Description:
We are seeking an experienced and pragmatic Senior AI Engineer to lead the end-to-end delivery of high-impact AI solutions. This role bridges technical engineering with strategic project execution, vendor management, and business alignment.
Key Behavioral Competencies
- Bridge-Builder: Seamlessly connect vendors, internal departments, IT, InfoSec, and leadership by translating complex technical concepts into business terms and driving unified alignment.
- Stakeholder Management: Build enduring trust with department heads and end-users, successfully managing expectations and navigating challenges proactively.
- Challenger Mindset: Critically evaluate internal assumptions, vendor proposals, and the status quo using a fact-based, constructive approach.
- Resilience & Pragmatism: Maintain steady momentum under shifting priorities and tight deadlines, prioritizing iterative delivery ("done is better than perfect") over endless optimization.
- Ownership & Business Acumen: Maintain full accountability from conceptualization to production performance while prioritizing high-value business use cases.
Team & Mission Overview
You will join a focused, hands-on AI team responsible for guiding the organization's comprehensive AI roadmap, spanning use-case discovery, execution, governance, and widespread adoption.
- Core Domains: Pensions administration, investment operations, and corporate support functions.
- Key Initiatives: Agentic assistants on Microsoft Teams, document intelligence platforms, automated data reconciliation, and enterprise AI governance frameworks.
- Infrastructure: A Microsoft-first ecosystem (Azure AI Foundry, Azure OpenAI, M365 Copilot, Copilot Studio, Power Platform). Strict compliance with UAE data residency, security, and regulatory frameworks is mandatory.
Core Responsibilities
- Solution Architecture & Delivery: Design, build, and scale end-to-end LLM applications, RAG pipelines, multi-agent workflows, and machine learning models from prototype to production.
- Project & Vendor Management: Oversee AI project lifecycles (scope, milestones, budget, risks) and lead vendor evaluations, technical proofs of concept, and strict performance accountability.
- Engineering & LLMOps: Establish robust data pipelines, CI/CD frameworks, automated hallucination/latency testing, cost tracking, and production monitoring.
- Governance & Security: Enforce organizational AI governance, access controls, human-in-the-loop validation, and comprehensive audit trails.
- Technical Leadership: Define engineering standards, mentor junior team members, and provide strategic recommendations on emerging models and platforms.
Qualifications & Technical Requirements
- Education & Experience: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline, with 6+ years in software, data, or ML engineering (including 2+ years specialized in LLM production deployment).
- Core Tech Stack: Expert proficiency in the Microsoft AI ecosystem (Azure OpenAI, Azure AI Foundry, Azure AI Search, Copilot Studio, Power Automate).
- Development & MLOps: Production-grade Python, SQL, REST APIs, prompt engineering, RAG, agentic frameworks (Semantic Kernel/Microsoft Agent Framework), and DevOps toolchains (GitHub/Azure DevOps, Docker, CI/CD).
- Preferred Background: Prior experience within regulated sectors (financial services, pensions, insurance, government) and bilingual fluency in English and Arabic.