AI Engineer

Nucleus•Vancouver, BC

16d•CA$120,000 - CA$150,000•Hybrid

About The Position

Nucleus is looking for a Forward Deployment AI Engineer to work with our clients' businesses, rolling up your sleeves to design, build, and deploy AI-powered solutions that create real operational impact. You won't be sitting behind a desk writing specs; you'll be on-site at small and mid-size businesses diagnosing inefficiencies, earning stakeholder trust, and shipping production-grade AI agents, automated workflows, and engineering solutions that change how these organizations run. This is a hands-on, client-facing engineering role built for someone who is as comfortable presenting to a small business owner as they are writing Python. This role may operate remotely from within Canada, with a strong preference for a candidate who is able to meet face-to-face with clients in either Vancouver or Toronto.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical field.
2+ years of professional experience in software engineering, AI/ML engineering, or a technical consulting role.
Working proficiency in Python and familiarity with REST APIs and cloud services.
Hands-on experience building with LLM APIs (OpenAI, Anthropic, Gemini, or similar).
Understanding of prompt engineering, RAG (Retrieval-Augmented Generation), and agentic workflow patterns.
Ability to work independently in ambiguous, fast-moving client environments.
Strong communication skills: You can explain a vector database to a CFO without losing them.

Nice To Haves

Experience with workflow automation platforms (Zapier, Make, n8n, or similar).
Familiarity with vector databases (Pinecone, Weaviate, Chroma) and embedding pipelines.
Exposure to low-code/no-code tools alongside custom-code solutions.
Prior client-facing, consulting, or forward-deployed engineering experience.
Experience working with SMB clients across industries such as professional services, healthcare, logistics, or retail.

Responsibilities

Embed directly with clients to discover operational pain points, map workflows, and identify high-ROI opportunities for AI and automation.
Design and build AI agents using frameworks such as LangChain, LangGraph, AutoGen, or similar, including tool-use, memory, and multi-agent orchestration patterns.
Develop AI-powered workflows that integrate with clients' existing systems (CRMs, ERPs, cloud platforms, communication tools, etc.)
Engineer automation solutions across areas such as document processing, data extraction, reporting, customer communication, and internal operations.
Own the full delivery lifecycle from scoping and architecture to build, testing, handoff, and lightweight documentation.
Train and enable client teams to maintain and iterate on solutions post-deployment.
Serve as a trusted technical advisor, translating complex AI capabilities into clear business value for non-technical stakeholders.
Contribute internally by codifying reusable components, playbooks, and delivery templates that scale across the practice.