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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Architect (2026 Vision)

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

Job Description

We are at the forefront of the technological revolution, building the systems that will define the year 2026 and beyond. Nexus Future Systems is seeking a visionary Senior AI Architect to lead the design and implementation of next-generation artificial intelligence infrastructure.

In this role, you will not just write code; you will architect the future. You will bridge the gap between theoretical machine learning models and scalable, production-grade applications. We need someone who is passionate about the horizon of 2026, ready to tackle challenges in generative AI, autonomous agents, and quantum-ready algorithms.

If you are a technical leader who thrives in ambiguity and wants to shape the roadmap of intelligent systems, we want to meet you.

Responsibilities

  • Architect and design scalable, high-performance AI systems capable of supporting enterprise-grade workloads.
  • Lead the research and implementation of cutting-edge machine learning models, specifically focusing on Generative AI and LLM optimization.
  • Define technical roadmaps for the engineering team, ensuring alignment with long-term 2026 strategic goals.
  • Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical solutions.
  • Mentor junior developers and senior engineers alike, fostering a culture of technical excellence and innovation.
  • Ensure system reliability, security, and ethical AI compliance across all deployed models.

Qualifications

  • 10+ years of experience in software engineering and at least 5 years in AI/ML architecture.
  • Deep expertise in Python, PyTorch, TensorFlow, or JAX.
  • Strong background in cloud infrastructure (AWS, GCP, or Azure) and containerization (Kubernetes, Docker).
  • Proven track record of deploying large-scale machine learning models into production environments.
  • Experience with MLOps tools and pipelines (MLflow, Kubeflow, Airflow).
  • Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Required Skills

Python Machine Learning Deep Learning AWS Kubernetes PyTorch TensorFlow MLOps Cloud Architecture Generative AI

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