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Chief Agentic AI Architect (2026 Vision)

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

We are Nexus Horizon Labs, a cutting-edge R&D firm pioneering the technological landscape for the year 2026. We are seeking a visionary Chief Agentic AI Architect to lead the design and deployment of autonomous intelligent systems that will redefine human-machine interaction. This is not just a job; it is a mission to build the operational backbone of the future.

In this role, you will bridge the gap between theoretical AI research and scalable production environments, ensuring our systems are robust, ethical, and capable of autonomous decision-making.

Responsibilities

  • Architect Autonomous Systems: Design and implement complex multi-agent architectures capable of self-correction and independent problem-solving in dynamic environments.
  • Lead R&D Strategy: Define the technical roadmap for Nexus Horizon Labs, specifically focusing on Agentic AI frameworks and Next-Gen Neural Networks.
  • Optimize LLM Performance: Fine-tune large language models for high-context reasoning and execute prompt engineering strategies that minimize hallucinations.
  • Ensure Ethical AI: Establish and enforce governance frameworks to ensure AI autonomy adheres to strict ethical standards and safety protocols.
  • Cross-Functional Leadership: Mentor a team of data scientists and engineers, fostering a culture of innovation and technical excellence.
  • Scalability Engineering: Oversee the infrastructure required to support billions of autonomous agent interactions efficiently and securely.

Qualifications

  • Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related field is highly preferred.
  • Experience: Minimum of 8+ years of experience in software engineering, with at least 3 years specifically in AI/ML architecture.
  • Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with vector databases (e.g., Pinecone, Milvus).
  • Domain Knowledge: Deep understanding of LLMs, Transformers, Reinforcement Learning from Human Feedback (RLHF), and Agentic workflows.
  • Leadership: Proven track record of leading technical teams and delivering high-impact projects from conception to deployment.
  • Future-Ready Mindset: Ability to anticipate emerging trends in AI and adapt technical strategies accordingly.

Required Skills

Agentic AI Large Language Models Python PyTorch TensorFlow Autonomous Systems Machine Learning Architecture Cloud Computing Leadership

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