Job Description
Shape the Future of Intelligence.
At Nexus Future Systems, we are building the infrastructure for the Agentic AI era. As we look toward 2026, our mission is to redefine human-machine interaction through autonomous, self-improving systems. We are seeking a visionary 2026 Horizon AI Architect to lead our research and engineering efforts in building the next generation of autonomous agents capable of complex, multi-step reasoning and execution.
You will be at the forefront of the tech revolution, working alongside world-class engineers and researchers to deploy scalable, secure, and ethical AI models that power the digital economy of tomorrow.
Why Join Us?
- Work on cutting-edge Agentic AI technology expected to dominate 2026.
- Competitive compensation package and equity options.
- Flexible remote-first culture with hubs in Austin and San Francisco.
- Access to top-tier hardware and cloud infrastructure.
Ready to architect the future? Apply today.
Responsibilities
- Design Core Architectures: Architect and implement scalable, distributed AI agent systems capable of autonomous decision-making and complex task execution.
- Pioneer Agentic Models: Lead the development and fine-tuning of Large Language Models (LLMs) specifically optimized for tool use, memory retention, and long-horizon planning.
- Optimize Performance: Engineer efficient inference pipelines and training workflows to reduce latency and costs while maximizing model accuracy.
- Risk & Safety: Implement robust guardrails and safety protocols to ensure AI agents operate ethically and securely within enterprise environments.
- Cross-Functional Leadership: Collaborate with product managers, data scientists, and security experts to translate business requirements into technical AI solutions.
- Research & Innovation: Stay ahead of the curve on emerging trends in AI safety, reinforcement learning, and multimodal systems.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- Experience: 5+ years of professional experience in Machine Learning, AI Engineering, or Software Development, with a strong focus on NLP or Deep Learning.
- Technical Skills: Deep proficiency in Python, PyTorch, or TensorFlow. Experience with model deployment (Kubernetes, Docker) and MLOps pipelines is required.
- Model Expertise: Proven track record of working with or deploying state-of-the-art LLMs (e.g., GPT-4, Llama 3, Claude) and fine-tuning techniques (LoRA, PEFT).
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems and think critically about system design at scale.
- Communication: Excellent verbal and written communication skills, capable of explaining technical concepts to diverse stakeholders.