Job Description
We are building the operating systems for the autonomous future. Nexus Future Labs is seeking a visionary Lead AI Architect to spearhead the development of next-generation Agentic AI frameworks. In this pivotal role, you will define the architecture for autonomous systems that can plan, reason, and execute complex tasks independently by 2026.
As a key driver of our innovation engine, you will bridge the gap between cutting-edge research and production-grade engineering. You will be responsible for scaling our multimodal LLM infrastructure and ensuring our AI agents are safe, scalable, and ethically aligned.
Why Join Us?
- Future-First Technology: Work on the bleeding edge of AI evolution, specifically targeting the Agentic AI paradigm expected to dominate 2026.
- Global Impact: Your work will power intelligent automation across Fortune 500 enterprises.
- Unlimited PTO & Remote Flexibility: Enjoy a culture that values results over hours.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of scalable, fault-tolerant distributed systems for large language models and autonomous agents.
- Agentic Framework Development: Build the core logic for context-aware agents capable of multi-step reasoning and tool utilization.
- Model Optimization: Implement techniques such as quantization, pruning, and RAG (Retrieval-Augmented Generation) to optimize inference speed and cost.
- System Integration: Integrate third-party AI APIs and proprietary models into a cohesive, unified platform architecture.
- MLOps Pipeline: Establish robust CI/CD pipelines for model training, validation, and deployment, ensuring reproducibility.
- Ethical AI Compliance: Establish guidelines and technical guardrails to ensure AI outputs adhere to safety and ethical standards.
Qualifications
- Education: Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s degree or PhD is a strong plus.
- Experience: 7+ years of experience in software engineering, with at least 3 years focused on Machine Learning or AI systems architecture.
- Core Stack: Proficiency in Python, PyTorch, TensorFlow, and modern cloud infrastructure (AWS, GCP, or Azure).
- System Design: Demonstrated ability to design high-throughput, low-latency distributed systems.
- Agentic AI: Hands-on experience with LLMs, RAG, prompt engineering, and autonomous agent frameworks (LangChain, AutoGen, or similar).
- Communication: Exceptional ability to translate complex technical concepts for diverse stakeholders.