Artificial Intelligence Consultant

Job summary

Identify valuable AI opportunities with clients, assess data readiness, risks, workflows, and ROI, and develop practical roadmaps and business cases. Design, prototype, and evaluate AI solutions; guide responsible implementation and adoption; and lead client workshops, training, and engagement activities.

Job details

What you’ll do Meet with client executives and teams to find high-value AI opportunities and separate real use cases from hype Assess data readiness, workflows, risks, and ROI, and turn findings into clear roadmaps and business cases Design and prototype solutions using LLMs, retrieval-augmented generation (RAG), agents, classification, forecasting, and computer vision Build proofs of concept and production pilots with Python and platforms such as Azure OpenAI, AWS Bedrock, Google Vertex AI, OpenAI, Anthropic, or Hugging Face Work with data engineers and developers to connect solutions to client systems, data pipelines, and APIs Evaluate models rigorously: accuracy, cost, latency, bias, and safety, with testing methods clients can trust Guide responsible AI practice: privacy (PIPEDA and provincial laws), governance, security, and human oversight Translate technical tradeoffs into plain language for executives, and business needs into technical requirements for engineers Run workshops, demos, and training sessions that help client teams adopt AI and actually use it Support change management so new tools stick after the project ends Contribute to proposals, reusable assets, and internal research, and share what you learn with the team Find your level Level Typical experience What you’ll own AI Consultant I-0-2 years : Prototyping, data analysis, research, documentation, and client support, learning on live projects with a dedicated mentor AI Consultant II - 2-5 years : Owning workstreams end to end, leading solution design, running client workshops, managing day-to-day client relationships, mentoring Senior AI Consultant - 5+ years : Leading engagements, shaping AI strategy for clients, scoping and selling work, setting technical and ethical standards, developing the team Promotion criteria are written down at every level, with regular career conversations. You can grow as a hands-on technical expert, toward strategy and leadership, or into practice management. What you bring Must have Solid foundations in data and AI: Python, SQL, and an understanding of machine learning and modern LLM techniques Hands-on experience building something with AI, through a job, internship, coursework, or a serious personal project Clear communication: you can explain a model to a CFO and a business problem to an engineer Curiosity about how businesses work and a practical, results-first mindset Comfort with ambiguity, since client problems rarely arrive well defined Degree or diploma in Computer Science, Data Science, Engineering, Statistics, Mathematics, Business Analytics, or a related field, or equivalent experience. A strong portfolio counts as much as a degree. Legal authorization to work in Canada (citizens, permanent residents, and valid work permit holders) Nice to have (not required) Experience with prompt engineering, RAG, vector databases, agent frameworks (LangChain, LlamaIndex), or fine-tuning Cloud experience on Azure, AWS, or GCP, and familiarity with MLOps and deployment practices Consulting, client-facing, or customer-success experience Certifications: Azure AI Engineer, AWS Machine Learning, Google Professional ML Engineer, or similar Knowledge of AI governance and risk frameworks (NIST AI RMF, ISO/IEC 42001) and Canadian privacy and AI regulation Industry background in [financial services, healthcare, public sector, retail, energy, manufacturing, legal, etc.] Fluency in French, an asset for clients in Quebec or bilingual organizations [if applicable] GitHub projects, Kaggle work, published writing, or demos you can show

What you’ll do

Identify valuable AI opportunities with clients, assess data readiness, risks, workflows, and ROI, and develop practical roadmaps and business cases. Design, prototype, and evaluate AI solutions; guide responsible implementation and adoption; and lead client workshops, training, and engagement activities.

Requirements

Candidates need foundations in Python, SQL, machine learning, and modern LLM techniques, plus hands-on AI project experience and strong communication skills. A relevant degree or diploma, or equivalent experience, is required, as is legal authorization to work in Canada; consulting experience, cloud platforms, and AI governance knowledge are assets.

Listed skills

• Python · Preferred
• SQL · Preferred
• Machine learning · Preferred
• Data analysis · Preferred
• prompt engineering · Preferred
• Communication · Preferred
• Change Management · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• SQL
• Machine Learning
• Large Language Models
• Retrieval-Augmented Generation
• Data Analysis
• AI Solution Design
• Prompt Engineering
• Model Evaluation
• Responsible AI
• AI Governance
• Cloud Platforms
• Client Consulting
• Communication
• Change Management
• Computer Vision

Job areas

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

More jobs from SMARTFOX