Job Description
Are you ready to define the architecture of the autonomous future?
We are Nexus Horizon, a pioneering research lab building the foundational infrastructure for 2026. We are moving beyond static models to build dynamic, self-governing AI agents capable of complex decision-making. We are looking for a visionary Lead Agentic AI Engineer to join our core team in San Francisco.
In this role, you won't just be training models; you will be architecting the workflows that allow agents to perceive, reason, and act autonomously. If you want to be at the bleeding edge of artificial general intelligence (AGI) and build systems that matter, this is your opportunity.
Why join Nexus Horizon?
- Work on next-generation autonomous agents.
- Competitive salary and equity package.
- Top-tier talent in a collaborative environment.
Responsibilities
- Architect Autonomy: Design and implement robust multi-agent systems that can execute complex tasks independently with minimal human oversight.
- Reasoning Engine Development: Develop advanced chain-of-thought and reflection mechanisms to enhance LLM reasoning capabilities.
- System Optimization: Engineer high-throughput inference pipelines and optimize memory usage for long-horizon tasks.
- Tool Integration: Create seamless interfaces between AI agents and external tools, APIs, and databases.
- R&D Leadership: Conduct research on emerging paradigms in reinforcement learning and human-in-the-loop systems.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on AI/ML.
- Experience: 5+ years of experience in Machine Learning, with at least 2 years specifically in LLM development and deployment.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and modern NLP libraries (HuggingFace, LangChain, LlamaIndex).
- System Design: Strong understanding of distributed systems, microservices architecture, and cloud infrastructure (AWS/GCP).
- Problem Solving: Demonstrated ability to tackle novel problems in reasoning, planning, and multi-modal understanding.