Job Description
Are you ready to architect the future of intelligence? Nexus Future Systems is leading the charge into the 2026 era of autonomous AI and quantum-assisted computing. We are looking for a visionary Senior AI Architect to design scalable, secure, and ethically grounded systems that redefine human-machine interaction.
In this role, you won't just be maintaining legacy models; you will be building the foundational infrastructure for the next generation of generative AI. You will collaborate with a world-class team of data scientists, engineers, and futurists to push the boundaries of what is possible.
Why join us?
- Work on cutting-edge proprietary technology.
- Competitive compensation and equity package.
- Flexible remote/hybrid work environment.
- Opportunity to shape industry standards for 2026.
Responsibilities
- Architectural Design: Design and implement scalable, fault-tolerant AI architectures for high-volume generative models and autonomous agents.
- Research & Development: Lead research initiatives to integrate emerging technologies (e.g., Neuro-symbolic AI, Quantum ML) into production pipelines.
- Performance Optimization: Oversee the optimization of model inference latency and resource utilization on cloud infrastructure (AWS/GCP).
- Ethical AI Governance: Establish and enforce strict guidelines for AI bias, transparency, and safety to ensure responsible deployment.
- Team Leadership: Mentor junior engineers and data scientists, conducting code reviews and architectural walkthroughs.
- Strategic Roadmapping: Contribute to the long-term technical strategy for the 2026 product roadmap.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related technical field (or equivalent extensive industry experience).
- Technical Expertise: Deep expertise in deep learning frameworks (PyTorch, TensorFlow, JAX) and large language model (LLM) architectures.
- Programming: Proficiency in Python, C++, and experience with CUDA programming.
- Infrastructure: Strong background in distributed systems, cloud computing, and MLOps best practices.
- Experience: 8+ years of experience in AI/ML engineering, with a proven track record of shipping production-level AI products.
- Communication: Exceptional ability to translate complex technical concepts into clear strategic value for stakeholders.