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Added 6 mins ago
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Greenlight Consulting

Senior Forward Deployed Engineer

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Full-time

Apply About employer

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Job details

Job type: Full-time
Apply by: Apr 2, 2027
Posting language: English
Posted: Oct 4, 2026

Original job description

Greenlight helps organizations solve complex business challenges through intelligent automation, agentic AI, and custom technology solutions. We combine deep consulting expertise with hands-on engineering to bridge the gap between strategy and execution. Anthropic's Claude is embedded across how we design, build, and validate solutions - and this role is at the technical frontier of that capability.

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
Seniority: Senior - 5+ years full-stack engineering, 1+ year FDE or client-embedded delivery
Platform Focus: Anthropic Claude (Cowork + Skills), MCP, Python / Node.js, REST APIs
Travel: Regular client travel - discovery, workshops, POC delivery, go-live
Location: Toronto, ON preferred - hybrid onsite + remote delivery
Compensation: $110,000 – $150,000 CAD annually, based on experience

What Makes a Star at Greenlight

Full-stack engineering foundation - you've built things end to end, backend to frontend, and you own the whole stack

Builder's instinct, architect's discipline - working software over slide decks, every time

AI-native at depth - you know how LLMs fail and build reliable systems around them

Client-embedded, not arm's length - you thrive in client environments, not back-office settings

Commercially aware - scope, delivery economics, and what it costs when technical decisions go sideways

The most technically credible person in the room - credible with a CTO and a COO in the same meeting

The Role

The Senior 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.

You bring a strong full-stack engineering background (5+ years) combined with at least one year of forward deployed or client-embedded delivery experience. You know how to ship production-grade software, navigate a complex enterprise environment, and show up credibly in front of technical and business stakeholders in the same day. The platform is Anthropic Claude. The problem space is complex, regulated, and high-stakes. The bar is production-grade.

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

Present technical architectures to executive and non-technical audiences with clarity, confidence, and the credibility that comes from having built things like this before

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 simpler is better than AI

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

Build and maintain MCP connectors integrating AI agents with enterprise systems - CRMs, ERPs, document platforms, core banking systems, and custom APIs - handling authentication, data mapping, error handling, and audit requirements

Implement advanced LLM patterns: RAG, tool use, multi-agent orchestration, structured output validation, and chain-of-thought reasoning

Conduct output validation, performance tuning, and safety testing of deployed AI agents before client go-live

Full-Stack & Integration Engineering

Write production-quality Python and/or Node.js to extend platform capability - data pipelines,

transformation logic, webhook handlers, API wrappers, and back-end components

Build, test, and maintain integrations with enterprise platforms (Salesforce, SharePoint, ServiceNow, Jira, DocuSign, 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

Accelerators & Practice Development

Build and continuously refine reusable Skills libraries, automation templates, and reference

architectures that make every subsequent Greenlight engagement faster

Contribute to pre-sales activities: technical demos, POC builds, RFP responses, and solution

estimations

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

Mentor junior FDEs and Automation Engineers on AI agent patterns, LLM integration best practices, and platform capabilities

What We're Looking For

Experience

5+ years of professional full-stack or backend engineering experience - building, shipping, and maintaining production systems

1+ year of forward deployed, client-embedded, or consulting engineering experience - working directly inside client environments, not just delivering remotely

Hands-on experience building with LLM platforms in production - Anthropic Claude preferred; OpenAI, Azure OpenAI, or Gemini also relevant

Demonstrated experience with enterprise system integrations - REST APIs, OAuth 2.0, webhooks, authentication flows at scale

Experience deploying and maintaining solutions in cloud environments (AWS, Azure, or GCP)

Technical Stack

Full-Stack Engineering: Python and/or Node.js (production-grade); REST & GraphQL APIs;

TypeScript; SQL and NoSQL databases; CI/CD AI & LLM Anthropic Claude API; MCP connector design; RAG; multi-agent orchestration; tool use; structured output validation; LLM evals & observability (LangSmith or equivalent)

Enterprise Integration Salesforce, SharePoint, ServiceNow, Jira, or similar; OAuth 2.0;

webhook handling; error handling and retry logic at scale

Cloud & DevOps AWS, Azure, or GCP; Docker; deployment basics; logging and

monitoring

What Makes You the Right Fit

You've been the most technical person in a client meeting and the most client-facing person in an engineering room - and you're comfortable in both

You build things that work in production, not just in demos - and you know the difference

You define structure where none exists and deliver without needing hand-holding

You write code the next engineer can understand without a two-hour briefing

You know when the LLM is going to fail before it does, and you've already built the fallback

You leave every engagement with a client technical team more capable than when you arrived

What You'll Find at Greenlight

Complex, high-stakes enterprise AI projects that push you technically and strategically

A team that combines deep consulting expertise with hands-on engineering - no arm's-length delivery

Training budget and dedicated time for certifications

Clear growth paths - technical track or leadership track

Real work-life balance: hybrid model, flexible hours, and a culture that respects what matters outside of work

A firm where your opinions on architecture, practice, and client strategy are actually heard

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. We welcome applicants of all backgrounds. If you need accommodations during the process, please let us know.

Compensation

The expected salary range for this role is $120,000 – $140,000 CAD annually, based on experience and qualifications.

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More about this job

Responsibilities

Lead client discovery and design end-to-end AI agent and automation architectures that meet enterprise infrastructure, security, and compliance needs. Build, integrate, test, and operationalize production-grade solutions, while developing reusable accelerators, supporting pre-sales, documenting deployments, and mentoring junior engineers.

Requirements

Requires 5+ years of professional full-stack or backend engineering experience and at least 1 year of forward-deployed, client-embedded, or consulting engineering experience. Candidates should have production LLM experience, enterprise integration expertise, and experience deploying and maintaining solutions on AWS, Azure, or GCP.

Skills

Full-Stack Engineering
Python
Node.js
Anthropic Claude
MCP Connector Design
AI Agent Development
LLM Integration
RAG
Multi-Agent Orchestration
REST APIs
GraphQL
OAuth 2.0
Enterprise Integrations
Cloud Platforms
Client-Facing Delivery
Solution Architecture

Benefits

Training Budget
Certification Support
Flexible Hours
Hybrid Work
Work-Life Balance

Visa sponsorship

Not detected in the job text

Keywords

Anthropic Claude
Claude Cowork
Claude Skills
Model Context Protocol
Python
Node.js
TypeScript
REST APIs
GraphQL
OAuth 2.0
RAG
Multi-Agent Orchestration
Tool Use
Structured Output Validation
LLM Evaluation
LLM Observability
LangSmith
Salesforce
SharePoint
ServiceNow
Jira
DocuSign
AWS
Azure
Google Cloud Platform
Docker
CI/CD
SQL
NoSQL
Webhooks

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