts, caching, rate limiting, testing, logging, and cross-service performance debugging.
Hands-on experience designing evaluation systems for LLM applications, including dataset construction, metric definition, regression testing, and
release quality gates.
Strong understanding of security risks associated with LLM and Agent applications, including prompt injection, data leakage, unsafe tool
execution, permission boundaries, and uncontrolled Agent autonomy.
Ability to independently design, implement, debug, deploy, and operate complex production systems.

Preferred Qualifications

Strong experience with RAG and advanced retrieval systems, including embeddings, vector and hybrid search, reranking, chunking strategies,
grounding and citation mechanisms, as well as multi-hop retrieval, Knowledge Graphs, or GraphRAG.
Familiarity with Agent frameworks such as LangGraph, LangChain, AutoGen, and LlamaIndex, as well as standardized protocols such as MCP
(Model Context Protocol) for connecting Agents with external tools and systems. A strong understanding of the underlying architecture is more
important than expertise in any specific framework.Experience designing Agent runtime mechanisms, including Human-in-the-Loop workflows such as risk classification, approval, interruption, pause
/resume, as well as context management for long-running Agent workflows, including state persistence, history compression, and memory
systems.
Experience with LangSmith or similar LLM observability and evaluation platforms.
Experience with LLM fine-tuning, including LoRA or other parameter-efficient fine-tuning techniques.
Experience applying LLM technologies to networking, infrastructure, cybersecurity, observability, or other complex technical domains.
Fluent in both English and Chinese, with strong cross-regional communication and collaboration skills.

What We Offer

Our comprehensive compensation package is vital in how we recognize our people for the impact they make on us reaching our goals as a company.

For this role, the estimated base is CAD $130,000 - CAD $165,000 + Bonus. The actual salary may vary based on a range of factors, including market and individual qualifications objectively assessed during the interview process.

The range listed above is a guideline and may be modified. People Experience offers a comprehensive benefits package in addition to cash compensation that includes but is not limited to RRSP and medical/dental coverage. Speak with your Recruiter for more details on our Total Rewards philosophy.

NetBrain invites all interested and qualified candidates to apply for employment opportunities.

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or other characteristics protected by law.

If you have a disability that prevents or limits your ability to use or access the site, or if you require any other accommodation in the application process due to a disability, you may request a reasonable accommodation. To make a request, please contact our People Team at: people@netbraintech.com and we will be happy to assist you.

In compliance with applicable laws, NetBrain conducts holistic, individual background reviews in support of all hiring decisions.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

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More about this job

Responsibilities

Design and build production-grade agent and RAG systems to power intelligent network automation. Develop evaluation frameworks, observability tools, and self-learning feedback loops to ensure reliability and performance in production.

Requirements

Requires a bachelor's degree or higher in a technical field and at least 3 years of experience in software engineering or applied AI. Candidates must have hands-on experience deploying LLM-powered features and strong proficiency in Python and distributed backend engineering.

Skills

Python
LLM
Agent architectures
RAG
Machine learning
Distributed systems
Fine-tuning
Prompt engineering
Evaluation frameworks
Observability
API development
Cloud computing
Data structures
Software engineering
System architecture
Networking

Benefits

RRSP
Medical coverage
Dental coverage

Visa sponsorship

Not detected in the job text

Keywords

AI Engineer
No-code
Network automation
Hybrid multi-cloud
Agent platform
RAG
LLM
ReAct
Supervised Fine-Tuning
DPO
RLHF
LoRA
GraphRAG
Knowledge Graphs
LangChain
LangGraph
AutoGen
LlamaIndex
MCP
Python
Distributed systems
Observability
Latency optimization
Prompt engineering
Hallucination mitigation
API development
Cybersecurity
Infrastructure
Data engineering
Software engineering

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