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Senior AI Architect (2026 Vision)

Nexus Future Labs
San Francisco
Estimated Salary
USD 160.000 – USD 230.000
Live Update
23 Mei 2026
Deadline
23 Mei 2027

Job Description

Join the Architects of Tomorrow. Nexus Future Labs is seeking a visionary Senior AI Architect to lead the development of our proprietary Agentic AI ecosystem designed for the 2026 era. You will be at the forefront of integrating Large Language Models (LLMs) with autonomous decision-making frameworks to build systems that don't just respond, but act.


As a key player in our mission to redefine human-computer interaction, you will design scalable, secure, and ethically aligned AI infrastructure. If you are passionate about the convergence of Generative AI, Vector Databases, and Reinforcement Learning, this is your opportunity to build the foundational technology of the next decade.

Responsibilities

  • Architect Agentic Workflows: Design and implement complex autonomous AI agents capable of multi-step reasoning and tool usage.
  • Model Optimization: Fine-tune and optimize LLMs for specific industry verticals, ensuring low-latency inference and high accuracy.
  • System Scalability: Build distributed systems capable of handling petabyte-scale data processing and millions of concurrent requests.
  • MLOps Implementation: Establish robust CI/CD pipelines for machine learning models, ensuring seamless deployment and monitoring.
  • Security & Compliance: Lead initiatives in data privacy, model governance, and adversarial robustness.
  • Research & Innovation: Stay ahead of the curve in emerging AI paradigms (e.g., Neuro-symbolic AI, Multimodal models).

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
  • 5+ years of experience in software engineering with a focus on Machine Learning or Artificial Intelligence.
  • Deep expertise in Python, PyTorch, and TensorFlow.
  • Experience designing and deploying LLMs (e.g., GPT-4, Llama 3, Claude).
  • Proficiency with Vector Databases (Pinecone, Weaviate, Milvus) and RAG architectures.
  • Strong understanding of distributed systems, cloud infrastructure (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
  • Excellent communication skills with the ability to translate complex technical concepts for diverse stakeholders.

Required Skills

Python PyTorch TensorFlow LLMs Machine Learning MLOps Docker Kubernetes AWS RAG Vector Databases Generative AI

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