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Principal Engineer, AI/ML

Harnham

Toronto · Hybrid Full-time Lead 2w ago

About the role

Principal Engineer, AI/ML

Location: Hybrid — Canada or U.S. (Toronto, Ann Arbor, Frisco, Eagan)

About the Opportunity

We’re partnering with the innovation lab of a global enterprise organization at the forefront of applying AI, machine learning, and data science to real‑world professional workflows.

This group operates like a startup within a large‑scale platform, building cutting‑edge products that leverage LLMs, generative AI, and agentic systems to transform how users interact with complex information.

  • AI‑powered research and summarization
  • Intelligent content and knowledge systems
  • End‑to‑end automation of high‑value professional workflows

This is a rare opportunity to work on AI‑native products at scale, with meaningful real‑world impact.

Role Overview

As a Principal Engineer, AI, you will lead the design and delivery of next‑generation AI systems, driving technical strategy and building scalable, production‑grade GenAI applications.

You’ll operate at the intersection of:

  • Architecture
  • Hands‑on engineering
  • Cross‑functional leadership

What You’ll Do

  • Define and drive technical strategy for large‑scale AI initiatives
  • Architect and build LLM‑powered applications and agentic systems
  • Lead development of AI‑native features for content and knowledge platforms
  • Design scalable systems leveraging RAG, prompt engineering, and fine‑tuning
  • Integrate GenAI into user‑facing applications and workflows
  • Mentor and guide senior engineers and technical leaders globally
  • Partner with product and business teams to translate requirements into technical solutions
  • Own delivery of complex, high‑impact engineering initiatives

Core Tech Areas

  • AI/ML: LLMs, Generative AI, RAG, Agentic Systems
  • Languages: Python, Java, TypeScript (varies by team)
  • Cloud: AWS, Azure, or GCP
  • Frameworks: LangChain, LLM tooling, modern AI dev frameworks
  • Practices: DevOps, CI/CD, scalable distributed systems

What They’re Looking For

  • 10+ years of hands‑on software engineering experience
  • Proven experience building scalable AI / ML / GenAI systems in production
  • Strong understanding of:
    • LLMs and generative AI
    • RAG architectures
    • Prompt engineering and fine‑tuning
    • Agent‑based / agentic systems
  • Experience working in cloud environments (AWS, Azure, or GCP)
  • Background in enterprise SaaS or large‑scale platforms
  • Ability to operate in ambiguous, fast‑moving environments
  • Strong communication skills and ability to influence across teams
  • Experience mentoring engineers and driving engineering best practices

Nice to Have

  • Experience building AI systems for content, knowledge, or domain‑specific workflows (e.g., legal, compliance, research)
  • Familiarity with AI governance, evaluation, and responsible AI practices
  • Advanced degree in Computer Science, Engineering, or related field

Why This Role

  • Work on cutting‑edge GenAI systems with real‑world impact
  • Combine startup velocity with enterprise scale and resources
  • High visibility role with influence across product and engineering strategy
  • Opportunity to shape AI‑native platforms from the ground up

Ideal Candidate

  • Deeply technical AI/ML engineer with architectural mindset
  • Comfortable owning systems from design → build → scale
  • Passionate about LLMs, agentic systems, and applied AI
  • Thrives in environments requiring ownership, autonomy, and leadership

Requirements

  • 10+ years of hands-on software engineering experience
  • Proven experience building scalable AI / ML / GenAI systems in production
  • Strong understanding of LLMs and generative AI
  • Strong understanding of RAG architectures
  • Strong understanding of prompt engineering and fine-tuning
  • Strong understanding of agent-based / agentic systems
  • Experience working in cloud environments (AWS, Azure, or GCP)
  • Background in enterprise SaaS or large-scale platforms
  • Ability to operate in ambiguous, fast-moving environments
  • Strong communication skills and ability to influence across teams
  • Experience mentoring engineers and driving engineering best practices

Responsibilities

  • Define and drive technical strategy for large-scale AI initiatives
  • Architect and build LLM-powered applications and agentic systems
  • Lead development of AI-native features for content and knowledge platforms
  • Design scalable systems leveraging RAG, prompt engineering, and fine-tuning
  • Integrate GenAI into user-facing applications and workflows
  • Mentor and guide senior engineers and technical leaders globally
  • Partner with product and business teams to translate requirements into technical solutions
  • Own delivery of complex, high-impact engineering initiatives

Skills

AWSAzureCI/CDDevOpsGCPGenerative AIJavaLangChainLLM toolingLLMsPythonRAGTypeScript

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