Job Description
Join Aethelgard Dynamics as we pioneer the technological frontier of 2026. We are seeking a visionary Lead AI & Quantum Integration Architect to bridge the gap between classical machine learning and next-generation quantum computing architectures.
In this pivotal role, you will not merely write code; you will define the protocols for a new era of computational power. You will work in a high-performance environment where the impossible becomes the standard, directly influencing the future of enterprise AI.
Responsibilities
- Architectural Design: Design and implement hybrid quantum-classical algorithms tailored for enterprise-scale applications and complex data sets.
- Technical Leadership: Mentor a team of top-tier engineers and researchers, fostering a culture of innovation, technical excellence, and autonomy.
- Hardware Integration: Collaborate directly with quantum hardware engineers to optimize software stacks for emerging superconducting and trapped-ion processors.
- Optimization: Develop advanced strategies to minimize quantum noise and maximize computational throughput in real-world scenarios.
- Prototyping: Build rapid prototypes to validate new integration methodologies before scaling to production-level infrastructure.
- Strategy: Define the long-term technical roadmap for our AI integration initiatives and ensure alignment with business goals.
- Stakeholder Management: Translate complex quantum concepts into clear value propositions for non-technical stakeholders and investors.
Qualifications
- Education: Master’s or PhD in Computer Science, Physics, Mathematics, or a related field with a focus on computational theory.
- Experience: 5+ years of experience in software engineering with a strong focus on AI/ML and distributed systems.
- Quantum Expertise: Proficiency in quantum programming frameworks such as Qiskit, Cirq, or PyQuil with a demonstrated portfolio of quantum algorithms.
- Deep Learning: Strong background in TensorFlow, PyTorch, or similar deep learning libraries with experience deploying models in production.
- Programming: Expert-level proficiency in Python, C++, or Rust with a deep understanding of memory management and parallel computing.
- Communication: Exceptional ability to translate complex technical concepts for diverse stakeholders, including investors and technical leads.