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Added 3 months ago
EB
Senior AI Platform Operations Engineer
EQ Bank | Canada's Challenger Bank
Toronto, ON
- Full-time
The Senior AI Platform Operations Engineer is accountable for the reliability, operability, and controlled enablement of the organization’s AI platform.
Added 3 months ago
CF
Senior AI Engineer
CI Financial
Toronto, Ontario
- Full-time
CI Financial is seeking an experienced and technically strong Senior AI Engineer to join our Data, AI & Analytics (DNA) team. This role focuses on the applied use of Generative AI and…
Added 3 months ago
Network Engineer, Operations & Support
Meta
Quinte West, Ontario
Meta is seeking a Network Engineer to support the reliability and performance of its production network infrastructure. In this role, you will own operational responsibilities across…
Added 1 month ago
R
Principal Data Science and AI Engineer
RBC
Toronto, ON
- Full-time
As a Principal AI Engineer, you will be at the helm of developing, deploying, and owning the strategic direction of advanced AI systems, including autonomous AI agents that leverage and…
Added 1 month ago
Q
Firmware Engineer, Staff
Qualcomm
Toronto, ON
- Full-time
…a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or…
Added 1 month ago
SC
Sr. Mixed Signal ASIC Systems Engineer
SiTime Corporation
Ottawa, ON
- $96,190 to $132,270 CAD / year
- Full-time
As a Systems Engineer we are the first in line to work on brand new devices from Silicon Designers before they get into the hands of customers. The devices that SiTime Canada works on are…
Added 1 month ago
E
Senior Software Engineer, AI Platform
eBay
Toronto, ON
- Full-time
…maintaining high quality and performance. As a Senior Software Engineer – Backend, you will architect and develop core platform services, solving complex technical problems and shaping…
Added 1 month ago
RB
Principal Data Science and AI Engineer
Royal Bank of Canada
Toronto, ON
- Full-time
As a Principal AI Engineer, you will be at the helm of developing, deploying, and owning the strategic direction of advanced AI systems, including autonomous AI agents that leverage and…
Added 1 month ago
DS
Ingénieur Analytique / Analytics Engineer
Data Sciences
Montreal, QC
- Full-time
3+ années expérience en rédaction de code SQL en tant qu’ingénieur analytique (analytics engineer), analyste de données (data analyst), ingénieur de données (data engineer) ou autres rôles…
Added 1 month ago
EN
Senior Full Stack Developer – Generative AI & Autonomous Agents - Toronto, Canada - Hybrid (10038)
Extreme Networks
Toronto, ON
- Full-time
We are seeking an experienced Senior Full Stack Developer with deep expertise in backend systems (Java, Python, microservices) and modern UI frameworks (Angular, React) to join our…
Added 1 month ago
R
Principal Data Science and AI Engineer
RBC
Toronto, ON
- Full-time
As a Principal AI Engineer, you will be at the helm of developing, deploying, and owning the strategic direction of advanced AI systems, including autonomous AI agents that leverage and…
Added 1 month ago
RB
Data Scientist and AI Engineer Autonomous AI Agents (LLMs and Deep Learning)
Royal Bank of Canada
Toronto, ON
- Full-time
…language models (LLMs) and other deep learning models. As an AI Engineer, you will play a pivotal role in building intelligent systems that transform the way we operate and deliver…
Added 1 month ago
N
IP Routing App Engineer Co-op/Intern
Nokia
Ottawa, ON
- Full-time
Position: IP Routing App Engineer Co-op/Intern
Added 1 month ago
R
Data Scientist and AI Engineer Autonomous AI Agents (LLMs and Deep Learning)
RBC
Toronto, ON
- Full-time
…language models (LLMs) and other deep learning models. As an AI Engineer, you will play a pivotal role in building intelligent systems that transform the way we operate and deliver…
Added 1 month ago
SS
Generative AI Engineer
Soho Square Solutions
Montreal, QC
- Contract
We are seeking a Cloud & AI Engineer to design, build, and maintain enterprise-scale multi-cloud infrastructure across Azure and AWS while enabling cloud-native AI solutions and agentic AI…
Added 1 month ago
ST
Lead Quantitative Financial Engineer
SS&C Technologies
Toronto, ON
- Full-time
Training: Hands-On, Team-Customized, including SS&C Learning Institute
Added 1 month ago
UT
Senior DevOps Engineer
Unity Technologies
Montreal, QC
- Full-time
Are you a visionary DevOps Engineer with a keen focus on driving modern infrastructure through Automation, Infrastructure-as-Code (IaC), and advanced CI/CD practices? At Unity Technologies…
Added 2 months ago
N
Firmware Integration and Test Engineer
Nokia
Ottawa, ON
- Full-time
As an Optical Firmware Integration Test (SIT) Engineer at Nokia, you'll play a crucial role in enhancing our optical pluggable firmware development and verification process. You will…
Added 2 months ago
Staff Software Engineer, Fullstack
Fivetran
Toronto, ON
We’re looking for a Staff Software Engineer, Fullstack to join our Reverse ETL product engineering team.
Added 3 months ago
GC
Forward Deployed Engineer (AI Practice)
Greenlight Consulting
North York, Ontario
- $90,000 to $130,000 CAD / year
…measurable business value. We combine deep consulting expertise with hands-on engineering to bridge the gap between strategy and…
Added 3 months ago
Senior Agentic Software Engineer
Lantern
Edmonton, AB
As a Senior Software Modernization Engineer, you'll work directly with enterprise software engineering organizations to help modernize applications, improve developer productivity,…
Added 4 months ago
S
Senior Software Engineer, Notebooks
Snowflake
Toronto, ON
- $245,250 to $295,250 CAD / year
- Full-time
Drive high-impact initiatives that span our product areas and full tech stack, including golang and Python on the backend and TypeScript/React on the frontend.
Added 1 month ago
Staff Full stack Engineer [CONSUMER]
HelloFresh
Toronto, ON
We are looking for an engineer to help implement solutions & write beautiful code, working with various team members as we build out our consumer facing applications & the infrastructure…
Added 4 months ago
I
Senior Data Engineer
iQmetrix
Winnipeg, MB
- Full-time
The ideal candidate is a hands-on engineer with strong production experience in Python, SQL, and distributed compute environments. They should have deep familiarity with modern lakehouse…
Added 4 months ago
I
Senior Data Engineer
iQmetrix
Regina, SK
- Full-time
The ideal candidate is a hands-on engineer with strong production experience in Python, SQL, and distributed compute environments. They should have deep familiarity with modern lakehouse…

