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Information Technology 🏢 Full Time ⭐️ Verified

Future-Ready AI Architect

Nexus Horizon Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Join the Architects of 2026

Nexus Horizon Systems is pioneering the digital infrastructure of tomorrow. We are seeking a visionary Future-Ready AI Architect to lead our strategic transformation initiatives. In this role, you will define the technical blueprint for our AI-driven ecosystems, ensuring our solutions are scalable, sustainable, and future-proof for the next decade.

We are looking for a thought leader who doesn't just adapt to change but drives it. If you have a passion for integrating cutting-edge generative AI with robust backend systems, this is your opportunity to shape the landscape of 2026 and beyond.

Responsibilities

  • Design Future-Proof Architectures: Lead the end-to-end design of scalable, distributed systems capable of supporting next-generation AI workloads and autonomous agents.
  • Strategic Roadmapping: Develop and communicate long-term technical strategies aligned with the company's 2026 vision and market demands.
  • Cloud & Edge Integration: Oversee the deployment and optimization of cloud-native infrastructure (AWS/Azure) and edge computing solutions for low-latency AI processing.
  • Security & Compliance: Implement rigorous zero-trust security protocols and ensure all architectural designs adhere to global data privacy regulations.
  • Team Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation, code quality, and continuous learning.
  • Performance Optimization: Analyze system bottlenecks and implement high-performance computing solutions to handle massive data throughput.

Qualifications

  • Experience: 8+ years of experience in software architecture, with at least 3 years specifically focused on AI/ML infrastructure or Generative AI applications.
  • Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
  • Technical Proficiency: Deep expertise in Python, Java, or Go; strong knowledge of distributed systems, microservices, and containerization (Docker/Kubernetes).
  • AI Knowledge: Hands-on experience with LLMs, RAG (Retrieval-Augmented Generation), and MLOps pipelines.
  • Leadership: Proven track record of leading cross-functional teams and delivering complex projects on time.
  • Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts into business value.

Required Skills

Artificial Intelligence System Architecture Machine Learning Python Kubernetes AWS Cloud Computing Leadership Generative AI MLOps

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