Job Description
We are at the precipice of a technological paradigm shift. As a Lead AI Architect at Nebula Future Systems, you won't just be writing code; you will be architecting the intelligence layer that will define the digital landscape of 2026 and beyond. We are seeking a visionary engineer to lead our Generative AI division, focusing on Agentic Workflows, Large Language Model (LLM) fine-tuning, and the ethical deployment of autonomous AI agents.
Why Join Us?
- Shape the Future: Work on bleeding-edge projects that are setting the standard for the next generation of human-machine interaction.
- Impact at Scale: Your work will power solutions used by millions, influencing how industries operate in the near future.
- Top-Tier Compensation: Competitive salary, equity packages, and comprehensive benefits designed for high-performers.
If you are passionate about the potential of Artificial General Intelligence (AGI) and want to build the tools that drive it, we want to hear from you.
Responsibilities
- Architect and deploy scalable, high-performance LLM applications and RAG (Retrieval-Augmented Generation) pipelines.
- Lead the research and implementation of Agentic AI workflows, enabling autonomous decision-making capabilities.
- Ensure model accuracy, safety, and alignment through rigorous testing, validation, and ethical oversight protocols.
- Collaborate with cross-functional teams of data scientists, product managers, and security experts to translate complex AI concepts into user-centric solutions.
- Optimize model inference latency and resource utilization for production environments.
- Mentor junior engineers and establish best practices for MLOps and AI governance.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
- 8+ years of professional experience in software engineering, with at least 3 years dedicated to Machine Learning and NLP.
- Deep expertise in Python, PyTorch, or TensorFlow.
- Proven experience working with state-of-the-art models (e.g., GPT-4, Claude, Llama) and experience in model fine-tuning or LoRA adapters.
- Strong understanding of vector databases (e.g., Pinecone, Milvus, Weaviate) and embeddings.
- Demonstrated ability to manage complex technical projects and drive technical strategy from conception to deployment.