Job Description
We are looking for a visionary Senior AI Architect to lead the development of our next-generation infrastructure for the year 2026 and beyond. At OmniFuture, we are building the cognitive layer of the digital world, and we need a technical leader who can bridge the gap between theoretical artificial intelligence and scalable, production-ready engineering. If you are passionate about the future of AI, quantum-ready algorithms, and ethical machine learning, we want to hear from you.
Why Join Us?
- Work on cutting-edge projects that define the next decade of technology.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a hub in San Francisco.
The Role:
You will be responsible for the architectural design and implementation of our core AI systems. You will work closely with data scientists, software engineers, and product managers to translate complex research into robust, scalable software solutions.
Responsibilities
- Architect and design scalable, high-performance AI systems capable of handling petabyte-scale data streams.
- Define and implement the technical roadmap for our 2026 AI infrastructure, including integration of generative models and predictive analytics.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Collaborate with cross-functional teams to identify business opportunities and translate them into technical requirements.
- Ensure system reliability, security, and ethical compliance in all AI deployments.
- Stay at the forefront of industry trends, researching and evaluating emerging technologies such as Neuromorphic computing and edge AI.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or similar deep learning frameworks.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Experience designing MLOps pipelines and model lifecycle management tools.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.
- Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, or a related field is preferred.