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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Architect (2026 Vision)

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

Job Description

We are building the operating systems of the 2026 era. Nexus Future Labs is seeking a visionary Senior AI Architect to spearhead our mission of defining the technological landscape of the next decade. As we stand on the precipice of the AI-native era, your work will define how autonomous agents interact with the digital world.

In this role, you will not just write code; you will architect the future of intelligent systems. You will be responsible for designing scalable, ethical, and high-performance AI infrastructures that power our next-generation products. Join us in shaping the technology stack of tomorrow, today.

Responsibilities

  • Architect Agentic Workflows: Design and implement complex autonomous AI agent systems capable of multi-step reasoning and self-correction.
  • LLM Integration: Lead the integration of state-of-the-art Large Language Models (LLMs) into enterprise-grade applications, optimizing for speed and accuracy.
  • System Design: Build robust, fault-tolerant microservices and cloud-native architectures that support real-time AI inference.
  • Ethical AI Governance: Define and enforce best practices for bias mitigation, data privacy, and AI safety protocols.
  • Technical Leadership: Mentor a team of talented ML engineers and data scientists, fostering a culture of innovation and continuous learning.
  • Prototyping: Rapidly prototype and validate cutting-edge AI concepts to ensure they align with our 2026 product roadmap.

Qualifications

  • Experience: 7+ years of experience in software engineering and 3+ years specifically in AI/ML architecture.
  • Core Skills: Deep expertise in Python, TensorFlow/PyTorch, and distributed system design.
  • AI Knowledge: Proven track record of working with LLMs, RAG (Retrieval-Augmented Generation), and vector databases.
  • Cloud Mastery: Strong proficiency in AWS, GCP, or Azure with experience deploying machine learning models at scale.
  • Problem Solving: Ability to tackle complex, undefined technical problems and translate them into elegant architectural solutions.
  • Communication: Exceptional ability to communicate technical concepts to both technical and non-technical stakeholders.

Required Skills

Python Machine Learning Deep Learning System Design AWS GCP Kubernetes LLMs RAG PyTorch TensorFlow Distributed Systems

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