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Senior AI Architect | Future Tech Strategy

Apex Future Systems
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

We are seeking a visionary Senior AI Architect to lead our strategic initiatives in artificial intelligence and future-tech infrastructure. As we look toward the 2026 horizon, we need a technical leader who can bridge the gap between cutting-edge research and scalable enterprise solutions. You will define the architectural roadmap for our next-generation AI ecosystem, ensuring robustness, security, and scalability.

Join a team dedicated to pioneering the next generation of intelligent applications and redefining the future of human-computer interaction.

Responsibilities

  • Architect and implement scalable AI/ML infrastructure aligned with 2026 strategic goals and industry standards.
  • Lead the design, training, and deployment of Generative AI models and Large Language Models (LLMs).
  • Collaborate with cross-functional teams to integrate AI solutions into complex existing workflows.
  • Establish best practices for model governance, ethics, and bias mitigation in production environments.
  • Conduct deep technical research to evaluate emerging technologies and frameworks (e.g., Graph Neural Networks, Federated Learning).
  • Oversee the MLOps pipeline, ensuring seamless CI/CD for machine learning models.
  • Act as a mentor to junior engineers, fostering a culture of innovation and continuous learning.

Qualifications

  • 10+ years of experience in software engineering, with 5+ years specializing in AI/ML architecture.
  • Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related technical field.
  • Deep expertise in Python, PyTorch, TensorFlow, and cloud-native architectures (AWS, GCP, Azure).
  • Proven track record of leading large-scale machine learning projects from conception to production.
  • Strong understanding of MLOps, data pipelines, distributed systems, and high-availability architectures.
  • Experience with Vector Databases and RAG (Retrieval-Augmented Generation) architectures.
  • Excellent communication skills with the ability to translate technical concepts for non-technical stakeholders.

Required Skills

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

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