Job Description
We are Nexus Horizon Labs, a pioneering research and development firm at the forefront of the 2026 AI revolution. We are building the next generation of autonomous agents that redefine human-computer interaction. We are seeking a visionary Senior Agentic AI Engineer to architect self-healing, multi-agent systems that can operate independently in complex, unstructured environments.
In this role, you won't just be coding models; you will be designing the nervous system of tomorrow's enterprise. You will bridge the gap between advanced Large Language Models (LLMs) and practical, high-stakes autonomous workflows.
Why Join Us?
- Work on cutting-edge Agentic AI infrastructure that is shaping the 2026 landscape.
- Competitive compensation and equity package.
- Flexible remote-first culture with a hub in the heart of San Francisco.
- Access to proprietary compute resources and next-gen neural hardware.
If you are passionate about the future of AI autonomy and want to build systems that learn and adapt in real-time, we want to hear from you.
Responsibilities
- Design and implement scalable Agentic AI architectures capable of complex task decomposition and execution.
- Develop and fine-tune Self-Healing Agents that can detect errors, self-correct, and recover from failure states autonomously.
- Integrate RAG (Retrieval-Augmented Generation) pipelines with real-time data streams for 2026-ready decision support systems.
- Optimize prompt engineering strategies and chain-of-thought reasoning for high-stakes enterprise applications.
- Collaborate with cross-functional teams to deploy autonomous agents into production environments using containerized orchestration (Kubernetes/Docker).
- Research and prototype novel techniques in Neural Symbolic AI to enhance agent reliability and safety.
Qualifications
- Master’s degree or Ph.D. in Computer Science, AI, or a related field (or equivalent practical experience).
- 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Strong proficiency in Python and frameworks such as PyTorch or TensorFlow.
- Hands-on experience with LangChain, LlamaIndex, or similar agent orchestration frameworks.
- Deep understanding of Vector Databases (Pinecone, Milvus) and embedding models.
- Experience deploying AI models in production with a focus on latency, throughput, and cost optimization.
- Excellent communication skills and the ability to translate technical concepts for diverse stakeholders.