Job Description
We are not just building software for today; we are architecting the infrastructure for 2026 and beyond. As the pace of artificial intelligence accelerates, we seek a visionary Lead AI Architect to define the next generation of intelligent systems.
In this pivotal role, you will bridge the gap between theoretical AI research and production-scale engineering. You will lead a high-impact team focused on developing autonomous agents, next-generation Large Language Models (LLMs), and spatial computing interfaces. If you thrive on solving complex problems at the intersection of neural networks, distributed systems, and human-computer interaction, we want to hear from you.
Why join us?
- Work on the bleeding edge of Generative AI 2.0.
- Competitive equity package and performance bonuses.
- Flexible remote-first culture with premium benefits.
Responsibilities
- Architect the 2026 Stack: Design and implement scalable, fault-tolerant systems for LLM inference and training pipelines.
- Pioneer Agentic Workflows: Lead the development of autonomous AI agents capable of complex reasoning and multi-step task execution.
- R&D Leadership: Define the technical roadmap for emerging technologies, including Quantum-resistant algorithms and Edge AI deployment.
- Model Optimization: Drive efficiency improvements for model serving, reducing latency and resource consumption by 40%.
- Cross-Functional Collaboration: Partner with product and design teams to translate abstract AI capabilities into intuitive user experiences.
- Code Review & Mentorship: Establish rigorous engineering standards and mentor a team of top-tier data scientists and engineers.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 3 years leading AI/ML architecture in a high-growth environment.
- Technical Mastery: Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- LLM Expertise: Proven experience with transformer architectures, RAG (Retrieval-Augmented Generation), and fine-tuning large models.
- System Design: Strong background in distributed systems, Kubernetes, and cloud-native architecture (AWS/GCP/Azure).
- Future-Forward Mindset: Demonstrated ability to anticipate industry trends and adapt technology stacks proactively.