What are the responsibilities and job description for the AI Solutions Architect position at Jobgether?
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a AI Solutions Architect based in Canada.
We are seeking an experienced AI Solutions Architect to design and guide the evolution of enterprise-scale artificial intelligence platforms.
This role focuses on transforming AI concepts into reliable, scalable, and production-ready solutions.
You will collaborate closely with engineering, product, data, and architecture teams to define modern AI strategies and technical frameworks.
The position requires deep expertise in multi-agent systems, RAG architectures, LLM integrations, and cloud-native environments.
You will influence critical decisions around AI governance, reliability, security, and operational excellence.
This is an opportunity to shape the future of intelligent platforms while helping teams adopt responsible and scalable AI practices.
The AI Solutions Architect will be responsible for defining technical direction, creating architectural standards, and supporting the delivery of advanced AI solutions across enterprise environments. The role combines strategic thinking with hands-on architecture expertise to ensure AI platforms are scalable, secure, and optimized for real-world usage.
- Review existing AI initiatives with engineering teams, identify improvement opportunities, and help establish a unified AI platform strategy.
- Design reference architectures for multi-agent orchestration, intent classification, routing frameworks, and context management across AI workflows.
- Define strategies for managing AI context, including token optimization, conversation memory, summarization approaches, and information flow between agents.
- Architect Retrieval-Augmented Generation (RAG) solutions, including ingestion pipelines, retrieval strategies, reranking approaches, and quality optimization.
- Establish AI governance practices covering prompt management, testing frameworks, monitoring, version control, and rollback processes.
- Define resiliency patterns for LLM-powered applications, including provider failover, cost management, observability, and graceful degradation strategies.
- Establish AI safety standards related to security, privacy protection, responsible AI practices, and hallucination mitigation.
- Collaborate with technical and business stakeholders to create implementation roadmaps and guide execution priorities.
- Produce architectural documentation, technical recommendations, and strategic guidance to support AI platform development.
Requirements:
The ideal candidate is a senior technology professional with extensive experience designing and delivering enterprise AI architectures. You should have a strong background in software architecture, machine learning systems, and cloud platforms, with proven experience bringing AI solutions into production environments.
- 10 years of experience in software engineering or machine learning architecture, with at least 5 years focused on enterprise AI solutions.
- Proven experience designing and deploying multi-agent AI platforms capable of supporting production-scale workloads.
- Strong expertise in conversational AI systems, including session management, memory strategies, and context handling.
- Hands-on experience architecting scalable RAG pipelines, including document processing, retrieval optimization, embeddings, and ranking strategies.
- Experience working with multiple LLM providers such as OpenAI, Claude/Bedrock, Gemini, or open-source models, understanding trade-offs between quality, cost, latency, and reliability.
- Experience designing intent classification and routing systems handling complex user interactions, multi-label classification, and fallback mechanisms.
- Knowledge of real-time and batch machine learning pipelines and the appropriate use cases for each approach.
- Strong cloud architecture experience with platforms such as AWS, GCP, or Azure.
- Experience with AI orchestration frameworks such as LangGraph, LangChain, or LlamaIndex.
- Familiarity with self-hosted model serving technologies and approaches for cost optimization or sensitive workloads.
- Understanding of AI security, governance, compliance, and responsible AI principles.
- Strong communication skills with the ability to translate complex technical concepts into clear recommendations for technical and non-technical audiences.
- Experience creating AI platform standards, architecture guidelines, or engineering best practices is highly desirable.
Benefits:
- Fully remote contract opportunity with required overlap with US time zones.
- Initial 6-month engagement with potential extension.
- Opportunity to influence enterprise AI strategy and platform development.
- Collaboration with experienced engineering, product, data, and architecture teams.
- Opportunity to work on advanced AI systems involving LLMs, multi-agent architectures, and intelligent automation.
- Flexible consulting environment focused on innovation and technical impact.
- Exposure to large-scale AI transformation initiatives and modern cloud technologies.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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