Job Description
We are building the infrastructure for the next decade of intelligence. At Nexus Future Labs, we are not just predicting the future; we are architecting it. As a Senior AI Architect, you will lead the design and deployment of next-generation Generative AI systems, specifically focused on LLM orchestration and Agentic workflows set to dominate the 2026 tech landscape.
In this high-impact role, you will bridge the gap between cutting-edge research and scalable production engineering. You will work with a world-class team to build systems that are not only intelligent but also ethical, efficient, and future-proof. If you are passionate about the intersection of cognitive science and software engineering, we want to hear from you.
Why Join Us?
- Future-Forward Impact: Work on projects that define the standard for AI in 2026 and beyond.
- Top-Tier Compensation: Competitive salary and equity package.
- Flexible Culture: Remote-first with a hub in the heart of San Francisco.
Responsibilities
- Architect System Design: Design and implement scalable, distributed AI systems capable of handling petabyte-scale data processing and real-time inference.
- LLM Optimization: Lead the optimization of Large Language Models (GPT-4, Claude, Llama) for specific industry verticals, focusing on speed, accuracy, and cost-efficiency.
- Agentic AI Development: Build autonomous AI agents that can perform complex, multi-step tasks with minimal human intervention.
- RAG Strategy: Develop and refine Retrieval-Augmented Generation pipelines to ensure contextually accurate and up-to-date AI responses.
- Research Integration: Evaluate and integrate emerging research papers and open-source models into our production stack.
- Code Review & Mentorship: Mentor junior engineers and data scientists, conducting rigorous code reviews to maintain high engineering standards.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related field (or equivalent industry experience).
- Experience: 5+ years of experience in software engineering, with at least 3 years focused on AI/ML architecture.
- Technical Proficiency: Deep understanding of Transformer architectures, Natural Language Processing (NLP), and Deep Learning frameworks (PyTorch, TensorFlow, JAX).
- Programming: Expert-level proficiency in Python and C++.
- Cloud Mastery: Experience deploying models on AWS, GCP, or Azure using containerization (Docker/Kubernetes).
- Soft Skills: Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders.