Job Description
Are you ready to define the landscape of Artificial Intelligence in 2026?
Nexus Horizon Labs is seeking a visionary Agentic AI Engineer to architect the next generation of autonomous, self-improving systems. In this pivotal role, you won't just write code; you will build the cognitive infrastructure that powers the future of enterprise automation and human-AI collaboration.
We are pioneers in the field of Autonomous Agents and Generative AI. As a key member of our R&D team, you will leverage cutting-edge Large Language Models (LLMs) to create intelligent agents capable of complex reasoning, multi-step planning, and real-world execution.
Why Join Us?
- Work on projects that shape the industry standards for 2026 and beyond.
- Competitive USD salary and performance-based equity.
- Access to state-of-the-art compute resources and proprietary datasets.
- Flexible remote-first culture with an office in the heart of San Francisco.
Ready to build the future? Apply today.
Responsibilities
- Design and deploy autonomous AI agents capable of complex decision-making and multi-step task execution.
- Optimize large language model (LLM) inference pipelines to ensure real-time latency and cost-efficiency.
- Develop and implement advanced prompt engineering strategies and fine-tuning pipelines (RLHF, LoRA).
- Integrate multimodal data streams (text, vision, audio) to enhance agent perception capabilities.
- Build robust evaluation frameworks to measure agent reliability, safety, and hallucination rates.
- Collaborate with product managers and designers to translate futuristic concepts into scalable, production-ready solutions.
- Stay at the forefront of AI research, adapting novel architectures (e.g., MoE, RAG, Agents) into our core platform.
Qualifications
- Master’s degree or PhD in Computer Science, Machine Learning, or a related technical field.
- 5+ years of professional experience in software engineering with a focus on AI/ML.
- Deep expertise in Python and PyTorch/TensorFlow.
- Proven track record of building, fine-tuning, or deploying LLMs (e.g., GPT-4, Llama 3, Claude).
- Strong understanding of distributed systems, cloud architecture (AWS/GCP), and MLOps practices.
- Experience with RAG (Retrieval-Augmented Generation) and vector databases.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, ambiguous environment.