Job Description
We are on the bleeding edge of technological evolution, and we are looking for a visionary AI Architect (2026 Vision) to join our elite engineering team in San Francisco. As we prepare for the next decade of computing, we need a leader who can bridge the gap between theoretical AI models and scalable, real-world infrastructure.
In this role, you won't just maintain systems; you will architect the foundation for the next generation of artificial intelligence. You will work on cutting-edge projects involving Generative AI, Large Language Models (LLMs), and autonomous agents designed to redefine human-computer interaction.
Why Join Us?
• Future-Ready Tech Stack: Work with the latest frameworks and hardware accelerators.
• Impactful Work: Your code will directly influence the trajectory of AI development globally.
• Competitive Compensation: Top-tier salary and equity packages for top-tier talent.
The Role
We are seeking a seasoned engineer to lead our AI infrastructure initiatives. You will be responsible for the end-to-end lifecycle of our AI products, from prototype to production deployment at scale.
Responsibilities
- Design and implement scalable machine learning pipelines and neural network architectures optimized for high-volume inference.
- Lead the research and integration of emerging AI technologies, specifically focusing on LLM optimization and agent-based systems.
- Collaborate with cross-functional teams of data scientists, backend engineers, and product managers to define technical requirements.
- Ensure system reliability, security, and performance of all AI workloads in cloud environments.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
- Optimize model training times and reduce operational costs through efficient hardware utilization.
- Define architectural best practices for the AI department and contribute to technical documentation.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture.
- Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Strong understanding of distributed systems, containerization (Docker/Kubernetes), and cloud platforms (AWS, GCP, or Azure).
- Experience deploying and scaling large-scale LLMs and generative models.
- Proven track record of leading engineering teams and managing complex technical projects.
- Excellent problem-solving skills and ability to thrive in a fast-paced, agile environment.
- Master’s degree or PhD in Computer Science, Machine Learning, or a related field is preferred.