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Added 52 mins ago
Y
GenAI Prompt Engineer
Yochana
Toronto, ON
- Contract
Prompt Writing: Design and refine creative, effective, and contextually relevant prompts for generative AI systems to maximize performance and accuracy across various use cases.
Added 1 hour ago
OA
Applied AI Engineer - Winnipeg
Outlier AI
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
We help train advanced generative systems by providing human feedback on AI agents.
Added 2 hours ago
T
GenAI Prompt Engineer
TechDoQuest
Toronto, ON
- Contract
-Prompt Writing: Design and refine creative, effective, and contextually relevant prompts for generative AI systems to maximize performance and accuracy across various use cases.
Added 2 hours ago
RC
Senior AI Engineer
Realtek Consulting LLC
Toronto, ON
- Contract
Added 3 hours ago
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Senior Manager, Data Engineer, Applied AI Data Ingestion & Integration
BMO
Toronto, ON · FCP
- Full-time
…and unstructured data used across AI, machine learning, and Generative AI…
Added 4 hours ago
IG
Machine Learning Engineer
IMCS Group
ON · Ontario, Canada
- Contract
We are looking for a highly experienced Senior AWS SageMaker / MLOps Engineer with 6+ years of overall IT experience and strong expertise in building, deploying, and operationalizing…
Added 4 hours ago
Logistics Engineering Specialist
Siemens
Concord, ON
The Logistics Engineer is responsible for analyzing, designing, implementing, and continuously improving material-flow and logistics processes across warehouse, receiving, production,…
Added 4 hours ago
E
AI Quality Engineer
EPITEC
Toronto, ON
- Contract
Hands-on experience with Generative AI / LLMs and applying AI to enterprise automation or testing use cases.
Added 4 hours ago
T
Machine Learning Engineer
TEEMA
Toronto, ON
- $115,000 to $120,000 CAD / year
- Full-time
MLOps Developer / DevOps Infrastructure Engineer
Added 4 hours ago
W
AI Engineer/Developer
W3Global
Toronto, ON
- $60,000 to $68,000 CAD / year
- Full-time
AI Developer (Generative AI / Machine Learning)
Added 5 hours ago
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Senior Python Engineer
Citi
Mississauga, ON
- Full-time
Understanding and practical application of Generative AI concepts in software development.
Added 5 hours ago
A
Java/AI Software Engineer
Aptonet
Vancouver, BC
- Full-time
We are seeking an Intermediate Software Engineer to join our team in Vancouver, BC, and help build innovative generative AI capabilities across Planview products. In this role, you will…
Added 5 hours ago
WT
Data Engineer
Wissen Technology
Montreal, QC
- Full-time
We are looking for a Data Engineer with strong backend engineering fundamentals and hands‑on experience building scalable, high‑performance data pipelines. The ideal candidate comes from a…
Added 5 hours ago
VT
AI Platform Developer
Volgo Technologies
Toronto, ON
- Contract
We are looking for a hands-on engineer who can build and deploy production-grade Agentic AI and multi-agent systems using Google ADK and MCP, while developing scalable AI platform…
Added 6 hours ago
F
Technical Consultant (Data & AI)
Fastloop
Vancouver, BC
- Full-time
You aren’t just a “Data Engineer” or a “Software Engineer”; you are the “connective tissue” of modern intelligence. You will be responsible for the programmatic development of Agentic…
Added 7 hours ago
RE
Applied AI Engineer
Randstad Enterprise
Montreal, QC
- Contract
The Applied AI Engineer will work with business and technology teams to develop and implement Generative AI solutions. This is a hands-on engineering role focused on building prototypes,…
Added 7 hours ago
TD
Robotics QA Automation Engineer
TELUS Digital
Canada
- Full-time
Familiarity with Generative AI models (e.g., LLMs, diffusion models) and their deployment.
Added 7 hours ago
DevOps & Cloud Platform Intern (December 2026 to April 2027)
ProCogia
Vancouver, BC
…production-ready solutions. We are actively advancing capabilities across generative AI, agentic systems, workflow automation, AI governance, and enterprise AI applications. At ProCogia,…
Added 8 hours ago
OA
AI Automation Engineer
Outlier AI
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
We train advanced generative systems by providing human feedback that helps improve AI agents.
Added 8 hours ago
OA
AI Agent Engineer
Outlier AI
Montreal, QC · Greater Montreal Metropolitan Area
- Full-time
We help train advanced generative AI systems by providing human feedback that improves autonomous agents.
Added 8 hours 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 9 hours ago
RE
Technical Project Manager
Randstad Enterprise
Montreal, QC
- Contract
…foundations and practical experience with enterprise search, generative AI or RAG-enabled knowledge experiences. The role does not require an AI engineer. It requires a thoughtful…
Added 1 day ago
L
Senior Yocto Developer Toronto
Litmus
Remote, Canada
- Full-time
- Remote
We are looking for a highly skilled and passionate Senior Yocto & Linux Software Engineer to join our engineering team in Toronto. In this role, you will be responsible for developing,…
Added 1 day ago
T
Senior AI Engineer (GCP/Vertex AI) Contract
TekRek
Canada
- Contract
5 to 10 years in software, ML or AI engineering, with at least 2 years delivering generative AI into production
Added 1 day 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…

