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2612 Lead AI & Full Stack Engineer
Our client is a well-established manufacturing and engineering company based in Mississauga, and they are looking for a Lead AI & Full Stack Engineer. This individual will lead the transformation of engineering and operational workflows through automation, the implementation of centralized data systems, and the development of AI-driven solutions. The role will be instrumental in shaping how engineering, operations, and business systems integrate and scale for future growth.
Key Responsibilities
Centralized Data & Systems Architecture: Design and implement a centralized engineering and operational database
Engineering Process Automation: Automate repetitive engineering workflows (design calculations, drawing generation, reporting, BOM creation)
AI & Intelligent Automation: Develop and deploy AI-powered solutions using LLMs (e.g., OpenAI, LangChain). Implement Retrieval-Augmented Generation (RAG) using internal engineering knowledge bases
Power Platform & Low-Code Development: Lead development using Microsoft Power Platform (Power Apps, Power Automate, Power BI)
System Integration & Automation Ecosystem: Integrate systems such as CRM, ERP, Engineering platforms. Build APIs and middleware to connect systems seamlessly
Full Stack & Platform Development: Develop scalable applications (web-based tools, dashboards, internal platforms)
Strategy, Leadership & Impact: Define and execute the automation and AI roadmap
Qualifications
5–8+ years of experience in software engineering, automation, or AI development
Strong Experience with Microsoft Power Platform (Power Apps, Power Automate, Power BI)
Strong Experience with Python, APIs, and backend development
Strong Experience with Databases (SQL, NoSQL) and data architecture
Strong Experience with Cloud platforms (Azure preferred; AWS/GCP acceptable)
Experience with AI/ML tools (OpenAI, LangChain, LLMs)
Experience with RPA tools (e.g., UiPath, Power Automate)
Experience with Full stack development (React, Node.js or similar)
Experience integrating multiple enterprise systems
Knowledge of engineering, construction, or manufacturing environments is an asset
Familiarity with CAD or engineering design workflows is an asset
Experience with data engineering tools (DBT, BigQuery, etc.) is an asset
Knowledge of workflow orchestration tools is an asset