Job Description
We are Nexus Future Labs, a pioneer in next-generation artificial intelligence. We are building the infrastructure for the 2026 roadmap, focusing on achieving Artificial General Intelligence (AGI) and autonomous agent systems. We are seeking a visionary Senior AI Architect to lead our technical strategy and build the core models that will define the future of human-computer interaction.
In this role, you won't just implement existing solutions; you will define the architectural patterns for the year 2026. You will work with a world-class team of researchers and engineers to push the boundaries of Large Language Models (LLMs), multimodal systems, and ethical AI deployment.
Why Join Us?
- Impact: Your work will directly shape the AI landscape for the next decade.
- Equity: Competitive equity package tied to our 2026 success milestones.
- Flexibility: Fully remote-first culture with a focus on output over hours.
Responsibilities
- Architect 2026 Tech Stack: Design and implement scalable, distributed AI infrastructure capable of supporting next-gen model training and inference.
- Model Development: Spearhead the development and fine-tuning of proprietary LLMs using PyTorch and TensorFlow, specifically tailored for enterprise integration.
- RAG & Agents: Lead the implementation of Retrieval-Augmented Generation (RAG) pipelines and autonomous AI agent frameworks to enhance system autonomy.
- Performance Optimization: Drive initiatives to reduce inference latency and optimize model resource utilization across cloud environments.
- Research Integration: Translate cutting-edge academic research into production-ready code and architectural patterns.
- Technical Mentorship: Mentor a team of mid-level and senior engineers, fostering a culture of technical excellence and innovation.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- Experience: 7+ years of professional software engineering experience, with at least 3 years specifically focused on Deep Learning and NLP.
- Core Skills: Expert proficiency in Python, C++, and CUDA.
- Frameworks: Deep experience with PyTorch, TensorFlow, or JAX.
- LLM Expertise: Strong understanding of LLM architecture, fine-tuning techniques (LoRA, QLoRA), and prompt engineering.
- Infrastructure: Experience with vector databases (Pinecone, Milvus) and cloud platforms (AWS, GCP, or Azure).
- Strategic Mindset: Ability to think long-term and translate high-level 2026 strategic goals into concrete technical roadmaps.