Greenlight Consulting

Forward Deployed Engineer (AI Practice)

North York, ON, Canada

$90,000 to $130,000 CAD / year

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Job details

Pay: $90,000 to $130,000 CAD / year
Experience: Intermediate 3-5 year’s experience
Posting language: English
Posted: Jul 7, 2026

Original job description

Greenlight helps organizations solve complex business challenges through intelligent automation, agentic AI, and custom technology solutions.

Our teams work directly with clients to understand their operations, identify opportunities, and rapidly build solutions that create measurable business value. We combine deep consulting expertise with hands-on engineering to bridge the gap between strategy and execution.

We’re building a future where consultants and engineers work alongside AI to deliver faster outcomes, stronger businesses, and transformative customer experiences. Anthropic’s Claude is embedded across how we design, build, and validate solutions - and this role is at the technical frontier of that capability.

What makes a star at Greenlight?

· Builder's instinct, architect's discipline

· The most technically credible person in the room

· AI-native at depth - you know how LLMs fail and build around it

· Client-embedded, not arm's length

· Commercially aware - scope, economics, outcomes

The Role

The Forward Deployed Engineer is Greenlight’s most senior technical delivery role. You design, build, and operationalize AI agent workflows and intelligent automation solutions - embedded directly in client environments, working alongside their teams to deliver production-grade solutions that create measurable business outcomes.

