AI Architect – Agentic Systems

CanadaRemoteFull-timemid

OtherAi Architect

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Quick Summary

Overview

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Architect – Agentic Systems based in Canada.

Technical Tools

OtherAi Architect

This fully remote role offers the opportunity to design and build advanced agentic AI systems across industries including healthcare, finance, manufacturing, and retail. You will combine generative AI, machine learning, cloud engineering, and full-stack development to create production-ready AI solutions. The role spans everything from RAG and LLM orchestration to multi-agent architectures, classical ML, and enterprise integrations. You will work closely with subject-matter experts to translate complex business workflows into intelligent systems. Your solutions will interact with enterprise applications, data platforms, IoT environments, and real-world operational workflows. This is a hands-on architecture role for an experienced AI professional interested in building the next generation of enterprise AI.

Design and implement agentic AI workflows and architectures for use cases across healthcare, finance, manufacturing, retail, and other enterprise domains.
Build LLM-powered systems incorporating RAG, embeddings, tool-calling agents, and multi-agent orchestration.
Develop healthcare AI solutions such as clinical assistants, triage agents, care pathway optimization, and revenue-cycle-management automation.
Design AI architectures for manufacturing workflows and integrate intelligent systems with sensor data, MES, ERP, and IoT platforms.
Develop multi-agent financial AI solutions for analysis, compliance, advisory, and related workflows, including RAG over financial documents, contracts, policies, and filings.
Build and deploy classical machine learning models for risk scoring, prediction, classification, NLP, time-series analysis, clustering, and anomaly detection.
Implement compliance-aware AI architectures with appropriate auditability, traceability, and governance, including HIPAA-aware solutions where applicable.
Develop full-stack AI applications using Python APIs, AI services, and user-facing dashboards.
Integrate AI solutions with EHRs, data lakes, CRM platforms, customer data, and healthcare systems, with FHIR/HL7 integration experience considered valuable.
Collaborate with subject-matter experts to translate business and medical workflows into effective agent logic and AI-enabled processes.
Deploy, monitor, troubleshoot, and continuously optimize production AI systems in Azure.
Communicate technical architecture and AI decisions clearly to non-technical stakeholders while balancing business requirements, technical constraints, and responsible AI considerations.

Requirements

~2 min read

8+ years of strong experience building Python-based AI systems and production-grade AI solutions.
8+ years of hands-on experience with generative AI technologies, including LLMs, RAG, embeddings, and prompt engineering.
8+ years of experience with traditional machine learning, including classification, regression, NLP, time-series analysis, and anomaly detection.
5+ years of full-stack development experience covering API design and UI integration.
5+ years of hands-on Azure experience, ideally including Azure ML, Azure OpenAI, Azure Functions, and AKS.
5+ years of experience working in regulated or compliance-heavy environments.
Bachelor's degree in Computer Science or a related field, or equivalent professional experience.
Demonstrated experience building and operating production AI systems rather than only prototypes or proof-of-concepts.
Strong understanding of agentic AI concepts and emerging AI architectures, with a genuine interest in next-generation AI systems.
Ability to collaborate effectively with subject-matter experts and translate domain knowledge into technical solutions.
Strong communication skills, including the ability to explain AI architecture, system behavior, and AI-driven decisions to non-technical stakeholders.
Strong learning mindset, adaptability, and ability to work across multiple technical and business domains.
Multi-domain industry experience is an advantage.
Experience with AWS, GCP, or NVIDIA AI technologies is a plus.
Knowledge of model governance and AI explainability is beneficial.
Experience with document intelligence pipelines is considered an asset.
Experience with FHIR/HL7 and healthcare system integrations is a plus.