Job Description
Build the Future of Intelligence with Us
We are seeking a visionary Senior Agentic AI Engineer to join the 2026 Initiative. In a world rapidly transitioning from static models to autonomous agents, you will architect the systems that define the next generation of human-machine interaction. You won't just be writing code; you will be building the cognitive infrastructure of tomorrow.
At Quantum Horizon Systems, we are pioneers in the 2026 niche, focusing on self-improving agents, multi-agent orchestration, and next-gen LLM reasoning. If you are obsessed with scalability, efficiency, and the bleeding edge of artificial general intelligence, this is your stage.
Why Join Us?
- Work on projects that are shaping the technological landscape of 2026.
- Competitive compensation and equity packages.
- Flexible remote-first culture with top-tier benefits.
Responsibilities
- Architect Multi-Agent Systems: Design and implement complex agent topologies that can autonomously plan, execute, and learn from complex tasks.
- Orchestration Excellence: Build robust middleware to manage communication between disparate AI agents, ensuring seamless data flow and error handling.
- Prompt Engineering & Logic: Develop sophisticated prompt chains and logical reasoning loops to enhance the decision-making capabilities of our agents.
- Model Optimization: Fine-tune and optimize open-source models for specific niche applications, reducing latency and increasing accuracy.
- R&D Leadership: Stay ahead of the curve in the 2026 tech landscape, researching new paradigms in autonomous systems and proposing innovative solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional experience in Machine Learning, NLP, or Software Engineering.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with LLM frameworks like LangChain, LangGraph, or AutoGen.
- Domain Knowledge: Deep understanding of prompt engineering, vector databases, and agent-based workflows.
- Problem Solving: Demonstrated ability to solve complex architectural problems in high-stakes environments.