Member of Technical Staff

Overview:

G42 is a leading AI and technology group headquartered in Abu Dhabi, delivering transformative AI, cloud, and digital infrastructure solutions globally. Through its portfolio of AI platforms, sovereign cloud capabilities, advanced computing infrastructure, and industry-focused AI products, G42 is building the foundational technologies that power the next generation of intelligent systems.

Role Overview

We are seeking a highly accomplished Member of Technical Staff (MTS) to join our U.S. engineering organization and play a key role in shaping the future of large-scale AI infrastructure, agentic systems, and enterprise AI platforms.

This is a hands-on technical leadership position focused on designing, building, and scaling production-grade AI systems. The successful candidate will combine deep expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), multi-agent architectures, and cloud-native engineering with a passion for solving complex real-world challenges.

The MTS will work across strategic initiatives including GPUaaS (GPU-as-a-Service), Token Factory, Agentic Compute, AI Foundries, and enterprise AI platforms, helping drive innovation from concept through production deployment.

Responsibilities:

AI Platform Architecture & Development

• Design and build scalable AI platforms leveraging LLMs, RAG architectures, agentic workflows, and enterprise knowledge systems.
• Develop production-ready AI solutions across distributed and cloud-native environments.
• Architect high-performance AI services supporting model hosting, inference optimization, evaluation frameworks, and orchestration layers.
• Drive technical direction for GPU infrastructure utilization, token-based AI services, and next-generation AI platform capabilities.

Agentic AI & Advanced AI Systems

• Design and implement multi-agent systems capable of complex reasoning, task delegation, planning, and orchestration.
• Develop advanced agent frameworks enabling enterprise-scale autonomous workflows.
• Create evaluation frameworks to measure model performance, reliability, safety, and business outcomes.
• Collaborate with product and research teams to translate emerging AI innovations into production capabilities.

Cloud & Infrastructure Engineering

• Architect and deploy large-scale AI solutions on Azure and cloud-native platforms.
• Build resilient AI pipelines using technologies such as Kubernetes, APIs, vector databases, AI search, document intelligence, and distributed data services.
• Optimize system performance, scalability, security, and operational excellence across AI workloads.
• Contribute to platform standards, reusable engineering frameworks, and reference architectures.

Technical Leadership

• Provide technical leadership across cross-functional engineering initiatives.
• Mentor engineers through design reviews, architecture guidance, coding best practices, and technical problem-solving.
• Influence engineering strategy while remaining deeply hands-on in design and implementation.
• Establish best practices for AI development, model evaluation, deployment, and platform governance.

Innovation & Thought Leadership

• Drive experimentation with emerging AI technologies, foundation models, agent frameworks, and AI infrastructure services.
• Contribute to technical publications, whitepapers, open-source initiatives, and developer communities.
• Represent G42 in technical discussions with strategic customers, partners, and industry stakeholders.
• Identify opportunities to enhance G42's AI platform capabilities and accelerate adoption of innovative technologies.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related technical field.
• 15+ years of software engineering experience with a strong track record of delivering enterprise-scale platforms and solutions.
• Deep expertise in LLMs, RAG architectures, multi-agent systems, prompt engineering, model orchestration, and AI evaluation frameworks.
• Strong programming expertise in Python and/or C#.
• Experience building production AI solutions using modern AI frameworks and toolchains.
• Hands-on experience with cloud-native platforms and distributed systems.
• Expertise with Azure services such as Kubernetes, AI Search, Cosmos DB, API Management, and AI platform services.
• Proven ability to lead complex technical initiatives from architecture through production deployment.
• Strong communication skills with the ability to influence senior technical and business stakeholders.