Fastloop

Technical Consultant (Data & AI)

Vancouver, BC, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Oct 30, 2026
Posting language: English
Posted: Jun 10, 2026

Original job description

Careers

Technical Consultant (Data & AI)

Full Time

Vancouver

At Fastloop, we don’t sugarcoat it.

We’re a small, high-impact, AI-Native consulting firm building at the intersection of Data and AI. We leverage cutting-edge AI to build custom, production-grade systems for our clients. We move fast, learn faster, and believe grit beats polish every time. We ship real systems, not just decks. We take pride in solving hard problems with clarity, accountability, and craft.

The Role: The Multi-Tool Engineer

At Fastloop, our Technical Consultants (TC) are our engine. We are looking for a code-first generalist who can bridge the gap between a raw data lake and a functional, agentic AI application.

You aren’t just a “Data Engineer” or a “Software Engineer”; you are the “connective tissue” of modern intelligence. You will be responsible for the programmatic development of Agentic workflows, GenAI pipelines, and the cloud-native infrastructure that powers them and the integration of these systems into existing business processes to drive measurable operational impact.

A TC typically owns the technical execution across 1-3 client projects simultaneously.

What You’ll Do

Agentic Engineering & GenAI Workflows
Build Intelligent Agents: Design and build agent architectures and reasoning loops (ReAct, Chain of Thought, Plan-and-Solve) using Google ADK, Vertex AI Agent Builder, LangChain, or LlamaIndex.
Advanced RAG & Search: Architect Retrieval-Augmented Generation (RAG) pipelines and enterprise search indexing using Vertex AI Search and Vector Databases.
LLM Integration: Orchestrate prompts, context management, and tool-calling for models like Gemini Enterprise.
Data Foundation & AI Pipelines
Automated Ingestion: Develop custom pipelines for ingesting and enriching structured and unstructured data (PDFs, text, logs) into GCS or BigQuery.
Data Engineering for AI: Write advanced SQL and automate dbt/Dataform pipelines to ensure data is “AI-ready.”
MLOps & Observability: Implement CI/CD for model updates and set up AI observability/eval frameworks (eg. RAGAS, Vertex Eval) to detect and prevent hallucinations.
Integration & Cloud-Native Development
Inference Layer & APIs: Design and build scalable backend services and RESTful APIs using Python (FastAPI, Flask) to expose AI capabilities (AIaaS).
Infrastructure as Code (IaC): Architect and deploy end-to-end GenAI infrastructure (Vertex AI, Cloud Run, Cloud SQL) entirely through Terraform.
Cross-Cloud Generalist: While we lean heavily on GCP, you maintain the “Generalist Edge” by ensuring solutions can be adapted to Azure or hybrid environments.
Process & Workflow Integration: Build event-driven architectures that trigger AI actions based on business events (eg. Pub/Sub, Webhooks, or Cloud Scheduler). Use Cloud Workflows or custom Python logic to orchestrate multi-step business processes.
Legacy & Tool Integration: Connect AI agents to “real world” tools – CRMs, ERPs, or custom proprietary databases – via secure API orchestration to allow agents to take action, not just provide answers.
Agile Execution & Quality
Daily Contribution: Own your stories from refinement to production. Validate technical feasibility, identify constraints early, and document technical tasks/DoD.
Testing & Validation: Prepare environments and test automation for UAT. Execute technical validation and resolve defects to ensure endpoints deliver business value.

