Job Description
Are you ready to architect the intelligent systems of tomorrow? Nexus Horizon is at the forefront of the AI revolution, building autonomous agents that redefine human-machine collaboration. We are looking for a visionary Senior Agentic AI Engineer to lead the development of next-generation LLM-powered systems.
In this role, you won't just be building models; you will be building ecosystems of intelligent agents capable of autonomous reasoning, complex decision-making, and seamless multi-modal interaction. Join a team of world-class researchers and engineers committed to pushing the boundaries of what's possible in 2026 and beyond.
Responsibilities
- Architect Agentic Systems: Design and implement scalable multi-agent frameworks using LangChain and AutoGen to enable autonomous task execution.
- Model Optimization: Fine-tune and optimize Large Language Models (LLMs) for specific enterprise use cases, focusing on retrieval-augmented generation (RAG) and context-aware reasoning.
- Pipeline Development: Build robust, high-throughput data pipelines to support continuous model training and evaluation.
- System Integration: Integrate AI agents with existing enterprise infrastructure and third-party APIs to create seamless end-to-end solutions.
- Ethical AI & Safety: Implement guardrails and safety protocols to ensure AI outputs are compliant, bias-free, and secure.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of innovation and technical excellence.
Qualifications
- Experience: 5+ years of professional experience in Machine Learning, NLP, or AI Engineering.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and modern deep learning frameworks.
- LLM Expertise: Deep understanding of transformer architectures, fine-tuning techniques, and prompt engineering strategies.
- Tools: Hands-on experience with Hugging Face, OpenAI API, vector databases (Pinecone/Weaviate), and orchestration tools (LangChain, LlamaIndex).
- Education: Master’s degree in Computer Science, Machine Learning, or a related field (or equivalent practical experience).
- Problem Solving: Demonstrated ability to tackle complex, ambiguous problems with creative technical solutions.