Job Description
Build the Intelligence Layer for the Future
Are you ready to architect the intelligence layer for the next decade? Nexus Horizon is seeking a visionary AI Systems Architect to lead the development of autonomous agents and multi-modal AI systems that will define the landscape in 2026 and beyond. This is not just a coding role; this is a strategic position at the forefront of the Agentic AI revolution.
In this role, you will bridge the gap between cutting-edge machine learning research and scalable, production-grade enterprise infrastructure. You will be responsible for designing the systems that allow AI agents to reason, plan, and execute complex tasks autonomously.
Why Join Us?
- Future-First Vision: Work on a roadmap specifically engineered for the 2026 technological paradigm shift.
- High Impact: Your work will directly influence how enterprises interact with autonomous intelligence.
- Elite Team: Collaborate with Ph.D. researchers and senior engineers from top-tier tech firms.
Responsibilities
- Architect Agentic Workflows: Design and implement complex, multi-step autonomous agent workflows using LLMs, vector databases, and orchestration frameworks (e.g., LangChain, AutoGen).
- System Optimization: Engineer high-performance inference pipelines to minimize latency and reduce operational costs at scale.
- Model Integration: Integrate and fine-tune proprietary and open-source foundation models to fit specific domain requirements.
- Roadmap Leadership: Define the technical strategy for the 2026 AI evolution, identifying emerging technologies like spatial computing and quantum-ready algorithms.
- Security & Compliance: Implement robust guardrails and ethical AI principles to ensure safe deployment of autonomous agents.
- Cross-Functional Collaboration: Partner with product managers and data scientists to translate business requirements into technical architecture.
Qualifications
- Deep Technical Expertise: 5+ years of experience in software engineering, with at least 2 years specifically in Machine Learning, NLP, or AI Systems.
- Framework Mastery: Proficient in Python, C++, and modern AI frameworks (PyTorch, TensorFlow, JAX).
- Orchestration Skills: Strong experience with LLM orchestration tools (LangChain, LlamaIndex) and knowledge graph construction.
- Infrastructure Knowledge: Experience designing systems on cloud platforms (AWS, GCP) with a focus on serverless and containerized environments (Docker, Kubernetes).
- Research Acumen: Ability to read and implement state-of-the-art research papers (e.g., from NeurIPS, ICML) into production code.
- Problem Solving: Demonstrated ability to solve complex, non-trivial engineering challenges in dynamic environments.