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Added 12 mins ago
AI Engineer/developer
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Contract
Added 12 mins ago
Senior Software Engineer
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Founding Engineer, Physical AI + Computer Vision (Equity-Based)
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Data Engineer
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Raise

AI Engineer

Brampton, ON, Canada

Pay: Pay Rate: $56.56/hour, depending on experience
Job type: Full-time
Apply by: Oct 30, 2026
Posting language: English
Posted: Sep 30, 2026

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Original job description

Pay Rate: $56.56/hour, depending on experience
Contract Length: 6 Months, with a strong likelihood of extension
Location: Brampton or Toronto, Ontario

Raise is currently hiring an AI Engineer on behalf of our client. They’re expanding their team to meet growing needs, making this a unique opportunity to work with an industry leader. Our Client is a technology company that combines decades of industry expertise with next-generation AI technology that helps organizations reinvent how they build, operate and deliver by pairing human ingenuity with agentic systems that scale intelligence across the enterprise.

Note: The primary pay rate is based on T4 classification; however, we will also consider applications from candidates interested in an INC classification, where applicable.

Description

The ideal candidate will be passionate about building reliable and practical AI agents and AI workflows powered by Large Language Models (LLMs). You will use Python, LangGraph, Langfuse, Model Context Protocol (MCP), and Google Cloud to develop AI agents, Retrieval-Augmented Generation (RAG) solutions, and production-ready AI services. You will work in a fast-paced organization using Agile/Scrum methodologies and collaborate with product managers, software engineers, and business stakeholders to deliver AI solutions for customer service and operational requirements.

Responsibilities

Design and develop LLM-powered applications using Python
Build AI agents and workflows using LangGraph
Develop RAG solutions using enterprise data, embeddings, and vector search
Build and integrate MCP servers to connect AI agents with enterprise tools, data, and services
Implement LLM tracing, monitoring, and evaluation using Langfuse
Develop and deploy AI services on Google Cloud
Create APIs and integrations for AI capabilities
Write unit and integration tests to ensure solution quality
Evaluate AI outputs for accuracy, relevance, reliability, and safety
Monitor and troubleshoot AI applications in production
Collaborate with product, engineering, architecture, and business teams
Contribute to AI engineering standards and reusable development patterns
Mentor developers and provide guidance through design and code reviews
Remain current with developments in LLMs and generative AI

Qualifications

5+ years of professional software development experience
2+ years of experience developing agentic AI or LLM-powered applications
Strong Python development experience
Hands-on experience building applications with LLMs
Experience with LangGraph, LangChain, or a similar AI application framework
Experience with Langfuse or another LLM observability platform
Understanding of Model Context Protocol (MCP) and its use in connecting AI agents with tools and enterprise systems
Experience with Google Cloud services such as Vertex AI and BigQuery
Experience building RAG solutions using embeddings and vector search
Experience developing RESTful APIs using FastAPI, Flask, or a similar framework
Understanding of prompt engineering, tool calling, structured outputs, and context management
Experience with automated testing, Git, and CI/CD practices
Understanding of data privacy, AI safety, and responsible AI principles
Experience working with Agile methodologies
Excellent verbal and written communication skills
Desirable Skills and Experience
Hands-on experience developing or integrating MCP servers and clients
Experience with Gemini, OpenAI, Anthropic, or open-source LLMs
Experience with vector databases such as Vertex AI Vector Search, Pinecone, pgvector, or Supabase
Experience with Docker and containerized deployments
Familiarity with event-driven systems such as Pub/Sub
Familiarity with LLM evaluation frameworks
Experience working with high-traffic enterprise applications
Experience in retail, e-commerce, loyalty, customer service, or supply-chain environments
Experience with collaboration tools such as JIRA and Confluence
Personal Skills & Qualities
Self-motivated with a strong team spirit
Strong problem-solving and troubleshooting skills
Ability to work independently and collaborate effectively within a team
Comfortable working with evolving requirements and technologies
Strong sense of ownership and accountability
Ability to manage multiple priorities in a fast-paced environment
Ability to communicate AI concepts to technical and non-technical stakeholders
Commitment to building reliable, secure, and responsible AI solutions
Education and Certifications
Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related quantitative field. Or equivalent practical experience (5+ years of professional software engineering) combined with a proven track record of deploying production-ready AI applications.
Recommended Certifications Google Cloud Professional Certifications, Google Cloud Certified Professional Cloud Architect or Google Cloud Certified Professional Data Engineer, AI & Machine Learning Certifications

Additional Information

Candiates will be working a hybrid schedule of 4 days per week a t the clients Toronto Downtown site or the clients Brampton site

Looking for meaningful work? We can help!

Raise is an established hiring firm with over 65 years of experience. We believe strongly in making the world a better place through work, which is why we’re a certified B Corporation and donate 10% of our profits to charity.

We strive to build teams that reflect the diversity of the communities we work in. We encourage all qualified applicants to apply, including people from traditionally underrepresented groups such as women, visible minorities, Indigenous peoples, people identifying as LGBTQ2SI, veterans, and people with visible/nonvisible disabilities.

We have a dedicated webpage for accommodations where you can learn more about what we offer and request accommodation: https://raise.jobs/accommodations/

In order to submit candidates for roles, our clients will sometimes require personal information to confirm the identity of applicants and their legal status to work. Raise will never ask you for personal or banking information unless you have been selected for a job. If you are ever unsure about the legitimacy of this or any other Raise job posting (or have any other questions), please contact us at +1 800-567-9675 or hello@raiserecruiting.com.

#WES

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More about this job

Responsibilities

Design, build, test, and deploy production-ready LLM applications, AI agents, workflows, and RAG solutions using Python and Google Cloud. Monitor and evaluate AI systems, integrate enterprise tools and data, troubleshoot production issues, and collaborate with stakeholders while contributing to engineering standards and mentoring developers.

Requirements

Requires at least five years of professional software development experience, including two or more years building agentic AI or LLM-powered applications, with strong Python skills and hands-on experience with AI frameworks, RAG, and cloud services. Candidates should also understand MCP, LLM observability, APIs, testing and CI/CD, prompt engineering, data privacy, AI safety, and Agile practices; a relevant bachelor's or master's degree or equivalent practical experience is specified.

Skills

Python
LangGraph
Langfuse
Model Context Protocol
Google Cloud
Large Language Models
AI Agents
Retrieval-Augmented Generation
Embeddings
Vector Search
RESTful APIs
FastAPI
Prompt Engineering
Tool Calling
Automated Testing
CI/CD

Visa sponsorship

Not detected in the job text

Keywords

Python
LangGraph
LangChain
Langfuse
Model Context Protocol
Google Cloud
Vertex AI
BigQuery
Large Language Models
Generative AI
AI Agents
Retrieval-Augmented Generation
Embeddings
Vector Search
FastAPI
Flask
RESTful APIs
Prompt Engineering
Tool Calling
Structured Outputs
Context Management
Automated Testing
Git
CI/CD
Docker
Pub/Sub
LLM Evaluation
Agile
Scrum
Responsible AI

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