Consultant’s Mindset: Effectively communicate technical trade-offs (e.g., speed vs. scalability) to both technical leads and non-technical stakeholders

Your Technical Toolkit

AI & GenAI Expertise: Proven experience with LLMs (Gemini preferred), prompt engineering, and context window management.
Agentic Frameworks: Hands-on with Google ADK, LangChain, or LlamaIndex.
Modern Databases: Expert SQL. Experience with pgvector, Pinecone, or Qdrant, alongside BigQuery and PostgreSQL.
Cloud & DevOps: Mastery of GCP (Cloud Run, GKE, Pub/Sub, IAM). Strong proficiency in Terraform and GitHub Actions. Experience with Event-driven architecture (Pub/Sub, Eventarc) and Workflow Orchestration (Google Cloud Workflows, Airflow, or Step Functions).
Backend: Advanced Python (FastAPI/Django). Familiarity with Document AI or unstructured data parsing is a plus.
Frontend Support: Ability to build lightweight internal UIs (Streamlit, React) for agent-facing dashboards or prototypes.

Background

3-6 years as a Cloud, AI, or Backend Engineer in a high-intensity environment.
You are a generalist who can be a SQL wizard in the morning, an AI/Python dev in the afternoon, and write IaC by end-of-day.
You don’t just write code; you own the technical outcome and the “definition of done.”
You understand that an AI model is useless if it doesn’t fit into the client’s actual workday. You take pride in ensuring the “plumbing” between the AI and the business process is seamless and robust.
Demonstrated ability to switch between different client environments and tech stacks multiple times a day without losing focus.

Preferred Experience & “Nice To Haves”

While the core of our stack is GCP-native AI, the ideal Fastloop consultant is a platform-agnostic problem solver. We value the following “extra gears”:

Multi-Cloud & Hybrid Expertise: Hands-on experience with Azure (Azure OpenAI Service, AI Search) or AWS (Bedrock, Sagemaker) to support clients in multi-cloud environments.
AI Observability & Reliability: Experience with evaluation frameworks (eg. RAGAS, Vertex Eval) and observability tooling to detect and prevent LLM hallucinations or drift.
Advanced Agentic Reasoning: Deep understanding of advanced reasoning techniques such as Chain of Thought (CoT), ReAct, or Plan-and-Solve architectures.
Data Science Lite: Experience with Google Document AI or advanced unstructured data parsing libraries for complex RAG preparation.
Frontend Fluency: Experience with React, Angular, Streamlit or Gradio for building polished internal prototypes or agent-facing interfaces.
Industry Context: Previous experience in Energy sectors or Heavy Industry helping you understand the business logic behind the data.
Professional Certifications: Google Cloud Professional ML Engineer, Cloud Developer, or Azure Solutions Architect certifications.

The Grit Factor

At Fastloop, we move fast. We are looking for a consultant who understands that:

Ambiguity is an Opportunity: You don’t wait for a perfectly groomed Jira ticket. You fill in the blanks and keep moving.
Troubleshooting is tenacious: When a pipeline fails or an API returns a 500, you dive into the logs and find the root cause rather than waiting for instructions.
Outcome is more important than Ego: You value shipping a working system in the real world over achieving “theoretical perfection” on a whiteboard.
We are built to build: You are energized by hard problems, real constraints, and production accountability.

Ready to join? Apply today.

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Responsibilities

Build and integrate agentic AI workflows, RAG pipelines, data ingestion and preparation systems, backend APIs, and cloud-native infrastructure for client projects. Own technical delivery from planning through production, including testing, observability, workflow integration, and communication of technical trade-offs.

Requirements

The role seeks a generalist with 3–6 years of experience as a cloud, AI, or backend engineer, strong Python and SQL skills, and hands-on experience with LLMs, agent frameworks, and GCP. Candidates should be comfortable with Terraform, data and workflow orchestration, production testing, and adapting to different client environments; multi-cloud experience and relevant certifications are preferred.

Skills

Python
SQL
Generative AI
Agentic AI
Retrieval-Augmented Generation
Google Cloud Platform
Terraform
FastAPI
LangChain
LlamaIndex
Vertex AI
BigQuery
PostgreSQL
CI/CD
Event-Driven Architecture
REST APIs

Visa sponsorship

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Keywords

Google Cloud Platform
Vertex AI
Google ADK
Gemini
LangChain
LlamaIndex
Agentic Workflows
Generative AI
Retrieval-Augmented Generation
Vector Databases
BigQuery
PostgreSQL
pgvector
Pinecone
Qdrant
Python
FastAPI
Flask
Terraform
GitHub Actions
Cloud Run
Google Kubernetes Engine
Pub/Sub
Eventarc
Google Cloud Workflows
Airflow
RAGAS
Vertex Eval
Azure OpenAI Service
AWS Bedrock

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