About the Role
Our client is seeking a practical and hands-on AI Integration Specialist to design, build, and implement AI capabilities across the business. This is a senior individual-contributor role working closely with engineering, product, IT, and business teams.
The role will focus on turning AI ideas into working systems, including RAG pipelines, AI agents, cloud-based AI infrastructure, business system integrations, and internal AI tools.
Key Responsibilities
Develop and maintain an AI integration roadmap across business systems, customer platforms, and engineering tools.
Identify and scope AI opportunities across ERP, CRM, documentation, product, engineering, and customer data platforms.
Design and implement Retrieval-Augmented Generation pipelines using structured and unstructured data sources.
Define ingestion, chunking, embedding, vector database, retrieval, and evaluation strategies.
Build and deploy AI workloads on cloud infrastructure using serverless, data lake, workflow, and managed AI services.
Integrate AI systems with business applications using APIs, databases, automation tools, and cloud services.
Prototype internal AI tools such as intelligent document search, call-note summarization, workflow automation, and anomaly detection.
Support customer-facing AI features such as natural-language querying, predictive insights, intelligent thresholds, and technical data search.
Create secure access models for AI systems, including least-privilege permissions, credential handling, and data segmentation.
Support responsible AI governance, including AI impact assessments, risk classification, human-in-the-loop controls, and security documentation.
Work with engineering and product teams to support AI-assisted development tools, data connectivity, and internal adoption.
Required Qualifications
3+ years of hands-on experience designing and deploying AI/ML systems in production environments.
Strong experience with RAG architecture, including chunking, embeddings, vector databases, retrieval scoring, and evaluation.
Experience integrating with LLM platforms such as OpenAI, Anthropic Claude, AWS Bedrock, or similar.
Experience building AI agents, tool-use workflows, or structured context integrations.
Strong cloud experience, preferably with AWS services such as S3, Glue, Athena, Lambda, DynamoDB, Step Functions, Bedrock, SageMaker, or similar.
Experience with infrastructure-as-code and CI/CD pipelines.
Strong SQL skills and experience working with multiple data sources, including relational databases, document systems, and object storage.
Experience integrating AI systems with business applications using REST APIs, GraphQL, OData, or similar.
Programming proficiency in Python and at least one of TypeScript/JavaScript, C#/.NET, or C/C++.
Comfortable working in Git-based development environments.
Ability to write clear architecture documents, integration plans, and technical documentation.
Experience working with security or compliance frameworks such as ISO 27001, SOC 2, or similar.
Preferred Qualifications
Experience with industrial IoT, time-series sensor data, infrastructure monitoring, or industrial data platforms.
Experience with managed RAG or cloud-native knowledge base tools.
Familiarity with AI-assisted development tools such as Claude Code, Kiro, or similar.
Knowledge of multi-tenant authorization models.
Experience with GIS, GeoJSON, Esri ArcGIS, CMMS, ERP, or asset-management system integrations.
AWS certifications would be considered an asset.
Ideal Candidate
The ideal candidate is a hands-on AI integration professional who can work across AI, data, cloud infrastructure, software development, and business systems. They should be comfortable building practical AI solutions, working with technical teams, and helping an organization adopt AI in a secure, scalable, and useful way.
Pay: $140,000.00-$175,000.00 per year
Benefits:
- Company pension
- RRSP match
Experience:
- designing and deploying AI/ML systems: 3 years (preferred)
Work Location: Hybrid remote in Calgary, AB
