Job Description
Shape the Future of Intelligence. Nexus Horizon Solutions is leading the charge into the technological paradigm of 2026. We are looking for a visionary Senior AI Architect to design the next generation of autonomous systems and generative models. In this pivotal role, you will bridge the gap between theoretical research and production-grade engineering, ensuring our platforms remain at the cutting edge of artificial intelligence.
Why This Role Matters
As we prepare for the explosive growth of AI in 2026, we need a leader who can architect scalable, secure, and efficient systems. You will be the technical face of our 'Future Forward' initiative, guiding a team of elite engineers and researchers.
Responsibilities
- System Architecture: Design and implement scalable AI frameworks capable of handling exascale data workloads for enterprise clients.
- Generative AI Leadership: Spearhead the development of next-generation Large Language Models (LLMs) and multimodal AI systems.
- Technical Roadmap: Define the strategic technical vision for the 2026 product suite, identifying emerging trends like quantum-ready algorithms.
- Performance Optimization: Engineer high-performance inference pipelines that minimize latency and maximize cost-efficiency on cloud infrastructure.
- Talent Development: Mentor a high-performing engineering team, fostering a culture of innovation, code excellence, and continuous learning.
- Collaboration: Partner closely with product managers and data scientists to translate complex AI capabilities into intuitive user experiences.
- Risk Management: Establish rigorous security and compliance standards for AI deployment, ensuring ethical use and data privacy.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 7+ years in software engineering, with at least 3 years in a senior architectural role within the AI/ML sector.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, or JAX; extensive experience with MLOps tools (MLflow, Kubeflow).
- Cloud Mastery: Expert knowledge of cloud architecture (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Research Skills: Proven track record of publishing in top-tier AI conferences (NeurIPS, ICML, ICLR) or shipping impactful research to production.
- Communication: Exceptional ability to articulate complex technical concepts to non-technical stakeholders and executive leadership.
- Problem Solving: Demonstrated ability to architect solutions for ambiguous, high-stakes problems.