Job Description
We are on a mission to redefine the digital frontier by 2026. We are seeking a visionary Lead AI Architect to spearhead our next-generation autonomous systems and long-term technological strategy. In this pivotal role, you will bridge the gap between theoretical AI research and scalable, real-world engineering solutions.
As we prepare for the 2026 era of generative intelligence, we need a leader who can architect robust systems that are secure, efficient, and ethically sound. You will work closely with cross-functional teams to deploy cutting-edge LLMs and AI agents that drive our core product innovation.
Why Join Us?
- Shape the future of technology with a team of world-class engineers and researchers.
- Competitive compensation package and equity options.
- Flexible work environment with a focus on work-life balance.
- Access to the latest hardware and cloud infrastructure for experimentation.
Responsibilities
- Strategic Roadmap: Define the technical vision and architectural strategy for AI systems leading up to and beyond 2026, focusing on autonomy and scalability.
- System Design: Design and oversee the implementation of complex distributed systems, microservices, and machine learning pipelines.
- Model Optimization: Lead initiatives to optimize large language models (LLMs) for inference speed and cost-efficiency in production environments.
- Team Leadership: Mentor senior engineers and data scientists, fostering a culture of innovation, code quality, and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and stakeholders to translate business requirements into technical specifications.
- Compliance & Ethics: Ensure all AI deployments adhere to strict data privacy regulations and ethical AI guidelines.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Machine Learning, or a related technical field.
- Experience: Minimum of 8+ years of experience in software engineering, with at least 4 years in AI/ML architecture.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or similar deep learning frameworks.
- System Architecture: Deep understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Leadership: Proven track record of leading high-performing engineering teams and delivering complex projects on time.
- Problem Solving: Ability to tackle ambiguous problems and drive technical decisions in a fast-paced startup environment.