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Information Technology 🏢 Full Time ⭐️ Verified

2026 GenAI Infrastructure Architect

FutureScale
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

We are not just preparing for the future; we are architecting it. At FutureScale, we are defining the roadmap for 2026 and beyond, focusing on the convergence of Generative AI and scalable infrastructure. We are seeking a visionary 2026 GenAI Infrastructure Architect to lead our technical strategy and build the backbone of next-generation intelligent systems.


If you are a technical leader who thrives on ambiguity, possesses deep expertise in AI/ML systems, and is passionate about scaling transformative technologies, we want to meet you. Join us in shaping the intelligence layer of the digital economy.

Responsibilities

  • Lead 2026 Roadmap Strategy: Define and execute the technical vision for GenAI infrastructure scaling, ensuring readiness for the 2026 technological landscape.
  • System Architecture Design: Design robust, fault-tolerant, and high-performance architectures capable of handling massive generative model workloads.
  • Model Orchestration: Oversee the deployment and optimization of Large Language Models (LLMs) and multimodal systems across cloud and edge environments.
  • Team Leadership & Mentorship: Build and mentor a high-performance engineering team, fostering a culture of innovation and technical excellence.
  • Performance Optimization: Drive initiatives to reduce inference latency, optimize token generation speeds, and minimize operational costs.
  • Security & Compliance: Implement rigorous security protocols to protect proprietary data and ensure compliance with evolving AI regulations.

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Physics, or a related technical field (PhD preferred).
  • Experience: 8+ years of experience in software engineering, with at least 3 years in a senior architecture or engineering leadership role.
  • AI/ML Expertise: Deep understanding of Machine Learning operations (MLOps), Deep Learning frameworks (PyTorch, TensorFlow), and Generative AI architectures.
  • Cloud Proficiency: Strong hands-on experience with major cloud providers (AWS, GCP, or Azure) and container orchestration (Kubernetes).
  • Programming: Proficiency in Python, Go, or Rust with a focus on performance-critical systems.
  • Strategic Mindset: Proven track record of translating business requirements into scalable technical solutions and leading cross-functional teams.

Required Skills

Generative AI Machine Learning System Architecture Kubernetes Python Cloud Computing MLOps AI Strategy Leadership 2026 Roadmap

Ready to Take This Challenge?

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