Job Description
We are on the cusp of the AI revolution, and NexusCore Systems is looking for a visionary Senior AI Architect to shape the landscape of Generative Intelligence for 2026 and beyond.
In this pivotal role, you won't just be managing models; you will architect the next generation of Agentic AI systems capable of autonomous reasoning and complex decision-making. We need a technical pioneer who thrives in ambiguity and possesses the expertise to build robust, scalable infrastructure for the future of enterprise.
Why Join Us?
- Future-Proof Your Career: Work on cutting-edge Agentic AI technologies that will dominate the 2026 market.
- Unlimited Growth: Direct exposure to C-suite executives and hands-on influence on architectural strategy.
- Top-Tier Compensation: Competitive salary plus equity package.
Responsibilities
- Design and implement scalable, high-throughput inference pipelines for Large Language Models (LLMs) and multimodal AI systems.
- Lead the research and integration of emerging AI paradigms, specifically focusing on Agentic AI and Autonomous Agents for 2026.
- Optimize model performance using techniques like quantization, pruning, and distributed training across heterogeneous hardware (TPU/GPU clusters).
- Establish best practices for MLOps, ensuring model deployment, monitoring, and rollback strategies are enterprise-grade.
- Collaborate with product and engineering teams to translate complex AI capabilities into user-centric features.
- Ensure data privacy, security compliance, and ethical AI usage in all architectural designs.
- Prototype novel algorithms and proof-of-concepts to validate technical feasibility before full-scale production.
Qualifications
- Master’s degree or PhD in Computer Science, Machine Learning, or a related technical field.
- 10+ years of experience in software engineering with a strong focus on AI/ML infrastructure.
- Deep expertise in training and fine-tuning Large Language Models (e.g., LLaMA, GPT architectures, Mistral).
- Proficiency in programming languages such as Python, C++, and Rust.
- Hands-on experience with deep learning frameworks (PyTorch, TensorFlow, JAX) and cloud platforms (AWS, GCP, or Azure).
- Strong understanding of MLOps tools (MLflow, Kubeflow, Airflow) and containerization (Docker, Kubernetes).
- Exceptional problem-solving skills and the ability to architect systems for 10x scale growth.