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Information Technology 🏢 Full Time ⭐️ Verified

Future Systems Architect

InnovateCore Solutions
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Join InnovateCore Solutions at the forefront of technological evolution as we build the digital infrastructure for 2026. We seek a visionary Future Systems Architect to design and implement next-generation platforms that will transform industries. This role offers the opportunity to shape how businesses adapt to emerging technologies like quantum computing, AI ethics frameworks, and decentralized networks. You'll work in our state-of-the-art Austin R&D hub, collaborating with world-class engineers to solve complex challenges that define the next decade of innovation.

Responsibilities

  • Architect scalable systems integrating quantum-resistant cryptography and AI governance protocols
  • Lead cross-functional teams in developing 6G infrastructure prototypes
  • Design ethical AI frameworks ensuring compliance with 2026 regulatory standards
  • Research and implement blockchain solutions for supply chain transparency
  • Create predictive models for climate-resilient urban planning systems
  • Develop zero-trust architecture frameworks for metaverse security
  • Document system blueprints using advanced visualization tools

Qualifications

  • Master's degree in Computer Science, Systems Engineering, or related field
  • 5+ years experience in distributed systems architecture
  • Expertise in quantum computing principles and post-quantum cryptography
  • Proven track record in designing AI ethics and governance frameworks
  • Strong knowledge of 6G network protocols and edge computing
  • Experience with blockchain consensus mechanisms and smart contracts
  • Certification in zero-trust architecture (e.g., CISA ZT-EP)
  • Published research in IEEE or ACM journals on future technologies

Required Skills

Quantum Computing AI Governance 6G Protocols Zero-Trust Architecture Blockchain Systems Architecture Predictive Modeling

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