Job Description
We are Nexus Horizon Labs, a pioneering force in the next generation of Artificial Intelligence. As we accelerate towards our 2026 Roadmap, we are seeking a visionary Senior Generative AI Engineer to lead the development of autonomous Agentic AI systems. You will be at the forefront of building the intelligent infrastructure that powers the next evolution of digital interaction.
Why Join Us?
• Impactful Work: Build systems that redefine how machines understand and execute complex tasks autonomously.
• Future-Ready: Work with cutting-edge LLMs, Vector Databases, and Reinforcement Learning from Human Feedback (RLHF).
• Competitive Package: Comprehensive benefits, equity, and a flexible remote-first culture.
The Role
In this pivotal role, you will architect and deploy scalable AI agents capable of reasoning, planning, and executing multi-step workflows in real-world environments.
Responsibilities
- Architect Agentic Workflows: Design and implement complex, multi-step AI agent architectures that leverage LLMs for autonomous decision-making and task execution.
- Model Optimization: Fine-tune and optimize large language models (LLMs) for specific domain applications, focusing on reduced latency and high accuracy.
- RAG Pipelines: Build and maintain robust Retrieval-Augmented Generation (RAG) systems to ensure agents have access to up-to-date, reliable knowledge bases.
- System Evaluation: Develop rigorous evaluation frameworks and benchmarks to measure the performance, safety, and reliability of AI agents.
- Cross-Functional Collaboration: Partner with product managers and engineers to translate business requirements into technical AI solutions.
- Research & Innovation: Stay ahead of industry trends in Generative AI and implement emerging techniques to keep our technology competitive.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in software engineering with a strong focus on AI/ML.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and modern NLP libraries (Hugging Face, spaCy).
- LLM Expertise: Deep understanding of Large Language Models, including fine-tuning methods (LoRA, QLoRA) and prompt engineering.
- Tooling: Experience with vector databases (Pinecone, Weaviate, Milvus) and orchestration frameworks (LangChain, LlamaIndex).
- Problem Solving: Proven track record of solving complex engineering challenges in high-scale production environments.