Job Description
Architect the Future of Intelligence
At Nexus Horizon, we are building the infrastructure for the year 2026. As a Senior AI Architect, you will design the backbone of our next-generation autonomous agents and generative AI ecosystems. We are looking for a visionary leader who thrives in ambiguous environments and is obsessed with scalability, latency, and ethical AI deployment.
Our Vision
We are transitioning from static models to dynamic, self-evolving AI agents. You will be responsible for the architecture that powers this shift, ensuring our systems are robust, secure, and ready for the demands of a hyper-connected future.
What You'll Do
- Lead the architectural design of multi-modal AI systems and large language model (LLM) fine-tuning pipelines.
- Design high-throughput, low-latency inference engines capable of serving millions of concurrent requests.
- Implement and optimize MLOps strategies to streamline model deployment and monitoring.
- Collaborate with cross-functional teams to define product roadmaps aligned with 2026 technology trends.
- Ensure data privacy, security, and compliance across all AI workloads.
- Research emerging paradigms in AI, including Agentic workflows and Neural Symbolic AI.
Requirements
- 10+ years of experience in software engineering, with at least 5 years specifically in Machine Learning Engineering or AI Architecture.
- Deep expertise in Python, PyTorch, and TensorFlow.
- Proven experience designing systems using Vector Databases (e.g., Pinecone, Milvus) and Retrieval-Augmented Generation (RAG) architectures.
- Strong background in distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Experience with model quantization, pruning, and optimization techniques.
- Excellent communication skills and the ability to translate technical concepts for diverse stakeholders.
Benefits
Competitive equity package, fully remote-first culture, and continuous learning stipends.
Responsibilities
- Lead the architectural design of multi-modal AI systems and large language model (LLM) fine-tuning pipelines.
- Design high-throughput, low-latency inference engines capable of serving millions of concurrent requests.
- Implement and optimize MLOps strategies to streamline model deployment and monitoring.
- Collaborate with cross-functional teams to define product roadmaps aligned with 2026 technology trends.
- Ensure data privacy, security, and compliance across all AI workloads.
- Research emerging paradigms in AI, including Agentic workflows and Neural Symbolic AI.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically in Machine Learning Engineering or AI Architecture.
- Deep expertise in Python, PyTorch, and TensorFlow.
- Proven experience designing systems using Vector Databases (e.g., Pinecone, Milvus) and Retrieval-Augmented Generation (RAG) architectures.
- Strong background in distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Experience with model quantization, pruning, and optimization techniques.
- Excellent communication skills and the ability to translate technical concepts for diverse stakeholders.