Principal Engineer Applied AI
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About the Role
Discover the Opportunity Our client is building an elite, highly specialized AI engineering organization designed to put modern technology, data, and frontier AI at the center o.
Key Skills for This Role
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Overview
Discover the Opportunity Our client is building an elite, highly specialized AI engineering organization designed to put modern technology, data, and frontier AI at the center of large-scale, enterprise, and public-sector operations.
Their work spans frontier model evaluation and deployment, sovereign inference and serving infrastructure, retrieval and agentic systems, robust evaluation pipelines, and applied products built for mission-critical dependency.
The remit is unusually broad, our timelines are short, and the stakes are exceptionally high.
What we ship has to operate flawlessly inside strict data sovereignty, security, and accountability constraints.
We are small, high-caliber, decisive, and unwilling to accept the gap that usually exists between AI demos and AI in production.
Discover the Role I am looking for a Principal Engineer to be one of the deepest technical voices inside our organization.
You will set technical direction across multiple teams,lead the architectural decisions that no single team can own on its own, and raise the technical ceiling of the engineering organization through the work you doand the engineers you grow.
This is a senior, highly technical individual contributor role.
You will not run a line organization, but your influence will come from the quality of your technical judgment, the clarity of the systems you help design, and the decisions you unblock.
Crucially, this role requires a strong technical backbone.
You will be in the rooms where the hardest build/buy/partner calls are made, and where the question is whether a solution will hold up in production for high-stakes workloads.
You are expected to bring answers grounded in systems, constraints, and data meaning you have the confidence to push back firmly against unrealistic requests from stakeholders.
When a requirement cannot be met, you will use data to explain why it isn't feasible, and immediately pivot to offer viable, high-quality alternative architectures to achieve the objective.
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