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Principal Engineer Applied AI

Job in Abu Dhabi, UAE/Dubai
Listing for: Client of Discovered MENA
Full Time position
Listed on 2026-06-19
Job specializations:
  • Software Development
    Software Architect, AI Engineer (Applied/Software), DevOps
Salary/Wage Range or Industry Benchmark: 400000 - 500000 AED Yearly AED 400000.00 500000.00 YEAR
Job Description & How to Apply Below

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 a small, high‑caliber, decisive team 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 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, show confidence to push back firmly against unrealistic requests from stakeholders, and if a requirement cannot be met, use data to explain why it isn’t feasible and immediately pivot to offer viable, high‑quality alternative architectures to achieve the objective.

Responsibilities
  • Deeply Hands‑On & Current:
    Read code, run experiments, write prototypes, and produce reference implementations that other teams build from.
  • Data‑Driven Pushback:
    Use concrete benchmarks, metrics, and system constraints to push back firmly against unfeasible or high‑risk stakeholder demands.
  • Alternative Architecture Design:
    Immediately deliver alternative technical solutions when rejecting a request, ensuring the organization navigates constraints without losing momentum.
  • Cross‑Team Technical Direction:
    Set architecture, interfaces, deployment patterns, and standards for systems that span multiple engineering teams, ensuring they hold up under production pressures.
  • Navigating AI Realities:
    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:
    Raise the organization's technical ceiling by mentoring senior and staff engineers, pulling out the strongest technical thinking, and setting a high bar in technical reviews.
  • Strategic, High‑Stakes Impact:
    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.
Qualifications
  • 12+ years of software engineering experience, with a proven track record of operating at a staff or principal level.
  • Current, active technical depth – still write and read code, ensuring credibility in engineering rooms.
  • Demonstrated ability to handle multi‑stakeholder environments, 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.
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