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Senior AI Architect: Next-Gen Generative Systems (2026 Roadmap)

Apex Horizon Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Shape the Future of Intelligence

We are on the cutting edge of defining the AI landscape for the 2026 era. Apex Horizon Technologies is seeking a visionary Senior AI Architect to lead the development of next-generation Agentic AI systems. If you are passionate about building scalable, autonomous AI agents and possess deep expertise in Large Language Models (LLMs), we want you on our team.

In this role, you will bridge the gap between theoretical AI research and production-grade engineering, architecting systems that will define how humans interact with machines in the near future.

Responsibilities

  • Architect Next-Gen Systems: Design and implement the technical architecture for autonomous AI agents and multi-modal generative models targeting the 2026 roadmap.
  • LLM Optimization: Lead the optimization of inference pipelines and fine-tuning strategies for proprietary and open-source foundation models.
  • RAG & Vector Databases: Spearhead the development of advanced Retrieval-Augmented Generation (RAG) architectures to ensure factual accuracy and context awareness.
  • Scalability & Performance: Ensure high availability and low-latency performance for AI workloads serving millions of users globally.
  • Technical Leadership: Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
  • Collaboration: Partner with product and engineering teams to translate business requirements into robust AI technical solutions.

Qualifications

  • Experience: 7+ years of experience in software engineering, with at least 4 years specifically in Machine Learning and AI architecture.
  • Technical Mastery: Deep understanding of deep learning frameworks (PyTorch, TensorFlow) and LLM architectures (Transformers, GPT, BERT).
  • Programming: Proficiency in Python, C++, and distributed systems programming.
  • Tooling: Hands-on experience with MLOps tools, containerization (Docker/Kubernetes), and cloud platforms (AWS/GCP/Azure).
  • Education: M.S. or Ph.D. in Computer Science, Artificial Intelligence, or a related field is preferred.
  • Soft Skills: Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow LLM Generative AI MLOps Docker Kubernetes AWS GCP Machine Learning AI Architecture Python

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