Job Description
We are on the precipice of a technological singularity. As we approach 2026, the convergence of Generative AI, Autonomous Agents, and Quantum-ready architectures demands a new breed of engineering leadership.
The Opportunity:
Quantum Horizon is seeking a visionary Senior AI & Future Systems Architect to lead our infrastructure evolution. You won't just be maintaining systems; you will be architecting the foundational layers for the next era of computing. This is a high-impact role for a builder who thrives in ambiguity and is obsessed with scalability.
Key Objectives:
- Design and implement resilient, AI-native cloud infrastructure designed to scale for 2026 and beyond.
- Lead the integration of Agentic AI workflows into core enterprise systems.
- Define the technical roadmap for transitioning legacy monoliths to distributed, event-driven microservices.
- Collaborate with cross-functional teams to define the future of user experience through predictive computing.
- Establish best practices for security, ethics, and compliance in autonomous AI deployment.
Why Join Us?
We offer competitive compensation, equity options, and the chance to define the technological landscape of the future. If you are ready to build the systems that will power the next decade, we want to hear from you.
Responsibilities
- Architect scalable, fault-tolerant systems utilizing Kubernetes, Docker, and serverless technologies.
- Develop and optimize machine learning pipelines for real-time inference.
- Guide the engineering team in adopting next-gen programming paradigms and tools.
- Conduct deep-dive technical reviews and code architecture assessments.
- Drive innovation in edge computing and IoT infrastructure integration.
- Ensure high availability and performance under peak load conditions.
Qualifications
- 10+ years of experience in Software Engineering and System Architecture.
- 5+ years of experience specifically in AI/ML infrastructure or Generative AI deployment.
- Expert proficiency in Python, Go, or Rust.
- Deep knowledge of cloud platforms (AWS, GCP, or Azure) with a focus on AI services.
- Proven track record of leading high-performance engineering teams.
- Experience with large language models (LLMs), vector databases, and RAG architectures.
- Strong understanding of distributed systems principles and data privacy regulations.