Job Description
We are building the infrastructure for the year 2026. At Nexus Future Systems, we don't just predict trends; we engineer them. We are seeking a visionary Senior AI Architect to lead our roadmap in Generative AI, Large Language Models (LLMs), and autonomous systems.
In this pivotal role, you will bridge the gap between theoretical AI breakthroughs and production-ready systems. You will define the architectural standards for our next-generation platforms, ensuring scalability, security, and ethical compliance. If you are passionate about shaping the future of technology and want to be at the forefront of the AI revolution, we want to hear from you.
Why Join Us?
- Future-Forward Impact: Work on projects that will define the technological landscape of 2026 and beyond.
- Top-Tier Talent: Collaborate with world-class engineers and researchers in a cutting-edge environment.
- Competitive Compensation: Comprehensive benefits package including equity, health, and wellness programs.
Responsibilities
- Architect Scalable Solutions: Design and implement robust, scalable AI architectures for large-scale enterprise applications, focusing on high-performance inference and low-latency processing.
- GenAI Leadership: Spearhead the integration and optimization of Large Language Models and Generative Adversarial Networks (GANs) into core product lines.
- Roadmap Strategy: Define technical roadmaps for AI capabilities, forecasting trends up to 2026 and allocating resources for R&D.
- Ethical AI Governance: Establish frameworks for AI safety, bias mitigation, and transparency to ensure responsible deployment of autonomous systems.
- System Optimization: Continuously monitor, evaluate, and improve model accuracy and efficiency, reducing computational costs while maximizing performance.
- Talent Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence within the AI team.
Qualifications
- Education: MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically focused on AI/ML systems architecture.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Proven experience deploying models in cloud environments (AWS, GCP, or Azure).
- GenAI Knowledge: Hands-on experience with transformer architectures, RAG (Retrieval-Augmented Generation), and fine-tuning LLMs.
- System Design: Strong understanding of distributed systems, microservices, and containerization (Docker, Kubernetes).
- Soft Skills: Excellent communication skills with the ability to translate complex technical concepts for diverse stakeholders.