Job Description
We are seeking a visionary Lead AI Architect to spearhead the technological roadmap for the year 2026. In this pivotal role, you will define the architectural framework for next-generation artificial intelligence systems, ensuring scalability, security, and future-proofing our core infrastructure. You will work closely with cross-functional teams to integrate cutting-edge machine learning models into our enterprise solutions, driving innovation that shapes the future of our industry.
Why Join Apex Horizon Systems?
- Future-First Technology: Work on greenfield projects designed for the 2026 landscape.
- Competitive Compensation: $180k - $260k base salary + equity package.
- Flexible Work Environment: Hybrid model based in our San Francisco headquarters.
- Professional Growth: Access to top-tier training and industry conferences.
Responsibilities
- Define and execute the long-term architectural strategy for AI and machine learning infrastructure leading up to 2026.
- Design scalable, distributed systems capable of handling high-throughput data processing and real-time inference.
- Lead the research and integration of emerging AI technologies, including Large Language Models (LLMs) and generative AI.
- Mentor senior engineering teams and conduct code reviews to ensure best practices in security and performance.
- Collaborate with product managers to translate business requirements into technical roadmaps.
- Ensure system reliability, fault tolerance, and data governance across all AI initiatives.
- Present architectural proposals to executive leadership and stakeholders.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (PhD preferred).
- 10+ years of experience in software architecture, with at least 5 years in AI/ML engineering.
- Deep proficiency in Python, TensorFlow, PyTorch, or similar ML frameworks.
- Proven experience designing microservices and cloud-native architectures (AWS, GCP, or Azure).
- Strong understanding of distributed systems, data structures, and algorithmic complexity.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience with MLOps and model deployment pipelines.