Job Description
Are you ready to architect the future of Artificial Intelligence?
QuantumLeap Systems is seeking a visionary Senior AI Architect to lead the design and implementation of next-generation intelligent systems. In this pivotal role, you will shape the technological roadmap for 2026 and beyond, bridging the gap between cutting-edge research and scalable production infrastructure.
We are not just building AI; we are defining the ethical and technical standards for the industry. If you possess a deep understanding of Large Language Models (LLMs), Agentic workflows, and distributed cloud architectures, we want to hear from you.
Why Join Us?
- Impactful Work: Build systems that will power the digital economy of 2026.
- Top-Tier Compensation: Competitive salary, equity package, and comprehensive benefits.
- Flexible Environment: Hybrid work model based in the heart of San Francisco.
- Continuous Learning: Access to the latest GPUs, research papers, and training resources.
What You Will Do:
You will act as a technical leader, architecting end-to-end AI solutions that drive business value and innovation. Your expertise will guide engineering teams in deploying robust, secure, and efficient machine learning models.
Responsibilities
- Architect Design: Design and oversee the deployment of scalable AI infrastructure, focusing on LLMs, computer vision, and predictive analytics.
- Technical Leadership: Provide architectural guidance and code reviews for a high-performance engineering team, ensuring best practices in security and scalability.
- Model Optimization: Lead initiatives to optimize model inference speed and reduce latency in production environments.
- Strategic Roadmapping: Collaborate with product leaders to define the technical vision for future product iterations.
- Integration: Seamlessly integrate AI models into existing legacy systems and new microservices architectures.
- Stakeholder Communication: Translate complex technical concepts into actionable insights for non-technical stakeholders and investors.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field (PhD preferred).
- Experience: 7+ years of software engineering experience with 3+ years specifically in AI/ML architecture and MLOps.
- Core Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of distributed systems (Kubernetes, Docker).
- Cloud Expertise: Extensive experience designing solutions on AWS, Azure, or GCP.
- LLM Knowledge: Hands-on experience with fine-tuning, RAG (Retrieval-Augmented Generation), and prompt engineering.
- Problem Solving: Proven track record of solving complex, ambiguous technical challenges in a fast-paced startup environment.