Principal Engineer - Applied AI

Principal Engineer – Applied AI

Abu Dhabi - Onsite

80,000 - 100,000 AED p/m

About the Project

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, the timelines are short, and the stakes are exceptionally high. What they ship has to operate flawlessly inside strict data sovereignty, security, and accountability constraints. They are small, high-caliber, decisive, and unwilling to accept the gap that usually exists between AI demos and AI in production.

Role Overview

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 do and 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.

Key Highlights of the Role

• Deeply Hands-On & Current: This is not an advisory role from afar. You will actively read code, run experiments, write prototypes that settle architectural debates, and produce reference implementations that other teams build from.
• Data-Driven Pushback: You will act as the empirical voice of reason, using concrete benchmarks, metrics, and system constraints to push back firmly against unfeasible or high-risk stakeholder demands.
• Alternative Architecture Design: When you say "no" to a request, you will immediately deliver alternative technical solutions, ensuring the organization navigates around constraints without losing momentum.
• Cross-Team Technical Direction: You will set the architecture, interfaces, deployment patterns, and standards for systems that span multiple engineering teams, ensuring they hold up under production pressures.
• Navigating AI Realities: You will design specifically for the complexities of operating AI in production, successfully managing non-determinism, model drift, latency, and cost at scale.
• Multiplying the Engineering Bar: You will raise the organization's technical ceiling by mentoring senior and staff engineers, pulling the strongest technical thinking out of teams, and setting an incredibly high bar in technical reviews.
• Strategic, High-Stakes Impact: You will represent engineering realities to leadership and external partners, making technical trade-offs legible to non-technical leaders while adhering to strict compliance, data privacy, and hosting constraints.

Core Qualifications

• 12+ years of software engineering experience, with a proven track record of operating at a staff or principal level.
• Current, active technical depth—you still write and read code, ensuring you are highly credible to a room of strong engineers.
• Demonstrated ability to handle multi-stakeholder environments, with clear evidence of using data-driven assertiveness to steer product and business requirements.
• Strong working knowledge of the current AI technology landscape (frontier models, RAG and retrieval architectures, agent frameworks, and inference infrastructure).
• Exceptional written and verbal communication—able to author complex architecture documents and represent technical truths directly to executive stakeholders.