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Senior AI Architect: 2026 Roadmap

Apex Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

We are not just building software; we are architecting the digital reality of 2026. Apex Future Systems is seeking a visionary Senior AI Architect to lead our infrastructure toward the next generation of artificial intelligence.

In this role, you will define the technical strategy for our flagship product, ensuring scalability, security, and innovation that defines the era of 2026. You will bridge the gap between theoretical research and production-grade deployment, working on cutting-edge multimodal models designed for enterprise-scale impact.

Responsibilities

  • Lead the 2026 Technical Roadmap: Define the architectural vision for the next two years, integrating Generative AI, predictive analytics, and autonomous agents into our core ecosystem.
  • Design Scalable Infrastructure: Build robust, high-availability systems capable of handling billions of inference requests daily with sub-millisecond latency.
  • Optimize LLM Performance: Implement advanced quantization, pruning, and distributed inference strategies to reduce operational costs and improve response times.
  • Enterprise Integration: Collaborate with product and security teams to integrate AI capabilities into complex, secure enterprise workflows.
  • Mentorship: Guide a team of talented engineers and data scientists in best practices for MLOps, model training, and system architecture.

Qualifications

  • Experience: 7+ years of experience in software engineering, with at least 3 years focused on AI/ML architecture and system design.
  • Tech Stack: Deep proficiency in Python, PyTorch, TensorFlow, and experience with GPU acceleration (CUDA) and TPU environments.
  • System Design: Proven ability to design large-scale distributed systems using Kubernetes, Docker, and cloud-native architectures (AWS/GCP).
  • AI Expertise: Strong understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning principles.
  • Problem Solving: Demonstrated ability to solve complex engineering challenges under tight deadlines in a fast-paced environment.

Required Skills

Python PyTorch Machine Learning System Architecture Kubernetes AWS Generative AI NLP Distributed Systems

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