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Senior AI Architect (2026 Readiness)

Nexus Future Labs
San Francisco
Estimated Salary
USD 165.000 – USD 240.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Join the Pioneers of Tomorrow

Nexus Future Labs is on a mission to architect the intelligence layer for the year 2026 and beyond. We are looking for a visionary Senior AI Architect to lead the development of scalable, autonomous systems that define the next generation of human-computer interaction. If you are passionate about pushing the boundaries of generative AI, large-scale model optimization, and ethical machine learning, we want to hear from you.

In this role, you will bridge the gap between theoretical research and production-grade engineering, ensuring our solutions are not just advanced, but resilient and future-proof.

Responsibilities

  • Architectural Leadership: Design and implement robust, scalable AI infrastructure capable of handling exascale data workloads.
  • Future-Proofing: Proactively research and integrate emerging technologies and standards anticipated to define the 2026 tech landscape.
  • Model Optimization: Lead the optimization of LLMs and neural networks for latency reduction and cost efficiency in cloud environments.
  • Team Mentorship: Foster a culture of innovation by mentoring junior engineers and conducting technical workshops on advanced AI concepts.
  • Cross-Functional Collaboration: Work closely with product managers and data scientists to translate complex business requirements into technical AI solutions.
  • R&D Strategy: Define the technical roadmap for AI research initiatives, ensuring alignment with company long-term goals.

Qualifications

  • Education: Master’s degree in Computer Science, Artificial Intelligence, or a related field (PhD preferred).
  • Experience: Minimum of 7+ years of experience in software engineering with a specific focus on AI/ML architecture.
  • Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Docker).
  • Cloud Mastery: Proven track record of deploying large-scale AI models on AWS, Azure, or GCP.
  • Problem Solving: Exceptional ability to troubleshoot complex system bottlenecks and architectural challenges.
  • Communication: Superior verbal and written communication skills, with the ability to articulate complex technical ideas to non-technical stakeholders.

Required Skills

Python TensorFlow PyTorch Kubernetes Cloud Architecture Machine Learning NLP Distributed Systems System Design

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