Job Description
We are looking for a visionary Senior AI Architect to lead our research into next-generation artificial intelligence systems. As we accelerate towards 2026, our mission is to redefine human-machine interaction through autonomous agents and advanced multimodal models. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and generative AI, we want to hear from you.
You will be responsible for the architectural design, implementation, and scaling of our core AI infrastructure. You will work in a high-performance environment where innovation is not just encouraged but required. Join us in building the intelligent systems of tomorrow.
You will be responsible for the architectural design, implementation, and scaling of our core AI infrastructure. You will work in a high-performance environment where innovation is not just encouraged but required. Join us in building the intelligent systems of tomorrow.
Responsibilities
- Architect and deploy scalable, high-performance AI models and autonomous agent systems.
- Lead the research and implementation of next-generation Generative AI and Large Language Model (LLM) applications.
- Optimize model inference pipelines to ensure real-time performance and low latency.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Collaborate with cross-functional product teams to translate complex technical requirements into robust AI solutions.
- Stay ahead of industry trends, including Multimodal AI and Agentic workflows, to integrate cutting-edge advancements.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- 5+ years of professional experience in Machine Learning, Deep Learning, or AI Engineering.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Deep understanding of Natural Language Processing (NLP) and Large Language Model architectures (e.g., GPT, LLaMA).
- Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven track record of delivering complex AI products from concept to production.