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Information Technology 🏒 Full Time ⭐️ Verified

Lead 2026 AI Solutions Architect

FutureForge Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 240.000
New
Live Update
2 Juni 2026
Deadline
2 Jun 2027

Job Description

Are you ready to shape the future? At FutureForge Technologies, we are actively preparing for the next digital leap. We are seeking a visionary Lead 2026 AI Solutions Architect to join our elite engineering team in San Francisco. In this role, you will pioneer next-generation AI frameworks, focusing on the emerging technological trends and infrastructural demands projected for 2026 and beyond. If you are passionate about pushing the boundaries of artificial intelligence, machine learning, and scalable cloud architecture, this is your opportunity to leave a lasting mark on the tech landscape.

Responsibilities

  • Design and deploy highly scalable, forward-looking AI architectures that anticipate 2026 technological standards and capabilities.
  • Lead cross-functional engineering teams in the integration of Large Language Models (LLMs) and autonomous agents into core enterprise platforms.
  • Conduct rigorous R&D to evaluate emerging hardware accelerators and next-gen cloud computing paradigms.
  • Collaborate with executive stakeholders to align AI roadmaps with long-term business objectives.
  • Establish best practices for ethical AI development, focusing on security, compliance, and sustainability.
  • Mentor senior engineers and foster a culture of continuous innovation and technical excellence.
  • Oversee the transition from legacy machine learning pipelines to hyper-automated, real-time data ecosystems.

Qualifications

  • Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
  • Minimum of 7+ years of experience in software architecture, with at least 4 years dedicated to AI/ML engineering.
  • Deep expertise in modern AI frameworks (e.g., PyTorch, TensorFlow) and MLOps methodologies.
  • Proven track record of designing large-scale, distributed systems on AWS, GCP, or Azure.
  • Strong understanding of generative AI, neural network optimization, and edge computing.
  • Exceptional leadership, communication, and project management skills.
  • Ability to work in a hybrid environment in San Francisco, CA.

Required Skills

AI Architecture Machine Learning MLOps LLM Integration Cloud Computing Python Distributed Systems Edge Computing

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