Principal Engineer, AI/ML
Harnham
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
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