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Information Technology 🏢 Full Time ⭐️ Verified

2026 Horizon AI Architect | San Francisco, CA

Nebula Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

We are seeking a visionary AI Architect: 2026 Horizon to lead our next-generation infrastructure projects. As we prepare to redefine the digital landscape of the coming years, you will be at the forefront of deploying Agentic AI and Large Language Models (LLMs) into scalable production environments. This is a unique opportunity to build the systems that will power the future of our company and our clients.

Why Join Us?

Our mission is to accelerate the transition to autonomous intelligent systems. We offer a competitive compensation package, equity packages, and a collaborative culture that values innovation over convention.

Responsibilities

  • Design Future-Proof Systems: Architect and implement high-performance AI infrastructure capable of scaling to petabyte-level data lakes by 2026.
  • Lead GenAI Integration: Spearhead the integration of Generative AI workflows into core business operations to drive automation and efficiency.
  • Model Optimization: Fine-tune and optimize large foundation models for specific domain applications, ensuring low-latency inference.
  • Technical Strategy: Define the technical roadmap for our AI initiatives, evaluating emerging technologies to maintain a competitive edge.
  • Cross-Functional Collaboration: Work closely with product managers, data scientists, and software engineers to translate business requirements into technical solutions.
  • Risk & Compliance: Establish best practices for AI ethics, data privacy, and model governance to ensure regulatory compliance.

Qualifications

  • Experience: 7+ years of experience in software engineering, with at least 3 years in AI/ML architecture.
  • Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with cloud platforms (AWS/GCP/Azure).
  • Architecture: Deep understanding of microservices, distributed systems, and vector databases (e.g., Pinecone, Milvus).
  • Generative AI: Hands-on experience with RAG (Retrieval-Augmented Generation) pipelines and LLM fine-tuning.
  • Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
  • Problem Solving: Demonstrated ability to solve complex technical problems in ambiguous environments.

Required Skills

Python AI Architecture Machine Learning Generative AI LLM Cloud Computing Distributed Systems PyTorch TensorFlow AWS System Design

Ready to Take This Challenge?

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