About the Role We’re seeking an inventive AI Applied Scientist to us and drive breakthroughs in agentic AI architecture. You will conduct cutting-edge research, design novel algorithms, and help translate state-of-the-art theory into practical solutions. Your work will shape the future of autonomous agents, creative reasoning, and predictive intelligence. This is a hybrid role between research and applied development—working with the best minds in AI and contributing meaningful innovation with real-world impact. Key Responsibilities •End-to-end ownership of products / features: Experience of delivering product features / products •Manage a small pod for product / feature delivery: Manage a team of 4-6 people to deliver the required features / products •Mentorship: Guide and support AI engineers, elevating team expertise and scientific rigor. •Cross-functional Collaboration: Work with engineers, data teams, and evaluation partners to integrate research outputs into evaluation pipelines and prototypes. •Research & Architect Novel AI Systems: Collaborate with the G42 Technical team to conceive and implement advanced agentic AI architectures. •Algorithm Development: Build new algorithms for reasoning, planning, causal inference, and trend forecasting— anchored in the latest scientific advances. •Innovate and Ideate: Drive ideation and design of new models, expanding the frontier of AI capabilities. •Publish and Present: Contribute high-impact research outcomes to top-tier academic venues and technical outlets. Qualifications •Academic Credentials: Master's or Ph.D. in AI/ML, Computer Science, or a closely related field. •Experience Level: 6 years+ (negotiable if the candidate is good and experience is less than 6 years) of relevant work experience, ideally at the intersection of research and applied AI development. • Technical Expertise: Strong foundation in LLMs and Multimodal models, and techniques such as reasoning, planning, causal inference, forecasting. Proficiency in programming languages and frameworks commonly used in AI research (e.g. Python, PyTorch). Experience in designing and evaluating AI models and algorithms, with a research-driven mindset. Scholarly Output: Record or strong potential for publishing in high-impact conferences or journals. Soft Skills: Excellent problem-solving and critical-thinking abilities. Effective communication skills, capable of both mentoring and translating complex concepts for diverse audiences.
About the Role We are seeking a highly accomplished Principal AI Architect / Tech Delivery Head to lead the technical design, architecture, and delivery excellence of our agentic AI systems. This role is central to shaping the core orchestrator, master agents, and multi-agent reasoning frameworks that power our R&D Lab. You will serve as the senior-most technical leader—owning system architecture, research-to-production translation, engineering quality, and technical governance. Working alongside applied scientists, engineers, data teams, and product leaders, you will define architectural patterns, ensure reliability, and guide the creation of novel multi-agent capabilities. This is a hands-on technical leadership role requiring deep expertise in LLMs, distributed systems, agent frameworks, and scalable AI infrastructure. Key Responsibilities Architect the Multi-Agent System: Own the end-to-end architecture for the Central Orchestrator, Master Agents, interoperability standards, and runtime execution models. Technical Leadership: Set engineering direction, define technical standards, establish best practices, and oversee system reliability and scalability. Delivery Ownership: Ensure high-quality, timely delivery of R&D prototypes, internal pilots, and platform capabilities. Mentorship: Coach applied scientists, AI engineers, and platform engineers; elevate engineering rigor and problem-solving depth. Cross-Functional Collaboration: Work with Product, Data Engineering, MLOps, and Evaluation teams to translate research ideas into robust, deployable systems. R&D Decision-Making: Drive architectural choices, technology selection, performance optimization, and system-level trade-offs. Security & Compliance: Ensure architectures meet requirements for sensitive data, hybrid cloud, and enterprise/government operational constraints. Technical Review & Governance: Lead design reviews, provide high-level code oversight, and ensure long-term architectural coherence. Qualifications Experience 10+ years of experience in AI/ML engineering, distributed systems, or large-scale software architecture. Demonstrated expertise designing and delivering complex multi-component AI systems. Prior leadership experience guiding engineering teams (player/coach model). Technical Expertise Deep knowledge of LLMs, agentic systems, and reasoning frameworks. Expertise in distributed systems, microservices, event-driven workflows, and hybrid cloud architectures. Strong programming background (Python, Go, or similar). Experience with model-serving infrastructure, vector databases, orchestration frameworks, and modern MLOps practices. Soft Skills Strong systems thinking and architectural clarity. Excellent written and verbal communication. Ability to make high-quality technical decisions under ambiguity. Who You Are A hands-on architect who enjoys solving deep technical problems while guiding teams. A systems thinker who balances innovation with delivery execution. A collaborative leader comfortable navigating research, engineering, and product domains. A technical visionary who can design future-proof platforms while enabling rapid iteration.