Job Description
We are defining the intelligence layer for the next decade. Aether Dynamics is looking for a visionary Senior Generative AI Architect to spearhead our mission in building autonomous, high-performance AI agents. As we prepare for the 2026 technological landscape, we need a leader who can bridge the gap between cutting-edge research and scalable production engineering.
In this role, you will architect the core infrastructure for our proprietary large language models, ensuring they are not only capable but safe, efficient, and compliant. You will work in a high-impact environment where your code will directly shape the future of enterprise automation.
Responsibilities
- Architect and implement scalable Generative AI pipelines and large language model (LLM) infrastructures using Python and modern MLOps practices.
- Optimize model performance through advanced techniques including quantization, pruning, and model distillation to reduce inference costs.
- Design and integrate Retrieval-Augmented Generation (RAG) systems to enhance factual accuracy and reduce hallucination rates.
- Lead the development of AI Agents capable of multi-step reasoning and autonomous tool execution.
- Establish best practices for prompt engineering, fine-tuning strategies, and continuous model evaluation.
- Collaborate with product and security teams to ensure AI safety, ethics, and regulatory compliance.
- Mentor junior engineers and contribute to the technical roadmap for our AI capabilities.
Qualifications
- Master’s degree in Computer Science, Machine Learning, or a related quantitative field (PhD preferred).
- Minimum of 6 years of experience in software engineering, with at least 3 years focused on AI/ML and NLP.
- Deep proficiency in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
- Extensive experience deploying LLMs in production, including knowledge of serving frameworks like vLLM or Ray Serve.
- Strong understanding of vector databases (Pinecone, Weaviate, Milvus) and semantic search.
- Familiarity with cloud native technologies (AWS, GCP, Kubernetes) and containerization (Docker).
- Proven track record of delivering complex AI products from concept to launch.