Job Description
We are looking for a visionary Senior Agentic AI Engineer to help define the intelligence layer for the year 2026. At Nexus Future Systems, we are building autonomous systems capable of complex reasoning, multi-agent collaboration, and self-improvement. If you are passionate about the future of Artificial General Intelligence and want to architect the tools that will define the next decade of technology, we want to meet you.
As part of our elite '2026' research division, you will work at the intersection of large language models (LLMs), reinforcement learning, and distributed systems. You will be responsible for creating scalable agent architectures that can operate independently in dynamic environments.
Responsibilities
- Architect Multi-Agent Systems: Design and implement robust frameworks for autonomous agents capable of complex task delegation and execution.
- Optimize LLM Inference: Improve latency and reduce token costs for high-volume generative AI applications.
- Develop Self-Improving Algorithms: Create feedback loops where AI models learn and refine their outputs based on real-world performance metrics.
- Collaborate on 2026 Roadmap: Work closely with product leaders to translate futuristic concepts into tangible, deployable software solutions.
- Ensure Ethical AI: Implement guardrails and safety protocols to prevent hallucinations and ensure alignment with human values.
- Mentor Junior Engineers: Guide a team of ML researchers and software developers in best practices for AI engineering.
Qualifications
- Education: MS or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of experience in Machine Learning, specifically with PyTorch, TensorFlow, or JAX.
- Core Skills: Deep understanding of Large Language Models (GPT-4, Llama 3), RAG (Retrieval-Augmented Generation), and fine-tuning methodologies.
- Programming: Proficiency in Python and experience with distributed computing systems (Kubernetes, Ray, or Spark).
- Problem Solving: Proven track record of solving complex algorithmic problems in high-pressure environments.
- Communication: Ability to articulate complex technical concepts to non-technical stakeholders.