Job Description
We are looking for a Senior Generative AI Architect to help define the roadmap for our AI infrastructure through the year 2026 and beyond. In a world rapidly moving toward agentic AI, you will be at the forefront of building systems that reason, plan, and interact autonomously.
About the Role: You will lead the architecture and implementation of proprietary Large Language Models (LLMs) and multimodal systems. This is not just about coding; it's about defining how intelligent agents will interact with the digital economy.
Key Highlights:
- Work with cutting-edge transformer architectures.
- Drive the integration of AI agents into enterprise workflows.
- Shape the technical strategy for the next 3 years.
Responsibilities
- Strategic Architecture: Design scalable, secure, and efficient AI infrastructure capable of handling enterprise-grade workloads.
- Model Development: Lead the fine-tuning, alignment, and evaluation of LLMs using state-of-the-art techniques (RLHF, DPO).
- Agentic Systems: Develop and deploy autonomous AI agents that can perform complex, multi-step tasks in production environments.
- MLOps Implementation: Establish robust CI/CD pipelines for machine learning, ensuring continuous integration and delivery of model updates.
- Research & Innovation: Stay ahead of industry trends in AI safety, fairness, and efficiency, applying new research to our products.
- Technical Leadership: Mentor junior engineers and collaborate with cross-functional teams to translate business requirements into technical solutions.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related field.
- Experience: 7+ years of experience in software engineering and machine learning, with at least 3 years specifically in Generative AI/LLMs.
- Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, and Rust. Experience with LangChain, LlamaIndex, or similar frameworks is highly preferred.
- Knowledge: Strong understanding of transformer models, attention mechanisms, and neural network optimization techniques.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems in high-pressure environments.
- Communication: Excellent written and verbal communication skills for technical documentation and stakeholder presentations.