Job Description
Are you ready to define the technological landscape of 2026? Nexus Horizon Labs is seeking a visionary Lead Agentic AI Architect to pioneer the next generation of autonomous intelligent systems. We are building the brains behind the future, and we need a technical leader who understands the intricacies of Large Language Models (LLMs), multi-agent orchestration, and next-gen automation.
In this pivotal role, you will not just write code; you will architect the frameworks that will power enterprise solutions for the decade to come. You will bridge the gap between theoretical AI research and production-grade infrastructure, ensuring our systems are scalable, secure, and ethically sound.
Why Join Us?
- Work on cutting-edge Agentic AI projects that are redefining industry standards.
- Competitive compensation package with equity options.
- Flexible remote-first policy with access to premium San Francisco offices.
- Opportunity to mentor top-tier talent in a culture of innovation.
Responsibilities
- Architect Next-Gen AI Systems: Design and implement scalable, distributed neural architectures capable of autonomous decision-making for 2026 applications.
- Model Optimization: Lead initiatives to optimize Large Language Models (LLMs) for low-latency, high-throughput inference in edge and cloud environments.
- Agentic Workflow Design: Create robust orchestration layers that enable AI agents to collaborate effectively, plan multi-step tasks, and execute complex workflows autonomously.
- Technical Leadership: Mentor a team of Senior ML Engineers and Data Scientists, fostering a culture of continuous learning and technical excellence.
- R&D Integration: Translate cutting-edge research papers into deployable production code, staying ahead of the curve on Transformer architectures and reinforcement learning.
- Security & Compliance: Implement rigorous security protocols to ensure data privacy and mitigate adversarial attacks on AI models.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field (or equivalent practical experience).
- Experience: 8+ years of software engineering experience, with at least 4 years specializing in Machine Learning and Deep Learning infrastructure.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX; strong understanding of distributed systems (Kubernetes, Docker) and cloud platforms (AWS/GCP/Azure).
- Agentic AI: Demonstrated experience designing and deploying multi-agent systems, LLM fine-tuning, and RAG (Retrieval-Augmented Generation) pipelines.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts for non-technical stakeholders.
- Problem Solving: Proven track record of solving ambiguous problems and driving technical roadmaps from conception to delivery.