Job Description
Are you ready to architect the future of intelligence? Nexus Horizon Systems is seeking a visionary Lead AI Architect to spearhead our next-generation Generative AI initiatives.
In this pivotal role, you will define the technical roadmap for autonomous systems and large-scale language models that will define the industry landscape in 2026 and beyond. We are not just building software; we are constructing the cognitive infrastructure of tomorrow. If you are passionate about ethical AI, scalable architectures, and solving complex problems at the intersection of human creativity and machine logic, we want to hear from you.
Why join us? We offer a competitive benefits package, equity opportunities, and a culture that prioritizes innovation, inclusivity, and technical excellence.
Responsibilities
- Architect Next-Gen Systems: Design and implement scalable, high-performance AI architectures for Generative AI and Autonomous Agents.
- Model Development: Lead the end-to-end development lifecycle of Large Language Models (LLMs), ensuring optimal performance and accuracy.
- Technical Strategy: Define the long-term technical vision for our AI infrastructure, driving innovation in deep learning and neural networks.
- Team Leadership: Mentor a team of talented engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Collaboration: Partner with product managers and stakeholders to translate complex business requirements into robust technical solutions.
- Ethical AI: Implement frameworks to ensure AI systems are transparent, unbiased, and adhere to global safety standards.
- Infrastructure Optimization: Oversee the deployment of AI models on cloud infrastructure, ensuring cost-efficiency and scalability.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field; PhD preferred.
- Experience: 5+ years of experience in software engineering, with at least 3 years specializing in AI/ML architecture and deep learning.
- Technical Proficiency: Strong proficiency in Python, PyTorch, TensorFlow, or JAX; experience with MLOps tools (MLflow, Kubeflow) is required.
- Generative AI: Proven track record of working with LLMs (e.g., GPT, Llama), fine-tuning models, and RAG architectures.
- Cloud Expertise: Deep experience deploying models on AWS, GCP, or Azure.
- Problem Solving: Exceptional ability to troubleshoot complex system bottlenecks and optimize inference latency.
- Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to diverse audiences.