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Senior AI Systems Architect (2026 Vision)

Horizon Future Tech
Austin
Estimated Salary
USD 160.000 – USD 220.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Are you ready to architect the future of intelligent automation? Horizon Future Tech is pioneering the next generation of Agentic AI and Autonomous Systems. We are looking for a visionary Senior AI Systems Architect to lead the design of scalable, ethical, and high-performance machine learning infrastructures that will define the landscape of 2026 and beyond.

In this role, you won't just write code; you will build the backbone of our next-generation intelligent agents. You will bridge the gap between theoretical AI research and production-grade engineering, ensuring our systems are robust, secure, and capable of handling complex, real-world challenges.

Why Join Us?
We are a remote-first organization focused on solving the hardest problems in AI. You will have the autonomy to experiment with cutting-edge technologies, mentor a world-class engineering team, and directly influence the roadmap that will shape the future of work.

Responsibilities

  • Design and architect end-to-end AI/ML pipelines, focusing on LLMs, vector databases, and autonomous agent orchestration.
  • Lead the deployment of scalable machine learning models to production environments (Kubernetes, Docker, AWS/GCP).
  • Optimize model performance for latency, throughput, and cost efficiency in high-volume environments.
  • Collaborate with cross-functional teams (Product, Research, Security) to define AI requirements and roadmaps.
  • Establish best practices for MLOps, data governance, and AI ethics within the organization.
  • Conduct code reviews and technical architecture reviews to ensure code quality and system integrity.

Qualifications

  • 7+ years of experience in software engineering, with at least 4 years specifically focused on Machine Learning and AI systems.
  • Deep expertise in Python, PyTorch, TensorFlow, or JAX.
  • Strong understanding of LLM architectures, RAG (Retrieval-Augmented Generation), and prompt engineering.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies.
  • Familiarity with MLOps tools (MLflow, Kubeflow, Seldon) and CI/CD pipelines.
  • Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning LLM MLOps AWS Kubernetes System Architecture AI Ethics

Ready to Take This Challenge?

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