Job Description
The Future is Now (and Coming in 2026). Nexus Horizon is building the autonomous enterprise of tomorrow. We are seeking a visionary Senior Agentic AI Engineer to lead the development of next-generation AI systems that redefine human-machine collaboration.
In this role, you won't just be deploying models; you will architect the intelligence layer for our products. You will focus on building Autonomous Agents capable of complex reasoning, self-correction, and long-horizon planning—features that are set to define the industry standard in 2026.
Why Join Us?
- Work on cutting-edge Generative AI infrastructure.
- Shape the roadmap for the next generation of autonomous systems.
- Competitive compensation and equity packages.
- Flexible, remote-first culture with a San Francisco HQ.
Responsibilities
- Architect Multi-Agent Systems: Design and build scalable autonomous agent frameworks capable of complex task execution and tool usage.
- Optimize LLM Pipelines: Implement advanced Retrieval-Augmented Generation (RAG) strategies to maximize accuracy and reduce hallucinations.
- Model Fine-Tuning: Lead the fine-tuning and alignment of Large Language Models (LLMs) on proprietary datasets using methods like LoRA and P-Tuning.
- System Evaluation: Develop rigorous evaluation benchmarks and automated testing suites to measure agent performance against 2026 standards.
- Cross-Functional Leadership: Collaborate with product managers and data scientists to translate complex AI concepts into deployable software.
Qualifications
- Education: Master’s or PhD in Computer Science, AI, or a related technical field.
- Experience: 5+ years of professional software engineering experience with at least 3 years focused on Machine Learning or AI.
- Technical Skills: Deep proficiency in Python, PyTorch, or TensorFlow. Experience with LangChain, LlamaIndex, or similar agent frameworks.
- Databases: Strong experience with vector databases (e.g., Pinecone, Milvus, Weaviate).
- Cloud Infrastructure: Experience deploying models on AWS, GCP, or Azure using Docker and Kubernetes.