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Senior AI Architect | Project 2026 Lead

Apex Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

Are you ready to build the infrastructure of tomorrow? Apex Future Systems is seeking a visionary Senior AI Architect to spearhead our Project 2026 initiative.

We are on the cutting edge of next-generation generative intelligence and adaptive neural networks. In this pivotal role, you will define the architectural blueprints for systems that will define the technological landscape of the late 2020s. You won't just be maintaining systems; you will be inventing the future of scalable AI.

Why join us?

  • Work with a team of world-class engineers and futurists.
  • Shape the roadmap for next-gen quantum-ready AI infrastructure.
  • Competitive compensation and equity packages.

Responsibilities

  • Lead the architectural design and implementation of the Project 2026 core AI ecosystem.
  • Define and enforce best practices for scalable machine learning pipelines and data governance.
  • Collaborate with cross-functional teams (Data Science, DevOps, Product) to translate business requirements into technical solutions.
  • Mentor junior architects and engineers, fostering a culture of innovation and technical excellence.
  • Research and prototype cutting-edge technologies, including Large Language Models (LLMs) and autonomous agents.
  • Oversee system performance optimization, security, and fault tolerance at scale.

Qualifications

  • Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 10+ years of experience in software engineering, with at least 5 years in a senior architecture role.
  • Deep expertise in Python, TensorFlow, PyTorch, and distributed systems.
  • Proven track record of designing and deploying production-grade AI/ML systems.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Strong understanding of machine learning lifecycle, including MLOps and model deployment strategies.

Required Skills

Python TensorFlow PyTorch AWS GCP Kubernetes MLOps System Design Machine Learning Deep Learning

Ready to Take This Challenge?

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