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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Architect (2026 Strategic Vision)

Quantum Leap Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

We are looking for a visionary Senior AI Architect to lead our strategic technology roadmap toward 2026. In this pivotal role, you will bridge the gap between theoretical AI research and production-grade deployment, focusing on next-generation autonomous systems and edge computing.

Quantum Leap Technologies is at the forefront of digital transformation. You will work with a cross-functional team of engineers, product managers, and data scientists to build scalable, secure, and future-proof AI solutions that define the standard for the industry.

Responsibilities

  • Define and execute the technical roadmap for 2026 infrastructure initiatives, focusing on Agentic AI workflows and large language model (LLM) optimization.
  • Architect high-performance distributed systems capable of handling petabyte-scale data processing with low-latency requirements.
  • Lead the migration and modernization of legacy codebases to support next-gen cloud-native environments.
  • Collaborate with data science teams to fine-tune models for specific enterprise use cases, ensuring accuracy and compliance with privacy regulations.
  • Establish best practices for code quality, security, and scalability across the engineering department.
  • Mentor junior developers and engineers, fostering a culture of continuous learning and innovation.

Qualifications

  • 10+ years of experience in software engineering, with at least 5 years in a senior architecture role within the tech industry.
  • Deep expertise in Python, Rust, or Go, with a strong understanding of systems programming and concurrency.
  • Proven track record of designing scalable microservices architectures and cloud-native solutions (AWS, GCP, or Azure).
  • Experience deploying and optimizing LLMs and machine learning pipelines in production environments.
  • Familiarity with DevOps practices, CI/CD pipelines, and containerization technologies (Docker, Kubernetes).
  • Strong problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python Rust Machine Learning System Architecture Cloud Computing AWS Kubernetes DevOps AI

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