Job Description
We are on the precipice of a new era in artificial intelligence. As we look toward 2026, we are seeking a Senior AI Architect to lead the charge in deploying autonomous, scalable, and ethical AI agents. You won't just be writing code; you will be defining the infrastructure that powers the next generation of intelligent applications.
In this role, you will bridge the gap between theoretical machine learning and real-world, high-impact engineering. We are looking for a visionary who is obsessed with performance, scalability, and responsible AI development.
Responsibilities
- Architect Next-Gen AI Systems: Design and deploy large-scale machine learning pipelines capable of handling millions of requests per day, optimized for the infrastructure landscape of 2026.
- Model Optimization: Implement advanced quantization, pruning, and distillation techniques to reduce inference costs by up to 80% while maintaining high accuracy.
- Retrieval-Augmented Generation (RAG): Lead the integration of knowledge graphs and vector databases to ensure AI outputs are grounded in verified, real-time data.
- Ethical AI Oversight: Establish and enforce rigorous guidelines for bias detection, data privacy, and safety alignment in our generative models.
- Technical Leadership: Mentor a team of junior engineers and data scientists, conducting code reviews and architectural planning sessions.
- Production MLOps: Build robust CI/CD pipelines for machine learning models, ensuring seamless deployment, monitoring, and rollback capabilities.
Qualifications
- Experience: 5+ years of professional experience in software engineering and machine learning, with at least 2 years specifically focused on Large Language Models (LLMs) and Generative AI.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with frameworks like LangChain or HuggingFace.
- Education: Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s degree or PhD is preferred.
- System Design: Deep understanding of distributed systems, cloud infrastructure (AWS/Azure/GCP), and containerization technologies (Docker/Kubernetes).
- Problem Solving: Proven ability to debug complex, multi-layered systems and optimize performance under heavy load.
- Communication: Exceptional ability to translate complex technical concepts into clear, actionable strategies for non-technical stakeholders.