Job Description
Are you ready to build the infrastructure for the next generation of artificial intelligence?
We are Nexus Horizon Systems, a pioneering force in next-gen enterprise automation. As we approach the technological tipping point of 2026, we are seeking a visionary Lead AI Architect to define our technical roadmap and lead our elite engineering team in San Francisco.
In this role, you will not just implement existing solutions; you will architect the future. You will be responsible for designing scalable, secure, and high-performance AI systems that will power our clients' digital transformation. If you are passionate about the intersection of Generative AI, MLOps, and Cloud Infrastructure, we want to hear from you.
Why Join Nexus Horizon?
- Work with state-of-the-art technology and cutting-edge frameworks.
- Shape the strategic direction of AI within a rapidly growing market.
- Competitive compensation package and comprehensive benefits.
- Hybrid work model based in the heart of San Francisco.
Responsibilities
- Define and execute the long-term technical vision for AI infrastructure, specifically aligning with the roadmap leading up to 2026.
- Architect scalable machine learning pipelines and data lakes using modern cloud-native technologies.
- Lead a team of senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Collaborate with product managers to translate complex business requirements into robust technical solutions.
- Ensure system security, scalability, and performance optimization across all AI deployments.
- Stay ahead of industry trends, evaluating and integrating emerging AI technologies.
- Mentor junior developers and conduct technical code reviews to maintain high engineering standards.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- 8+ years of experience in software engineering, with at least 4 years in AI/ML architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or similar ML frameworks.
- Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Proven track record of designing end-to-end MLOps solutions.
- Experience with Large Language Models (LLMs) and prompt engineering architectures.
- Excellent communication skills, with the ability to bridge the gap between technical and non-technical stakeholders.