Job Description
Are you ready to shape the technology landscape of 2026?
OmniFuture Systems is seeking a visionary Senior AI Architect to lead our strategic engineering initiatives. As we prepare for the next wave of generative intelligence and autonomous systems, we need a leader who can bridge the gap between theoretical research and scalable production infrastructure.
In this role, you will define the architectural vision for our 2026 product roadmap, ensuring our solutions are secure, scalable, and ethical. You will work closely with cross-functional teams to integrate cutting-edge AI models into our core platforms.
Why Join Us?
- Work on mission-critical AI infrastructure that impacts millions.
- Competitive compensation and equity packages.
- Flexible remote and hybrid work options.
- Access to the latest hardware and cloud technologies.
We are looking for a problem solver who is not just keeping up with trends, but defining them.
Responsibilities
- Design and implement scalable AI and machine learning architectures tailored for the 2026 technology landscape.
- Lead the technical strategy for integrating Large Language Models (LLMs) into enterprise applications.
- Establish best practices for model training, fine-tuning, and deployment using MLOps pipelines.
- Mentor and guide a team of junior data scientists and machine learning engineers.
- Ensure data privacy, security, and ethical AI compliance across all projects.
- Collaborate with product managers to translate business requirements into technical solutions.
- Conduct rigorous code reviews and architecture assessments to ensure system resilience.
Qualifications
- Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s degree preferred.
- 5+ years of experience in machine learning, deep learning, or artificial intelligence engineering.
- Proficiency in programming languages such as Python, Java, or C++.
- Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Deep understanding of neural network architectures and optimization techniques.
- Experience with MLOps tools and frameworks (MLflow, TensorFlow Extended, Kubeflow).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.