Job Description
Shape the Future of Autonomous Intelligence
At Nexus Horizon AI, we are not just preparing for 2026; we are architecting it. As a pioneer in the Agentic AI space, we are building the next generation of autonomous systems capable of complex reasoning, multi-modal interaction, and self-improvement. We are looking for a visionary Lead Agentic AI Architect to join our elite engineering team and define the technical backbone of our upcoming ecosystem.
The Role
In this pivotal role, you will lead the design and implementation of our core Agentic AI frameworks. You will bridge the gap between cutting-edge research and production-grade deployment, ensuring our autonomous agents are scalable, secure, and capable of executing complex, long-horizon tasks with human-like autonomy.
Why Join Us?
- Future-Ready Tech: Work on the technologies defining the post-2026 AI landscape.
- Elite Team: Collaborate with world-class researchers and engineers.
- Equity & Impact: Competitive compensation packages and significant equity stakes.
Responsibilities
- Architect Agentic Systems: Design and implement scalable architectures for autonomous AI agents capable of planning, executing, and adapting to dynamic environments.
- Model Optimization: Lead the optimization of Large Language Models (LLMs) and Transformers for high-performance inference and reduced latency.
- Multimodal Integration: Integrate vision, audio, and text modalities into unified agent frameworks to create holistic AI experiences.
- MLOps & Infrastructure: Build robust CI/CD pipelines and MLOps infrastructure using Kubernetes and Ray to support continuous learning and deployment.
- Safety & Alignment: Establish rigorous testing protocols and safety guardrails to ensure AI behavior remains aligned with ethical standards and user intent.
- Technical Leadership: Mentor a team of senior engineers and guide them through the complexities of next-gen AI development.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field (or equivalent extensive industry experience).
- Experience: 5+ years of professional software engineering experience with a deep focus on Machine Learning and AI systems.
- Core Tech: Proficiency in Python, PyTorch, TensorFlow, and modern MLOps tools (MLflow, DVC, Kubeflow).
- Frameworks: Strong understanding of Agentic AI patterns, LLM orchestration (LangChain, LlamaIndex), and RAG architectures.
- System Design: Experience designing distributed systems capable of handling high-throughput, low-latency workloads.
- Language: Fluent in English; ability to communicate complex technical concepts to non-technical stakeholders.