Job Description
We are looking for a visionary Lead AI Architect to spearhead the development of our next-generation autonomous systems. As we accelerate towards the 2026 technological paradigm shift, we need a technical leader to design the infrastructure that will define the future of human-machine interaction. This is not just a job; it is a mission to build the intelligent backbone of the digital world.
In this role, you will bridge the gap between theoretical machine learning research and production-grade software engineering. You will lead a team of elite engineers in deploying state-of-the-art Generative AI models, ensuring they are scalable, secure, and aligned with the rapid pace of innovation expected in the 2026 landscape.
Responsibilities
- Architect and lead the end-to-end development of scalable Generative AI and Large Language Model (LLM) infrastructure.
- Define the technical roadmap for 2026, identifying emerging technologies (e.g., Neuromorphic Computing, AGI safety) and integrating them into our core stack.
- Design high-availability, low-latency inference systems capable of processing billions of tokens per second.
- Establish rigorous standards for AI ethics, data privacy, and algorithmic fairness to ensure responsible innovation.
- Mentor and cultivate a high-performance engineering culture focused on rapid prototyping and production excellence.
- Collaborate with product leaders to translate complex AI capabilities into intuitive user experiences.
Qualifications
- Master’s or PhD degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 10+ years of software engineering experience, with at least 5 years specifically in AI/ML architecture and system design.
- Deep expertise in Python, PyTorch, TensorFlow, and modern LLM frameworks (e.g., Hugging Face, LangChain).
- Proven track record of deploying production-ready AI models at scale in cloud environments (AWS, GCP, or Azure).
- Strong understanding of Transformer architectures, Reinforcement Learning from Human Feedback (RLHF), and RAG (Retrieval-Augmented Generation).
- Exceptional leadership skills with the ability to drive technical vision across cross-functional teams.