Job Description
We are seeking a visionary Senior AI Architect to lead our technical strategy for the upcoming 2026 era. As a pioneer in next-generation artificial intelligence, Veritas Future Labs is building the infrastructure that will power the digital world tomorrow. In this pivotal role, you will bridge the gap between theoretical research and scalable production systems, ensuring our AI models are robust, efficient, and ready for the demands of 2026 and beyond.
Why Join Us?
You will work in a state-of-the-art facility with top-tier researchers and engineers. We offer competitive equity packages, unlimited PTO, and a flexible remote-first culture. This is not just a job; it is an opportunity to define the future of AI.
Responsibilities
- Strategic Roadmap Planning: Define and execute the technical roadmap for 2026, aligning AI capabilities with long-term business objectives.
- System Architecture: Design scalable, fault-tolerant architectures for Large Language Models (LLMs) and generative AI agents.
- Performance Optimization: Lead initiatives to reduce inference latency and improve model accuracy on edge devices and cloud infrastructure.
- Team Leadership: Mentor a team of machine learning engineers and data scientists, fostering a culture of innovation and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and data scientists to translate business requirements into technical specifications.
- Security & Compliance: Implement rigorous security protocols and ensure AI systems adhere to industry regulations and ethical standards.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field (or equivalent industry experience).
- Experience: 8+ years of experience in software engineering and machine learning, with at least 3 years in a senior architectural role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed systems (Kubernetes, Docker).
- AI Expertise: Deep understanding of transformer models, reinforcement learning, and MLOps pipelines.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems with innovative technical solutions.
- Communication: Exceptional verbal and written communication skills, capable of presenting technical concepts to non-technical stakeholders.