Job Description
Are you ready to architect the future of intelligent automation? Nexus Horizon Labs is seeking a visionary Senior Agentic AI Engineer to lead our R&D efforts for the 2026 AI Evolution.
We are building the next generation of autonomous systems that don't just process data—they think, reason, and act independently. If you are passionate about pushing the boundaries of Large Language Models (LLMs) and building self-driving agents, this is your opportunity to define the industry standard.
Why Join Us?
- Future-Proof Role: Directly contribute to our 2026 strategic roadmap for autonomous AI.
- Top-Tier Compensation: Competitive salary, equity, and comprehensive benefits.
- Innovation-First Culture: Work with state-of-the-art tools and a world-class engineering team.
Location: San Francisco, CA (Hybrid)
We are looking for a self-starter who thrives in a fast-paced environment and is ready to solve complex problems at the intersection of deep learning and software engineering.
Responsibilities
- Architect Agentic Systems: Design and implement advanced autonomous agents capable of multi-step reasoning, planning, and tool execution using LLMs.
- Model Optimization: Fine-tune and optimize foundation models (LLMs) for specific enterprise use cases to enhance performance and reduce hallucination rates.
- RAG Implementation: Build and maintain Retrieval-Augmented Generation pipelines to ensure agents have access to real-time, accurate knowledge.
- System Scalability: Develop scalable MLOps infrastructure to handle high-throughput inference and continuous model training pipelines.
- Research & Development: Stay at the forefront of AI research, evaluating new architectures (e.g., Transformers, Diffusion, MoE) and integrating them into our product suite.
- Collaboration: Partner with product managers and data scientists to translate complex business requirements into elegant AI solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related field.
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or NLP.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX.
- Domain Knowledge: Deep understanding of Transformer architectures, Attention mechanisms, and prompt engineering.
- Tooling: Experience with orchestration frameworks (LangChain, LlamaIndex) and vector databases (Pinecone, Milvus).
- Problem Solving: Demonstrated ability to debug complex distributed systems and optimize for latency and throughput.