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Lead Full-Stack GenAI Developer (Contractor)

  • Toronto, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
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Original job description


About the Role


We are seeking a Senior Lead Full-Stack GenAI Developer for a 6-month contract engagement to lead the end-to-end hands-on build, integration, and deployment of enterprise GenAI and Agentic AI applications. Partnering closely with our Principal AI Solution Architect, you will own the full-stack development - spanning backend Python services, frontend interfaces, retrieval pipelines, AI agents, enterprise integrations, and GenAIOps.

Key Responsibilities


  • Hands-on AI Implementation: Personally author and maintain production-grade Python microservices, custom APIs, retrieval (RAG) systems, and agentic workflows.

  • Full-Stack Application Building: Create reviewer workbenches, operational dashboards, and user interfaces using React / TypeScript paired with backend-for-frontend APIs.

  • Enterprise Integration: Seamlessly integrate AI services into enterprise data pipelines, APIs, databases, and platform ecosystems including Microsoft Azure, Databricks, and Microsoft Foundry.

  • Evaluation & GenAIOps: Design automated evaluation test suites (RAG metrics, model latency, cost, groundedness) and establish CI/CD pipelines, Infrastructure-as-Code (IaC), containerization, and end-to-end telemetry.

  • Reusable Capabilities & Mentorship: Standardize repeated delivery patterns into reusable SDKs, component libraries, and templates, while mentoring internal engineering team members.




Requirements


Required Qualifications


  • Seniority & Experience: Proven track record as a Senior or Lead Engineer personally contributing code to production-deployed GenAI systems.

  • Backend & AI Core: Deep Python proficiency, REST/GraphQL APIs, RAG architectures, vector databases, prompt engineering, agentic frameworks, and automated LLM evaluation practices.

  • Frontend UI: Strong production skills in React and TypeScript.

  • Cloud & Platform Ecosystems: Practical experience within Microsoft Azure (Azure OpenAI, Azure AI Search) and Databricks environments.

  • Data & Ops: Proficiency in SQL, data engineering pipelines, CI/CD, Docker/containers, Infrastructure-as-Code, and runtime telemetry/monitoring.

Important Candidate Note:

Candidates focused primarily on prompt design, research notebooks, architectural oversight, project coordination, or generic web development without recent, hands-on production AI coding, enterprise integration, deployment automation, and production support will not be considered for this role.

More about this job

Responsibilities

Lead hands-on development, integration, and deployment of enterprise GenAI and agentic AI applications, including Python services, APIs, retrieval systems, workflows, and React/TypeScript interfaces. Build evaluation and GenAIOps capabilities, integrate with enterprise platforms, standardize reusable engineering components, and mentor internal engineers.

Requirements

Requires senior or lead-level experience personally coding production GenAI systems, with strong Python, API, RAG, vector database, agentic framework, and LLM evaluation expertise. Candidates must also have production React/TypeScript skills and practical experience with Azure, Databricks, SQL, data pipelines, CI/CD, containers, Infrastructure as Code, and telemetry.

Skills

  • Python
  • React
  • TypeScript
  • REST APIs
  • GraphQL
  • Retrieval-Augmented Generation
  • Vector Databases
  • Prompt Engineering
  • Agentic AI Frameworks
  • Microsoft Azure
  • Azure OpenAI
  • Azure AI Search
  • Databricks
  • SQL
  • CI/CD
  • Infrastructure as Code

Visa sponsorship

Not detected in the job text

Categories

  • Software
  • Technology
  • Engineering
  • Data & Analytics
  • Management & Leadership

Keywords

  • Generative AI
  • Agentic AI
  • Python
  • Microservices
  • REST APIs
  • GraphQL
  • Retrieval-Augmented Generation
  • Vector Databases
  • Prompt Engineering
  • LLM Evaluation
  • React
  • TypeScript
  • Backend-for-Frontend APIs
  • Microsoft Azure
  • Azure OpenAI
  • Azure AI Search
  • Databricks
  • Microsoft Foundry
  • SQL
  • Data Engineering Pipelines
  • CI/CD
  • Infrastructure as Code
  • Docker
  • Containerization
  • Telemetry
  • Monitoring
  • GenAIOps
  • Automated Evaluation
  • Enterprise Integration
  • SDKs

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