Job Description
Are you ready to define the standard for Artificial Intelligence in 2026?
Nexus Core Systems is at the forefront of the next technological revolution. We are looking for a visionary Senior AI Architect to lead the design and implementation of our next-generation generative AI and autonomous agent infrastructure. You won't just be writing code; you will be architecting the brain of our enterprise solutions for the future.
In this role, you will bridge the gap between theoretical AI research and scalable production systems. You will work with a world-class team to deploy models that redefine user experiences and operational efficiency.
Responsibilities
- System Architecture: Design and deploy scalable machine learning pipelines and large language model (LLM) infrastructures optimized for high-performance computing.
- Model Optimization: Lead the research and implementation of model quantization, distillation, and edge deployment strategies for latency-critical applications.
- Technical Leadership: Mentor a team of data scientists and ML engineers, fostering a culture of innovation and best practices in AI/ML engineering.
- Strategic Roadmap: Define the technical roadmap for AI capabilities, ensuring alignment with the company's 2026 product vision and business goals.
- Cross-Functional Collaboration: Partner with product managers and engineering leads to translate complex business requirements into robust AI solutions.
- Performance Tuning: Continuously monitor, evaluate, and improve model accuracy, throughput, and cost-efficiency in production environments.
Qualifications
- Education: Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 7+ years of professional experience in software engineering and machine learning, with at least 3 years in a senior architectural role.
- Technical Skills: Deep proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with MLOps tools (Docker, Kubernetes, MLflow) is required.
- AI Specialization: Strong understanding of Large Language Models (LLMs), Transformers, and Generative AI architectures.
- Cloud Expertise: Proven experience architecting solutions on major cloud providers (AWS, GCP, or Azure) with a focus on serverless and edge computing.
- Soft Skills: Exceptional problem-solving abilities and the communication skills to explain complex technical concepts to non-technical stakeholders.