Job Description
Welcome to the future of intelligence. Nexus Horizon is seeking a visionary Agentic AI Engineer 2026 to pioneer the next generation of autonomous systems. In this role, you won't just build models; you will architect ecosystems where AI agents collaborate, reason, and execute complex workflows independently.
As we prepare for the paradigm shift of 2026, we need a technical leader who understands the nuances of self-governing agents. You will work at the intersection of LLMs, Reinforcement Learning, and scalable distributed systems to build the infrastructure of tomorrow.
Why join us?
- Shape the roadmap for the next evolution of AI autonomy.
- Work with state-of-the-art hardware and cloud infrastructure.
- Competitive equity package and top-tier benefits.
Responsibilities
- Architect Multi-Agent Systems: Design robust frameworks for autonomous AI agents capable of complex reasoning, planning, and tool use.
- Orchestration & Workflow: Implement advanced orchestration layers to manage agent lifecycles, memory retention, and inter-agent communication.
- Model Optimization: Fine-tune and optimize large language models (LLMs) for specific agentic tasks to maximize accuracy and reduce hallucinations.
- Evaluation & Safety: Establish rigorous evaluation pipelines to measure agent performance and ensure safe, reliable autonomous operation.
- Scalability: Build scalable backend services that handle high-throughput inference and real-time agent interactions.
- Research Integration: Stay at the forefront of AI research, integrating cutting-edge papers and techniques into production systems.
Qualifications
- Experience: 5+ years of software engineering experience with 2+ years in AI/ML or LLM development.
- Technical Stack: Proficiency in Python, PyTorch, or TensorFlow; experience with LangChain or LlamaIndex.
- System Design: Strong understanding of distributed systems, API design, and microservices architecture.
- AI Mastery: Deep understanding of transformer architectures, prompt engineering, and reinforcement learning principles.
- Education: BS, MS, or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Soft Skills: Exceptional problem-solving skills and the ability to communicate complex technical concepts to diverse stakeholders.