About the Role
The company is seeking an Engineering Technology & AI Lead to enhance efficiency in the design, engineering, and delivery of projects through the application of technology, automation, and AI. This position is distinct from a traditional IT or AI tools role; you will collaborate directly with engineering and design teams to comprehend workflows, identify areas of inefficiency, and reshape these workflows utilizing technology and AI. Your primary objective is to leverage software and AI to minimize repetitive tasks while preserving the technical judgment, validation, and accountability of engineers. Initially focusing on engineering, this capability will eventually extend to the company's support functions.
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Key Responsibilities
- Map the company's engineering workflows and identify the 10–20 highest-volume/highest-friction processes.
- Assess opportunities based on hours × frequency × complexity × error risk × automation potential.
- Redesign workflows to enhance engineering capacity, speed, and quality.
- Build and deploy practical GenAI, RAG, AI-agent, and automation solutions.
- Establish the company's internal Engineering AI Layer incorporating: the company's Data, the company's Standards, the company's Workflows, and the company's Engineering Knowledge.
- Integrate AI into existing engineering tools, systems, and data, ensuring applications are cohesive rather than isolated.
- Develop systems to capture and reuse the company's engineering knowledge across various projects.
- Measure impact through time saved, capacity created, quality improved, and rework reduced.
- Create a repeatable approach that can be applied across Finance, HR, Business Development, Operations, and other support functions.
What We're Looking For
- Proven experience in building and deploying Generative AI/Agentic AI solutions.
- Strong Python development skills.
- Experience working with LLMs, RAG, AI agents, APIs, databases, and cloud technologies.
- Proficiency in processing and managing unstructured data, including PDFs, documents, and images.
- Robust understanding of software architecture, data integration, and production deployment.
- Familiarity with frameworks such as LangGraph, LangChain, CrewAI, or AutoGen is advantageous.
- Background in engineering, construction, architecture, BIM, or technical project environments is highly desirable.
- Exceptional ability to translate real business and engineering challenges into practical technology solutions.
What Success Looks Like
Less repetitive work → Faster delivery → Higher engineering capacity → Better quality → Reusable the company's knowledge.
