Job Description
Are you ready to architect the future of technology? Nexus Horizon Labs is seeking a visionary Senior AI Solutions Architect to lead our strategic roadmap toward 2026 and beyond. We are building the next generation of intelligent systems, and we need a leader who can bridge the gap between theoretical AI and scalable, production-ready infrastructure.
In this role, you will define the architectural vision for our generative AI platforms, ensuring our solutions are secure, scalable, and future-proof. You will collaborate with top-tier engineers and product leaders to transform complex AI concepts into robust software solutions.
Responsibilities
- Architect Future-Ready Systems: Design and oversee the development of scalable AI infrastructure and cloud-native solutions tailored for the 2026 technological landscape.
- Lead AI Integration: Spearhead the integration of Large Language Models (LLMs) and generative AI tools into core business workflows to drive automation and efficiency.
- Technical Strategy: Define technical roadmaps and best practices, ensuring alignment with company goals and industry standards for AI safety and ethics.
- Mentorship: Guide and mentor a team of senior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Stakeholder Communication: Translate complex technical concepts into clear, actionable insights for executive leadership and non-technical stakeholders.
- Security & Compliance: Implement rigorous security protocols and data governance frameworks to protect proprietary AI models and user data.
Qualifications
- Experience: 10+ years of experience in software architecture, with at least 5 years specifically focused on AI, Machine Learning, or Data Engineering.
- Tech Stack: Proficiency in Python, Java, or Go, with deep knowledge of cloud platforms (AWS, GCP, or Azure).
- AI Expertise: Strong understanding of neural networks, NLP, and vector databases (e.g., Pinecone, Milvus).
- Leadership: Proven track record of leading cross-functional teams and delivering large-scale projects on time and within budget.
- Certifications: AWS Certified Solutions Architect or Google Professional Machine Learning Engineer preferred.
- Problem Solving: Exceptional ability to troubleshoot complex system failures and optimize performance at scale.