Job Description
Are you ready to define the trajectory of Artificial Intelligence in 2026? Nexus Future Systems is at the forefront of next-gen technology, and we are seeking a visionary Senior AI Architect to lead our research and implementation teams. This is not just a job; it is a strategic role where you will shape the autonomous systems, Generative AI frameworks, and ethical AI protocols that will define the industry standard for the coming decade.
In this role, you will bridge the gap between theoretical AI advancements and scalable, production-ready engineering solutions. You will work in a high-performance environment focused on predictive modeling, large-scale language model optimization, and the integration of quantum-inspired algorithms into our core infrastructure.
Why Join Us?
- Work on the bleeding edge of technology with a team of world-class engineers.
- Competitive equity package and performance bonuses aligned with company milestones.
- Flexible remote-first policy with premium office amenities in Austin.
- Access to the latest hardware for rapid prototyping and training.
If you possess a deep understanding of machine learning lifecycles and a passion for solving complex, high-stakes problems, we want to hear from you.
Responsibilities
- Architectural Vision: Design and oversee the implementation of robust AI architectures that support autonomous decision-making systems for the 2026 product roadmap.
- Model Optimization: Lead the optimization of Large Language Models (LLMs) and multimodal AI systems for speed, accuracy, and energy efficiency.
- Research & Prototyping: Conduct rigorous research into emerging AI paradigms, including federated learning and reinforcement learning agents.
- Technical Leadership: Mentor junior architects and data scientists, establishing coding standards and best practices for the AI team.
- Ethical AI Governance: Define and enforce frameworks for AI safety, bias mitigation, and transparency in automated systems.
- Infrastructure Scaling: Collaborate with DevOps teams to deploy scalable machine learning pipelines on cloud-native environments.
- Stakeholder Communication: Translate complex technical AI concepts into clear strategies for executive leadership and product teams.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field; PhD preferred.
- Experience: 8+ years of experience in software engineering with a focus on AI/ML, including at least 3 years in a senior architectural or leadership role.
- Technical Skills: Deep proficiency in Python, PyTorch, TensorFlow, or JAX; experience with Hugging Face Transformers and LangChain.
- System Design: Proven track record of designing scalable distributed systems and handling high-volume data processing.
- AI Expertise: Strong understanding of NLP, Computer Vision, and Generative Adversarial Networks (GANs).
- Certifications: AWS Certified Machine Learning Specialty, Google Professional Machine Learning Engineer, or equivalent.
- Soft Skills: Exceptional problem-solving abilities, strategic thinking, and the ability to thrive in a fast-paced, experimental environment.