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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Solutions Architect

QuantumLeap Technologies
Austin
Estimated Salary
USD 180.000 – USD 240.000
Live Update
16 Mei 2026
Deadline
16 Mei 2027

Job Description

Join QuantumLeap Technologies at the forefront of the 2026 digital transformation revolution. We're seeking a visionary Senior AI Solutions Architect to design and implement next-generation artificial intelligence systems that will redefine industries. This role offers unparalleled opportunity to shape the future of AI-driven innovation in a collaborative, cutting-edge environment. You'll work with Fortune 500 clients to deploy scalable ML solutions while mentoring emerging talent in our Austin innovation hub.

Responsibilities

  • Architect end-to-end AI/ML solutions for enterprise clients using advanced LLM frameworks and generative AI
  • Lead cross-functional teams in deploying production-ready AI systems on cloud-native platforms
  • Develop ethical AI governance frameworks aligned with 2026 regulatory standards
  • Translate complex business requirements into scalable technical specifications
  • Drive innovation through prototyping of next-gen AI applications in quantum computing environments
  • Optimize AI models for edge computing deployment in IoT ecosystems
  • Establish best practices for MLOps and continuous model improvement pipelines

Qualifications

  • 8+ years in AI/ML architecture with proven experience deploying enterprise-scale solutions
  • Expertise in Python, TensorFlow, PyTorch, and cloud platforms (AWS/GCP/Azure)
  • Advanced degree in Computer Science, AI, or related field (PhD preferred)
  • Deep understanding of transformer architectures and generative AI systems
  • Certification in cloud architecture and AI ethics frameworks
  • Strong background in distributed computing and quantum machine learning concepts
  • Experience leading technical teams and mentoring AI engineers

Required Skills

AI Architecture Machine Learning LLM Generative AI Cloud Computing MLOps Quantum Computing Ethics TensorFlow PyTorch

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