Job Description
Are you ready to architect the digital backbone of tomorrow? Vertex Horizon is seeking a visionary Future-Ready AI Systems Architect to lead our 2026 infrastructure roadmap.
As we transition into the next era of computing, we are looking for a technical leader who doesn't just follow trends but defines them. You will be responsible for designing scalable, resilient, and intelligent systems capable of handling the demands of the post-2026 landscape. This is a high-impact role where your code will shape the future of enterprise AI.
Why Join Us?
We offer a competitive compensation package, stock options, and the opportunity to work with world-class engineers solving complex problems at the intersection of AI and distributed systems.
Responsibilities
- Architect Future-Proof Systems: Design and implement scalable microservices and distributed architectures designed to withstand the demands of the 2026 technology era.
- AI Integration: Lead the integration of next-gen GenAI models into our core infrastructure, optimizing for latency and inference speed.
- Cloud Strategy: Define and execute cloud-native strategies across AWS and Azure, ensuring high availability and cost-efficiency.
- Performance Engineering: Conduct deep-dive performance analysis and optimization to ensure our systems scale seamlessly with user growth.
- Technical Leadership: Mentor junior engineers and conduct code reviews, fostering a culture of excellence and innovation.
- Security & Compliance: Implement robust security protocols to protect sensitive data and ensure regulatory compliance.
Qualifications
- Education: Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s degree is preferred.
- Experience: 8+ years of professional software engineering experience with at least 3 years in a lead or architect role.
- Programming: Proficiency in Python, Go, or Rust, with deep knowledge of distributed systems.
- Cloud Mastery: Strong experience with Kubernetes, Docker, and major cloud providers (AWS/Azure/GCP).
- AI/ML Knowledge: Hands-on experience with MLOps, TensorFlow/PyTorch, and model deployment strategies.
- Problem Solving: Demonstrated ability to solve complex technical challenges and make data-driven architectural decisions.