Live opening · Posted 13 days ago

Senior AI Solutions Engineer

VRIZE · Canada (Remote)
Linkedin No
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At a glance

The key details from the original listing.

Posted 13 days ago
CompanyVRIZE
LocationCanada (Remote)
Work modeNo
SourceLinkedin
Listed13 days ago

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About the role

Description supplied by the original job listing.

Location: Canada (Remote)
Work Hours: 8:00 AM – 5:00 PM Pacific Time (Strict & Non-Negotiable)
Role Overview
We are seeking a production-focused Senior AI Solutions Engineer based in Canada to architect, build, and scale high-impact AI workflows, agentic automation, and internal tooling within our enterprise production systems.
In this role, you will bridge the gap between high-level business strategy and hands-on engineering execution. You will work directly with business stakeholders to clarify ambiguous requirements, design robust solution architectures around Claude and enterprise LLM APIs, and embed AI capabilities into existing, complex codebases.
Key Responsibilities
End-to-End Solution Ownership: Take loosely defined business problems and drive them from early architectural design through to deployment and rapid iteration.
Architectural Leadership: Design scalable AI applications, copilots, workflow automations, and agentic pipelines integrated into multi-language enterprise applications.
Cross-Functional Alignment: Collaborate closely with non-technical business partners and technical peers to validate requirements, ask probing questions upfront, and align on clear technical roadmaps.
Production Integration: Step into established, non-greenfield codebases to modify, extend, and embed AI APIs and automation tooling without requiring complete architecture handoffs.
Constructive Collaboration: Actively challenge assumptions when requirements are inefficient or unclear, presenting well-reasoned technical alternatives to keep teams moving forward.
Key Requirements
1. Communication & Autonomy
Direct & Concise Communication: Strong written and verbal communication skills. Ability to explain technical trade-offs clearly to both engineering peers and business partners without unnecessary complexity.
Self-Directed Problem Solver: High degree of autonomy. Able to navigate ambiguity, drive alignment across delivery teams, and own outcomes end-to-end.
2. Technical & AI Ecosystem
GenAI & Solution Architecture: 2+ years designing and delivering enterprise AI/GenAI solutions, backed by 10+ years of software engineering experience, including scalable architecture, API integration, security, observability, and production deployment.
Claude Experience (Mandatory): Proven hands-on experience designing, developing, and shipping production solutions using Claude and Claude APIs, including tool/function calling, structured outputs, prompt/context management, and enterprise integration patterns.
Agentic AI & Multi-Agent Systems: Strong experience designing agentic and multi-agent architectures, including agent orchestration, supervisor/worker patterns, task decomposition, agent-to-agent communication, dynamic routing, shared/isolated state, memory management, human-in-the-loop workflows, retries, guardrails, and failure handling.
AI Tooling & Frameworks: Deep hands-on experience with Python, RAG, Vector Databases, embeddings, semantic/hybrid search, prompt pipelines, and context engineering, using frameworks/protocols such as LangGraph, LangChain, and MCP.
Agent Orchestration & Tool Integration: Experience building agents that securely interact with APIs, databases, enterprise systems, search/RAG services, and MCP tools, with stateful workflow execution, checkpointing, structured tool invocation, and authorization controls.
AI Evaluation & Observability: Experience implementing LLM/agent evaluation, tracing, monitoring, hallucination/groundedness checks, token and latency optimization, cost monitoring, and agent/tool-call debugging for production AI systems.
Core Stack Expertise: Working knowledge of at least one core technology stack—React, JavaScript/TypeScript, Java, or .NET—to enable rapid onboarding and integration with existing production systems.
3. Availability
Strict PST Schedule: Must be fully available and responsive during business hours (8:00 AM – 5:00 PM Pacific Time, Monday–Friday).
Preferred Qualifications / Pluses
Retail & Ecommerce Context: Familiarity with digital commerce workflows, AI-powered search, pricing, customer experience, or transactional platform paradigms.
Internal Platform Tooling: Experience delivering internal automation, operational tools, or developer platforms at enterprise scale.
Azure / Enterprise Cloud: Hands-on experience with Azure OpenAI or multi-cloud platform integrations.
About VRIZE
VRIZE is a global digital engineering and technology consulting company that partners with leading enterprise organizations to accelerate digital transformation through AI, cloud, data, and modern software engineering. Our teams specialize in delivering innovative, scalable solutions across industries including retail, financial services, healthcare, manufacturing, and technology.
At VRIZE, you'll work alongside experienced engineers, architects, and business leaders to design and implement cutting-edge AI solutions that solve complex business challenges. We foster a collaborative, innovation-driven environment where continuous learning, technical excellence, and customer success are at the core of everything we do.

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