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Lead Architect: Generative AI & Agentic Systems (2026 Vision)

Nexus Horizon AI
Austin
Estimated Salary
USD 165.000 – USD 245.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

We are not just predicting the future; we are engineering it. Nexus Horizon AI is seeking a visionary Lead Architect: Generative AI to define the technical roadmap for 2026 and beyond.

In this pivotal role, you will spearhead the development of the next generation of autonomous agents and multimodal AI systems. We are looking for a technical heavyweight who can bridge the gap between theoretical research and scalable production deployment. If you are passionate about building the digital brain of tomorrow, this is your opportunity to lead.

Responsibilities

  • Architect and deploy cutting-edge Agentic AI workflows, enabling autonomous decision-making capabilities in enterprise environments.
  • Design and implement proprietary fine-tuning pipelines for Large Language Models (LLMs) to enhance reasoning, safety, and domain-specific accuracy.
  • Optimize model inference latency and reduce operational costs through advanced LLMops strategies, quantization, and pruning.
  • Establish the core infrastructure for Multimodal Learning, integrating text, vision, and audio generation into unified models.
  • Collaborate with product and engineering teams to integrate generative AI into complex, high-stakes software products.
  • Lead research initiatives in Constitutional AI and Reinforcement Learning from Human Feedback (RLHF) to ensure ethical alignment.

Qualifications

  • Master’s or PhD in Computer Science, Mathematics, or a related field, or equivalent years of senior-level industry experience.
  • Deep technical proficiency in Python, PyTorch, and TensorFlow, with a demonstrated history of publishing in top-tier AI conferences (NeurIPS, ICML, ICLR).
  • Extensive hands-on experience building, training, and deploying Large Language Models (GPT-4, Llama, Claude) and Multimodal models.
  • Strong understanding of vector databases, RAG (Retrieval-Augmented Generation), and semantic search architectures.
  • Familiarity with MLOps tools (MLflow, Kubeflow) and cloud infrastructure (AWS/GCP/Azure) at a scale.
  • Exceptional leadership skills with the ability to mentor a team of engineers and drive technical vision.

Required Skills

Python PyTorch TensorFlow Generative AI LLM Large Language Models Machine Learning Deep Learning NLP Natural Language Processing LLMops Reinforcement Learning AI Architecture Multimodal AI

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