Job Description
We are pioneering the infrastructure for the year 2026 and beyond. At Apex Future Systems, we are not just building software; we are architecting the cognitive layer of the next digital era. We are seeking a visionary Senior AI Architect to lead our Research and Development division, bridging the gap between theoretical AI breakthroughs and scalable production environments.
In this pivotal role, you will define the technical roadmap for our flagship product, ensuring our systems are resilient, intelligent, and future-proof. You will work alongside world-class engineers and data scientists to deploy cutting-edge solutions that will set the standard for the industry.
Why join us?
- Work on high-impact projects that define the future of technology.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first culture with a San Francisco hub.
Responsibilities
- Architect and lead the design of scalable, distributed AI systems capable of processing petabytes of data.
- Define the technical vision for the 2026 roadmap, identifying emerging technologies (e.g., AGI, Neuro-Symbolic AI) and integrating them into our stack.
- Oversee the research and development of proprietary machine learning models, ensuring they meet production-grade reliability standards.
- Mentor and guide a team of senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Collaborate with cross-functional stakeholders, including product managers and C-suite executives, to translate business goals into technical strategies.
- Ensure strict adherence to security, compliance, and ethical AI guidelines in all system designs.
- Conduct rigorous code reviews and performance optimization to maintain high system throughput.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years in a leadership or architect role focusing on Artificial Intelligence and Machine Learning.
- Deep expertise in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
- Proven track record of designing and deploying large-scale LLMs (Large Language Models) or Generative AI applications.
- Strong proficiency in cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field.
- Demonstrated experience in building ethical AI frameworks and managing model lifecycle (MLOps).