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AI Engineer

  • Canada

Compensation: $90-$100/hour · Contract

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Job details

Pay
Compensation: $90-$100/hour
Job type
Contract
Experience
6+ years of software/application engineering experience, including 1-2+ years building GenAI applications
Posting language
English
Posted

Original job description

Title: AI Engineer

Type: Contract, 6 months + possibility of extension

Location: Toronto, ON- Hybrid- 3- 4 Day’s in office/Week

Start Date: ASAP

Interview Process: 2 rounds (1-Inperson and 1- Virtual)

Compensation: $90-$100/hour

Day-to-Day Responsibilities:

  • The AI Engineer will design and build GenAI-powered applications and products using Python, React/Next.js, and AWS.
  • They will develop LLM pipelines, RAG/Graph RAG solutions, AI agents, MCP integrations, APIs, and prompt-based applications using technologies such as Lang Chain, LlamaIndex, Bedrock, and commercial/open-source LLMs.
  • The engineer will build cloud-native applications using AWS services such as EKS, Lambda, Fargate, Glue, Athena, and Lake Formation while deploying solutions through Docker, Terraform, and DevSecOps practices.
  • They will own solutions end-to-end, including architecture, coding, testing, deployment, performance optimization, monitoring, and ongoing improvements.

Must-Haves:

  • 6+ years of software/application engineering experience, including 1-2+ years building GenAI applications
  • Strong Python development experience with hands-on ownership of production applications, APIs, and microservices
  • Hands-on experience building GenAI applications using RAG, LLM pipelines, and Agentic AI
  • Strong AWS experience building and deploying cloud-native applications, ideally using Bedrock and services such as EKS, Lambda, or Fargate
  • Experience with GenAI frameworks and LLMs such as Lang Chain/LlamaIndex and GPT, Claude, Gemini, or LLaMA

Pluses:

  • Hands-on experience with MCP and/or Graph RAG architectures
  • Experience with vector/graph databases such as PGVector, Weaviate, Milvus, Neo4j, or Neptune
  • Front-end development experience with React, Next.js, TypeScript/JavaScript
  • Experience with Docker, Terraform, CI/CD, DevSecOps, Airflow, and automated AI testing/evaluation
  • Capital markets/investment management experience, particularly working with market analysis or enterprise financial data

We may use AI-enabled and/or automated tools to support parts of our recruitment process, including application screening, interview scheduling, and candidate communications. These tools are used to enhance consistency and efficiency. All hiring decisions involve human review and are not based solely on automated processing.

The Company offers a total rewards package in accordance with all applicable federal, provincial, and local laws and requirements. Benefit eligibility and offerings vary based on role, employment status, and work location. For contractor positions, benefits are limited to those entitlements and protections required by applicable law, which may include (as applicable) vacation pay, public holidays, leaves of absence, and other legally mandated benefits or payments.

More about this job

Responsibilities

Design, build, and deploy generative AI applications and cloud-native products, including LLM pipelines, RAG and Graph RAG solutions, AI agents, integrations, and APIs. Own solutions end to end, covering architecture, development, testing, deployment, performance optimization, monitoring, and ongoing improvements.

Requirements

Requires 6+ years of software or application engineering experience, including 1–2+ years building generative AI applications, with strong Python and production application, API, and microservices experience. Candidates must have hands-on experience with RAG, LLM pipelines, agentic AI, AWS cloud-native services, and generative AI frameworks and models.

Skills

  • Python
  • Generative AI
  • Retrieval-Augmented Generation
  • Large Language Model Pipelines
  • Agentic AI
  • AWS
  • Amazon Bedrock
  • LangChain
  • LlamaIndex
  • React
  • Next.js
  • MCP Integrations
  • Graph RAG
  • Docker
  • Terraform
  • DevSecOps

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Data & Analytics
  • Finance & Accounting

Keywords

  • Python
  • React
  • Next.js
  • TypeScript
  • JavaScript
  • Generative AI
  • Large Language Models
  • RAG
  • Graph RAG
  • Agentic AI
  • MCP
  • LangChain
  • LlamaIndex
  • Amazon Bedrock
  • AWS
  • EKS
  • Lambda
  • Fargate
  • Glue
  • Athena
  • Lake Formation
  • Docker
  • Terraform
  • DevSecOps
  • CI/CD
  • Airflow
  • Vector Databases
  • Graph Databases
  • Automated AI Testing
  • Capital Markets

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