Job Description
Are you ready to define the intelligence of tomorrow? Quantum Horizon is seeking a visionary Senior Agentic AI Architect to lead the development of next-generation autonomous systems. As we approach 2026, the era of passive AI assistants is over. We are building Agentic AI—autonomous agents capable of complex decision-making, multi-step planning, and self-correction.
In this high-impact role, you won't just write code; you will architect the neural foundations of a self-improving workforce. You will work at the intersection of Deep Learning, Reinforcement Learning, and Distributed Systems. If you are passionate about the future of AI and possess the technical prowess to handle massive-scale model deployment, we want to meet you.
Why Join Us?
- Work with state-of-the-art Generative Models and LLMs.
- Shape the roadmap for autonomous AI agents.
- Competitive equity and benefits package.
Ready to shape the future? Apply today.
Responsibilities
- Architect Autonomous Workflows: Design and implement complex agent architectures capable of reasoning, planning, and executing multi-step tasks with minimal human intervention.
- Model Optimization: Fine-tune and optimize large foundation models (LLMs) for high-performance inference in real-time environments, focusing on latency and cost-efficiency.
- Research Integration: Stay at the forefront of AI research, integrating cutting-edge advancements in Reinforcement Learning from Human Feedback (RLHF) and Chain-of-Thought reasoning.
- MLOps Infrastructure: Build scalable, robust MLOps pipelines to manage the lifecycle of our AI agents, ensuring seamless deployment and monitoring.
- Ethical AI Governance: Establish guidelines and safeguards to ensure AI autonomy aligns with safety protocols and ethical standards.
- Collaboration: Partner with cross-functional teams including Product, Engineering, and Security to deliver AI-driven solutions that solve real-world problems.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of experience in Machine Learning, Deep Learning, or Software Engineering with a strong focus on AI.
- Technical Skills: Deep proficiency in Python, PyTorch, or TensorFlow. Experience with Large Language Models (GPT, LLaMA, etc.) and RAG (Retrieval-Augmented Generation) architectures.
- System Design: Strong background in distributed systems, cloud computing (AWS/GCP/Azure), and containerization (Kubernetes/Docker).
- Problem Solving: Demonstrated ability to tackle ambiguous, high-complexity problems with innovative solutions.
- Leadership: Experience leading technical teams or mentoring junior engineers.