This is not a back-office engineering role. You will be in client discovery sessions, presenting architectures to IT leadership, deploying AI agents against real enterprise systems, and building the reusable skills and accelerators that make Greenlight faster and more differentiated on every subsequent engagement. You are expected to be the most technically credible person in the room - combining deep AI fluency with the consulting presence of a senior practitioner.

You work at the frontier of agentic AI - designing and building Claude-powered solutions, connecting AI agents to enterprise systems through MCP integrations, and producing the technical documentation that the delivery team and the client can both stand behind. The platform is Anthropic Claude. The problem space is complex, regulated, and high-stakes. The bar is production-grade.

At a Glance

Reports To	AI Practice Lead
Works Closely With	Pre-Sales SE, Automation Business Consultant, AI Delivery Engagement Manager
Client Interaction	Yes - C-suite, IT architects, operations leaders, technical teams
Travel Requirement	Regular client travel required - discovery, workshops, POC delivery, go-live
Platform Focus	Anthropic Claude (Cowork + Skills), MCP, Python / Node.js, REST APIs
Seniority	Intermediate 3-5 year’s experience
Location	Onshore Canada - Toronto preferred
Engagement Type	Hybrid - onsite client-facing with remote delivery phases

What You’ll Do

Solution Architecture & Technical Discovery

Lead technical discovery workshops with C-suite, IT architects, and operations leaders - identifying high-value AI automation opportunities and translating complex operational workflows into executable solution architectures
Design end-to-end AI agent architectures using Anthropic’s Claude platform (Cowork and Skills framework), aligned to client infrastructure, security requirements, and compliance constraints
Translate business requirements into agent-based automation blueprints: what the AI owns, what stays human, how exceptions route, and how the two coordinate
Assess the right solution architecture for each use case - knowing when a Claude agent is the answer, when a procode integration is cleaner, and when a simpler rules-based approach is more appropriate than AI
Present technical architectures to executive and non-technical audiences with clarity, confidence, and the credibility that comes from having built things like this before

AI Agent Build & Delivery

Engineer production-ready AI agent workflows using Claude Cowork and the Skills framework - built to a standard that holds up in regulated, enterprise production environments
Develop and configure Claude Skills: structured instruction sets, templates, validation rules, and reference documents that encode client-specific processes and quality standards into repeatable AI agent behaviour
Build and maintain MCP connectors that integrate AI agents with enterprise systems - CRMs, ERPs, document management platforms, core banking systems, and custom APIs - handling authentication, data mapping, error handling, and audit requirements
Implement advanced LLM patterns where required: retrieval-augmented generation (RAG), chain-of-thought reasoning, tool use, multi-agent orchestration, and structured output validation
Conduct output validation, performance tuning, and safety testing of deployed AI agents before client go-live - quality is non-negotiable when outputs go to regulators or clients

Procode & Integration Engineering

Write production-quality Python or Node.js to extend platform capability - data pipelines, transformation logic, webhook handlers, API wrappers, and back-end components that sit outside the automation itself
Build, test, and maintain integrations with enterprise platforms (Salesforce, Jira, DocuSign, SharePoint, ServiceNow, and others) using REST, GraphQL, OAuth 2.0, and enterprise authentication patterns
Design and implement monitoring, logging, and observability into deployed solutions so operations teams can diagnose issues without requiring an engineer in the room
Apply cloud platform fundamentals (AWS, Azure, or GCP) to deployment, scaling, and infrastructure decisions where the engagement requires it

Accelerators & Practice Development

Build and continuously refine reusable Skills libraries, automation templates, and reference architectures that make every subsequent Greenlight engagement faster and more defensible
Contribute to pre-sales activities: technical demos, POC builds, RFP responses, and solution estimations - your hands-on credibility is a direct input to Greenlight’s win rate
Produce high-quality technical documentation - solution design documents, architecture diagrams, runbooks, and post-deployment reports - written to a standard the client’s IT team can maintain
Identify account expansion opportunities within active engagements - additional use cases, adjacent processes, and follow-on automation candidates - and surface them to the AI Delivery Engagement Manager
Mentor Automation Engineers and client technical teams on AI agent patterns, LLM integration best practices, and platform capabilities

