Job Description
We are seeking a visionary Senior AI Architect to lead the charge in defining the technological landscape for the year 2026 and beyond. At Nexus Future Labs, we aren't just building software; we are architecting the intelligence that will power the next generation of global enterprises.
In this pivotal role, you will design scalable, robust, and ethically sound artificial intelligence systems. You will work closely with C-suite executives and engineering leads to translate complex business requirements into cutting-edge technical roadmaps. If you are passionate about the intersection of deep learning, large language models (LLMs), and future-forward infrastructure, this is your opportunity to shape history.
Why Join Us?
- Competitive compensation package ($160k - $210k).
- Equity stake in a high-growth startup.
- Flexible remote-first culture with a hub in San Francisco.
- Access to the latest hardware for AI research.
Responsibilities
- Architectural Leadership: Design and implement high-performance AI infrastructure capable of handling petabyte-scale data and millions of concurrent requests.
- Model Strategy: Oversee the selection, training, and fine-tuning of proprietary Large Language Models (LLMs) and generative AI agents.
- Team Mentorship: Mentor a team of senior data scientists and ML engineers, fostering a culture of innovation and continuous learning.
- System Optimization: Drive initiatives to reduce latency and improve inference efficiency in real-time applications.
- Roadmap Planning: Define the technical roadmap for 2026, ensuring alignment with business goals and emerging industry trends.
- Compliance & Ethics: Establish guidelines for AI safety, fairness, and transparency in all deployed models.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 8+ years of professional experience in software engineering, with at least 5 years focused on AI/ML architecture.
- Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Apache Spark).
- AI Proficiency: Proven track record of deploying production-grade LLMs (e.g., GPT-4, Llama, Claude) and RAG pipelines.
- Leadership: Demonstrated ability to lead cross-functional teams and communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Strong analytical skills with a focus on scalable solutions and architectural trade-offs.