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Senior AI Architect (2026 Roadmap)

Quantum Leap Technologies
San Francisco
Estimated Salary
USD 185.000 – USD 260.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Are you ready to define the future of intelligent systems?

Quantum Leap Technologies is on a mission to pioneer the technological landscape for the year 2026 and beyond. We are seeking a visionary Senior AI Architect to lead our architectural strategy, designing scalable, high-performance machine learning systems that will power the next generation of digital experiences.

In this role, you won't just maintain existing systems; you will architect the roadmap for 2026. You will bridge the gap between theoretical AI research and production-grade engineering, ensuring our platforms are robust, ethical, and future-proof.

Why Join Us?

  • Impactful Work: Build core infrastructure used by millions.
  • Future-First: Focus on emerging technologies (LLMs, Agents, Edge AI).
  • Competitive Package: Comprehensive benefits and equity package.

Join us in shaping the trajectory of AI for the decade ahead.

Responsibilities

  • Lead the end-to-end architectural design of our 2026 AI infrastructure, ensuring scalability and fault tolerance.
  • Define the technical roadmap for Generative AI integration and large-scale model deployment.
  • Collaborate with cross-functional teams (Data Science, Product, Security) to translate business requirements into technical solutions.
  • Optimize existing ML pipelines for latency, throughput, and cost-efficiency in cloud environments.
  • Establish best practices for MLOps, monitoring, and observability within the engineering organization.
  • Mentor junior architects and engineers, fostering a culture of innovation and technical excellence.

Qualifications

  • 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture.
  • Deep expertise in Python, PyTorch, TensorFlow, and modern ML frameworks.
  • Proven experience designing systems for Large Language Models (LLMs) and Generative AI.
  • Strong background in distributed systems, microservices, and cloud architecture (AWS, GCP, or Azure).
  • Familiarity with MLOps tools (Kubeflow, MLflow, Airflow) and containerization (Docker, Kubernetes).
  • Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.

Required Skills

AI Architecture Machine Learning Python PyTorch TensorFlow AWS Kubernetes MLOps Generative AI LLMs System Design

Ready to Take This Challenge?

Make sure your resume is ready. Submit your application now before the deadline.

Apply Now

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