Principal AI Architect

Harnham; Toronto; Hybrid; CAD 200,000 - 220,000; Full time

Benefits offered by this job

Flexible hybrid working environment

Competitive CAD 200k–220k salary

Job summary

Harnham is seeking a seasoned AI Architect to define the technical foundations of a rapidly evolving AI platform. You will lead the design of agentic AI architectures, establish standards, and drive scalable, production-ready products that transform content and knowledge workflows.

The role involves mentoring engineers, partnering with ML, product, and engineering teams, and evaluating new agentic AI advancements to deliver measurable impact across the organization.

Qualifications

• 10+ years of software engineering experience delivering production AI systems at Staff/Principal level.
• Proven experience building and shipping agentic AI products, including multi-agent systems and agent execution environments.
• Deep expertise in AI evaluation methodologies and regression testing.
• Strong experience with Retrieval-Augmented Generation (RAG) and agentic search architectures.
• Strong understanding of large language models, retrieval systems, and agent design patterns.
• Expertise in large-scale cloud-based AI infrastructure and deployment pipelines.
• Proficient Python development and hands-on experience with agent frameworks.
• Ability to influence engineering organizations through architecture and leadership.

Responsibilities

• Lead design and evolution of the agentic AI architecture and scalable infrastructure.
• Build AI infrastructure across evaluation, testing, observability, tracing, and production environments.
• Design agent orchestration layers, multi-agent workflows, and memory/planning systems.
• Collaborate with engineering to review architecture and mitigate risks.
• Establish AI quality framework including datasets, testing, and release gates.
• Mentor senior engineers through architecture reviews and leadership activities.
• Evaluate emerging AI advancements and apply to scalable solutions.

Skills

Senior software engineering

AI architecture

Agentic AI

LLM orchestration

RAG architectures

Python development

Distributed systems

Mentoring engineers

Cloud architecture

Tools

LangChain

LangGraph

Microsoft Agent Framework

AWS

Job description

Our client is a high-growth SaaS technology company at the forefront of applying AI to complex, knowledge-intensive workflows. With a strong investment in agentic AI and next-generation automation, they are building scalable, production-ready systems that transform how organizations interact with content, documents, and enterprise knowledge.

This is a rare opportunity for a seasoned AI architect to define the technical foundations of a rapidly evolving AI platform and have a significant impact on the future direction of the business.

RESPONSIBILITIES

• Lead the design and evolution of the company's agentic AI architecture, establishing standards, patterns, and infrastructure for scalable AI-driven product experiences.
• Build and enhance critical AI infrastructure across evaluation frameworks, testing systems, observability platforms, tracing capabilities, and production agent execution environments.
• Design and implement agent orchestration layers, multi-agent workflows, reasoning engines, memory systems, planning frameworks, and adaptive feedback mechanisms.
• Partner closely with engineering teams to review architecture, identify technical risks, and drive best practices without creating delivery bottlenecks.
• Establish a robust AI quality framework, including evaluation datasets, grading systems, regression testing, release gates, experimentation platforms, and production feedback loops.
• Collaborate with engineering, machine learning, and product leaders to make informed architectural decisions and ensure reliable delivery of advanced AI capabilities.
• Mentor senior engineers through design reviews, architecture discussions, and technical leadership, raising standards across the wider engineering organization.
• Evaluate emerging advancements in agentic AI and apply them to build scalable, measurable, and impactful solutions.

SKILLS AND EXPERIENCE

Required

• 10+ years of software engineering experience with substantial expertise designing and delivering production AI systems at Staff, Principal, or equivalent level.
• Proven experience building and shipping agentic AI products, including multi-agent systems, LLM orchestration, tool-use frameworks, and agent execution environments.
• Deep expertise in AI evaluation methodologies, including quality rubrics, curated datasets, deterministic and model-based grading, regression testing, and continuous feedback systems.
• Strong experience with advanced Retrieval-Augmented Generation (RAG) and agentic search architectures, including query decomposition, multi-hop retrieval, hybrid search, reranking, metadata filtering, source routing, evidence validation, citations, and confidence scoring.
• Strong understanding of large language models, retrieval systems, and modern agent design patterns.
• Expertise in large-scale systems architecture, cloud-based AI infrastructure, model serving, deployment pipelines, monitoring, and observability.
• Strong Python development skills and hands-on experience with agent frameworks such as LangChain, LangGraph, Microsoft Agent Framework, or similar technologies.
• Demonstrated ability to influence and guide engineering organizations of 15-20+ engineers through architecture and technical leadership.

Preferred

• Experience building agent-based systems within SaaS products focused on content, document management, or enterprise knowledge workflows.
• Experience with cloud-native machine learning infrastructure on AWS or comparable cloud platforms.
• Prior experience operating as a Principal Architect, Distinguished Engineer, or Staff-plus technical leader in a fast-growth technology environment.

BENEFITS

• Competitive base salary of CAD $200,000 - $220,000.
• Opportunity to shape the future of a cutting-edge AI platform.
• High-impact individual contributor role with significant technical ownership.
• Collaborative, innovation-focused engineering culture.
• Flexible hybrid working environment.
• Career growth within a rapidly scaling technology organization.

KEY TERMS

Principal AI Infrastructure Architect | Principal Engineer | AI Architecture | Agentic AI | Multi-Agent Systems | LLMs | RAG | Agent Frameworks | LangChain | LangGraph | Microsoft Agent Framework | AI Infrastructure | AI Evaluation | Observability | Tracing | Model Serving | Python | Distributed Systems | SaaS | Machine Learning Platform | AWS | Enterprise AI | Staff Engineer | Principal Architect | AI Quality Engineering | Knowledge Systems | Retrieval Systems | Orchestration Frameworks