Client Engagement & Consulting Delivery

Operate with high autonomy inside client environments - navigating ambiguity, defining structure where none exists, and delivering without requiring hand-holding from the practice lead
Manage scope, timelines, and deliverables across concurrent client engagements - you know when to flag a risk and when to absorb it
Build trusted-advisor relationships with client technical teams - the goal is to be the person they call when they have an AI or automation problem, not just the vendor who delivered the last project
Deliver working solutions within 2–4 week sprint cycles - you build and show, you don’t slide and tell

What We’re Looking For

Skills & Competencies

Technical depth with consulting presence - credible with a CTO and a COO in the same meeting
AI-native - you understand how LLMs behave under pressure, where they fail, and how to build reliable systems around them
Builder's bias - working software over slide decks, every time
High autonomy - you define structure where none exists without needing direction
Commercially aware - scope, delivery economics, and what it costs when technical decisions go sideways
Clear communicator - architecture decisions and trade-offs explained in language both business and IT can act on

Technical Familiarity

LLM platforms - Anthropic Claude (primary), Microsoft Copilot, Google Gemini, OpenAI; hands-on with APIs, agent frameworks, and production deployment across at least one
Claude Skills framework and Cowork - structured instruction design, output validation, skill packaging
MCP (Model Context Protocol) - connector design, enterprise system integration, authentication flows
Python and/or Node.js - production-grade, testable, maintainable code
REST and GraphQL APIs - authentication, error handling, rate limiting, webhooks
Cloud platforms - AWS, Azure, or GCP; deployment, containers, infrastructure basics
LLM evaluation and observability - LangSmith, Weights & Biases, or equivalent

What Great Looks Like in This Role

The standard we are hiring to:

The best FDEs we have worked with walk into a client environment and within a week they know more about the client’s process than the client’s own team has documented. They build a working POC in a few weeks that makes the client stop asking whether it’s possible and start asking when it can go to production. They write code that the next engineer can understand without a two-hour briefing. They know when the LLM is going to fail before it does, and they’ve already built the fallback. And they leave every engagement with a client technical team that is more capable than when they arrived - because that is what makes clients come back.

AI in Our Hiring Process

We use AI tools to support parts of our recruitment - organizing applications and flagging relevant experience. These tools inform our process, they don’t drive it. Every hiring decision is made by our team, full stop.

Compensation

The expected salary range for this role is $90,000 – $130,000 CAD annually, based on experience and qualifications.

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More about this job

Responsibilities

Design, build, and operationalize production-grade AI agent workflows and intelligent automation solutions embedded within client environments. Lead technical discovery workshops and develop reusable AI skills and connectors to integrate agents with enterprise systems.

Requirements

Requires 3-5 years of experience with deep fluency in LLMs, specifically Anthropic Claude, and proficiency in Python or Node.js. Candidates must possess a blend of high-level technical engineering skills and senior consulting presence for C-suite interaction.

Skills

AI Agent Architecture
Anthropic Claude
Python
Node.js
Model Context Protocol (MCP)
REST APIs
GraphQL
RAG
Solution Architecture
Technical Discovery
LLM Evaluation
Cloud Platforms
Enterprise Integration
Technical Consulting
Prompt Engineering
Multi-agent Orchestration

Visa sponsorship

Not detected in the job text

Keywords

Anthropic Claude
AI Agents
MCP
Python
Node.js
REST
GraphQL
RAG
AWS
Azure
GCP
LangSmith
Weights & Biases
Enterprise Automation
Solution Architecture
Agentic AI
LLM
OAuth 2.0
Salesforce
Jira
ServiceNow
SharePoint
DocuSign
Technical Documentation
POC
Consulting
Intelligent Automation
Chain-of-Thought
Multi-agent Orchestration
API Integration

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