Job Description
Are you ready to define the architecture of tomorrow's autonomous intelligence? Nexus Horizon AI is seeking a visionary Senior AI Architect to spearhead our next-generation Agentic AI initiatives. As we look toward 2026, we are building systems that go beyond simple chatbots—creating autonomous agents capable of complex reasoning, multi-step planning, and enterprise-grade execution.
In this pivotal role, you will design and implement sophisticated multi-agent systems that redefine how enterprises interact with Large Language Models (LLMs). You will work at the intersection of cutting-edge research and production-scale engineering, ensuring our AI is safe, scalable, and transformative.
Responsibilities
- Architect Agentic Workflows: Design and build complex multi-agent architectures that utilize LLMs for autonomous problem-solving and task execution.
- Model Optimization: Engineer and fine-tune proprietary and open-source models (e.g., Llama 3, GPT-4) to maximize performance and reduce latency for real-time applications.
- System Integration: Integrate AI agents with existing enterprise infrastructure, ensuring seamless data flow and API interoperability.
- Research & Development: Stay ahead of the curve on emerging AI trends (e.g., Reasoning Models, Tool Use, Memory Augmentation) to prototype novel features.
- Scalability & Reliability: Implement robust CI/CD pipelines and monitoring systems to ensure high availability of AI services in production environments.
- Mentorship: Guide a team of talented ML engineers and data scientists, fostering a culture of innovation and technical excellence.
Qualifications
- Experience: 8+ years of experience in software engineering, with at least 4 years specifically in AI/ML architecture or Machine Learning Operations (MLOps).
- Tech Stack: Proficiency in Python, PyTorch, or TensorFlow; extensive experience with LangChain or LlamaIndex for agent orchestration.
- Cloud Expertise: Deep understanding of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Distributed Systems: Strong background in designing distributed systems capable of handling high throughput and low-latency requirements.
- Educational Background: M.S. or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- Problem Solving: Proven track record of tackling ambiguous problems and delivering innovative technical solutions.