Job Description
Shape the Future of Intelligence with Aether Dynamics.
We are on the bleeding edge of technological evolution. As we approach the transformative era of 2026, we are seeking a visionary Senior AI Systems Architect to lead the architectural design and implementation of our next-generation Generative AI platforms. You won't just be writing code; you will be building the cognitive infrastructure that powers the digital world of tomorrow.
In this role, you will bridge the gap between theoretical AI research and production-grade engineering, ensuring our systems are scalable, secure, and ethically sound. If you are passionate about pushing the boundaries of Large Language Models (LLMs), optimizing inference pipelines, and leading a team of elite engineers, this is your opportunity to define the standard.
Why Join Us?
- Work on cutting-edge projects that redefine human-computer interaction.
- Competitive compensation package with equity options.
- Flexible remote-first culture with premium San Francisco office access.
- Access to state-of-the-art compute resources and research tools.
Responsibilities
- Architectural Leadership: Design and deploy scalable, fault-tolerant AI infrastructure capable of handling petabyte-scale data and real-time inference demands.
- Model Optimization: Lead the research and implementation of techniques to improve model latency, throughput, and cost-efficiency for production deployment.
- System Integration: Integrate AI models with enterprise-grade cloud platforms (AWS, GCP, Azure) and ensure seamless data flow across complex microservices architectures.
- Team Mentorship: Guide a high-performing team of ML engineers and data scientists, conducting code reviews, technical architecture planning, and fostering a culture of innovation.
- Compliance & Safety: Establish best practices for AI safety, bias mitigation, and data privacy in compliance with global regulations (GDPR, CCPA).
- Strategic Roadmap: Collaborate with product leadership to define the technical roadmap for AI feature development over the next 2-3 years.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, Applied Mathematics, or a related field from a top-tier institution.
- Experience: 8+ years of experience in software engineering, with at least 5 years specifically focused on AI/ML systems architecture.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Docker).
- Generative AI: Proven experience designing and deploying LLMs or generative models, including fine-tuning and RAG (Retrieval-Augmented Generation) implementations.
- Cloud Mastery: Strong understanding of cloud-native architecture and MLOps practices (MLflow, SageMaker, Vertex AI).
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams.